阅读说明：本技术 投运效果分析、数据处理方法、装置、设备及存储介质 (Commissioning effect analysis method, commissioning effect data processing method, commissioning effect analysis device, commissioning effect data processing device, commissioning effect equipment and) 是由 占怀旻 叶鲁彬 戢洋 于 2020-05-20 设计创作，主要内容包括：本申请实施例提供一种投运效果分析、数据处理方法、装置、设备及存储介质。在数据处理方法中,对设备进行自动投运时,检测设备在自动投运下的运行数据,可得到投运操作后运行参数的实际值；基于投运操作对应的运行参数的推荐值和实际值,可自动分析运行参数的投运效果,实现了投运效果的智能化分析,灵活度更高,且极大提升了分析结果的可靠性。(The embodiment of the application provides a commissioning effect analysis method, a commissioning effect data processing method, a commissioning effect analysis device, a commissioning effect data processing device, equipment and a storage medium. In the data processing method, when the equipment is automatically put into operation, the operation data of the equipment in the automatic operation is detected, and the actual value of the operation parameter after the operation is obtained; based on the recommended value and the actual value of the operation parameter corresponding to the commissioning operation, the commissioning effect of the operation parameter can be automatically analyzed, the intelligent analysis of the commissioning effect is realized, the flexibility is higher, and the reliability of the analysis result is greatly improved.)

1. A method for analyzing commissioning effect of industrial equipment is characterized by comprising the following steps:

acquiring a commissioning value for automatically commissioning the industrial equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; the industrial equipment belongs to the field of process manufacturing;

detecting operation data of the industrial equipment under the automatic operation, and acquiring an actual value of the first operation parameter under the at least one operation from the operation data;

and analyzing the commissioning effect of the first operation parameter according to the recommended value of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

2. A data processing method, comprising:

acquiring a commissioning value for automatically commissioning equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter;

detecting operation data of the equipment under the automatic commissioning, and acquiring an actual value of the first operation parameter under the at least one commissioning operation from the operation data;

and analyzing the commissioning effect of the first operation parameter according to the recommended value of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

3. The method of claim 2, further comprising:

visually displaying the at least one commissioning operation on a page;

and responding to the selected operation of the target operation in the at least one operation, and displaying the operation detail data corresponding to the target operation.

4. The method of claim 2, wherein detecting operational data of the device in the automatic commissioning comprises:

in the automatic commissioning process, sampling the parameter value of the first operation parameter according to a set sampling frequency; the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation; alternatively, the first and second electrodes may be,

and sampling the parameter value of the first operation parameter within a set time range after the operation of the first operation parameter is executed each time.

5. The method of claim 4, wherein obtaining from the operational data an actual value of the first operational parameter at each of the at least one commissioning operations comprises:

acquiring a plurality of sampling points obtained by sampling parameter values of the first operating parameters;

combining the plurality of sampling points and the recording nodes corresponding to the at least one commissioning operation according to the time correspondence to obtain combined data;

for any one commissioning operation in the at least one commissioning operation, determining a set ordered sampling point behind a recording node corresponding to the commissioning operation from the merged data, and taking the sampling point as a target sampling point;

and determining an actual value corresponding to the commissioning operation according to the parameter value corresponding to the target sampling point.

6. The method of claim 2, wherein analyzing the commissioning effect of the first operating parameter based on the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter at the at least one commissioning operation comprises:

determining a manually-intervened commissioning operation from the at least one commissioning operation according to the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation;

and analyzing the number of manual interventions in the at least one commissioning operation according to the commissioning operation of the manual interventions.

7. The method of claim 6, wherein determining a manually-intervened commissioning operation from the at least one commissioning operation as a function of the respective recommended value of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter at the at least one commissioning operation comprises:

calculating a difference between a recommended value and an actual value of the commissioning operation for any of the at least one commissioning operation;

and if the difference is larger than the statistical threshold of the first operation parameter, determining that the commissioning operation is a commissioning operation of manual intervention.

8. The method of claim 7, further comprising:

acquiring a historical recommended value and a historical actual value of the first operating parameter without manual intervention from a historical commissioning record;

calculating a parameter value floating range of the first operation parameter without manual intervention according to the historical recommended value and the historical actual value;

and determining a statistical threshold value of the first operating parameter according to the parameter value floating range.

9. The method of claim 8, wherein obtaining the historical recommended value and the historical actual value of the first operating parameter without human intervention from a historical commissioning record comprises:

obtaining a target historical commissioning record matched with the type of the equipment from the historical commissioning records;

and acquiring a historical recommended value and a historical actual value of the first operation parameter without manual intervention from the target historical commissioning record.

10. The method of claim 7, further comprising:

and if the commissioning operation is a commissioning operation of manual intervention, analyzing a manual intervention reason corresponding to the commissioning operation according to a numerical range to which a difference value between a recommended value and an actual value of the commissioning operation belongs.

11. The method according to any one of claims 6-10, further comprising:

and aiming at the commissioning operation of the manual intervention, collecting environmental data of the equipment at the time of the manual intervention so as to optimize the recommendation algorithm of the first operation parameter according to the environmental data.

12. A data processing apparatus, comprising:

a data acquisition module to: acquiring a commissioning value for automatically commissioning equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; detecting operation data of the equipment under the automatic commissioning, and acquiring an actual value of the first operation parameter under the at least one commissioning operation from the operation data;

an analysis module to: and analyzing the commissioning effect of the first operation parameter according to the recommended value of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

13. A data processing apparatus, characterized by comprising: a memory, a processor, and a communication component;

the memory is to store one or more computer instructions;

the processor is to execute the one or more computer instructions to: performing the steps of the method of any one of claims 1-11.

14. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the method of any one of claims 1 to 11.

Technical Field

The application relates to the technical field of intelligent control, in particular to a commissioning effect analysis method, a commissioning effect data processing method, a commissioning effect analysis device, a commissioning effect data processing device and a storage medium.

Background

At present, the production process of flow manufacturing enterprises (such as cement and chemical industry) realizes automatic commissioning. In the automatic operation Process, an intelligent algorithm can be used for predicting parameter values required by operation parameters of the production equipment, an instruction corresponding to the parameter values is sent to an Advanced Process Control (APC), and then the APC controls the production equipment through a Distributed Control System (DCS).

When the automatic operation is carried out, the management personnel can carry out manual intervention according to the production requirement or the operation state of the production equipment. In order to analyze the prediction effect of the intelligent algorithm, statistics needs to be carried out on the manual intervention condition in the automatic commissioning process. In the prior art, manual statistics is usually carried out manually, and the reliability of the mode is poor. Therefore, a solution is yet to be proposed.

Disclosure of Invention

Aspects of the present application provide a commissioning effect analysis method, a commissioning effect data processing method, a commissioning effect analysis device, a commissioning effect data processing device, and a storage medium, so as to automatically analyze an automatic commissioning effect under algorithm control, and improve flexibility of analysis operations and reliability of analysis results.

The embodiment of the application provides a commissioning effect analysis method of industrial equipment, which comprises the following steps: acquiring a commissioning value for automatically commissioning the industrial equipment; the commissioning value comprises a recommended value for each of at least one commissioning operation; the industrial equipment belongs to the field of process manufacturing; detecting operation data of the industrial equipment under the automatic commissioning, and acquiring actual values corresponding to the at least one commissioning operation from the operation data; and analyzing the commissioning effect of the automatic commissioning according to the recommended value of the at least one commissioning operation and the actual value corresponding to the at least one commissioning operation.

An embodiment of the present application provides a data processing method, including: acquiring a commissioning value for automatically commissioning equipment; the commissioning value comprises a recommended value for each of at least one commissioning operation; detecting operation data of the equipment under the automatic commissioning, and acquiring actual values corresponding to the at least one commissioning operation from the operation data; and analyzing the commissioning effect of the automatic commissioning according to the recommended value of the at least one commissioning operation and the actual value corresponding to the at least one commissioning operation.

An embodiment of the present application further provides a data processing apparatus, including: a data acquisition module to: acquiring a commissioning value for automatically commissioning equipment; the commissioning value comprises a recommended value for each of at least one commissioning operation; detecting operation data of the equipment under the automatic commissioning, and acquiring actual values corresponding to the at least one commissioning operation from the operation data; an analysis module to: and analyzing the commissioning effect of the automatic commissioning according to the recommended value of the at least one commissioning operation and the actual value corresponding to the at least one commissioning operation.

An embodiment of the present application further provides a data processing apparatus, including: a memory, a processor, and a communication component; the memory is to store one or more computer instructions; the processor is to execute the one or more computer instructions to: the operation effect analysis method or the data processing method of the industrial equipment provided by the embodiment of the application is executed.

The embodiment of the present application further provides a computer-readable storage medium storing a computer program, and the computer program, when executed by a processor, can implement the commissioning effect analysis method or the data processing method of the industrial device provided in the embodiment of the present application.

In the data processing method provided by the embodiment of the application, when the equipment is automatically put into operation, the operation data of the equipment in the automatic operation is detected, and the actual value of the operation parameter after the operation is obtained; based on the recommended value and the actual value of the operation parameter corresponding to the commissioning operation, the commissioning effect of the operation parameter can be automatically analyzed, the intelligent analysis of the commissioning effect is realized, the flexibility is higher, and the reliability of the analysis result is greatly improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1 is a flow chart of a data processing method provided by an exemplary embodiment of the present application;

FIG. 2a is a schematic diagram illustrating commissioning effects provided by an exemplary embodiment of the present application;

FIG. 2b is a schematic diagram of generating consolidated data as provided by an exemplary embodiment of the present application;

fig. 3 is a schematic flowchart of a commissioning effect analysis method for an industrial device according to an exemplary embodiment of the present application;

fig. 4 is a schematic diagram of a variation of an actual value of a first operating parameter according to an embodiment of an application scenario of the present application;

FIG. 5 is a schematic flow chart diagram of a data processing apparatus according to an exemplary embodiment of the present application;

fig. 6 is a schematic structural diagram of a data processing device according to an exemplary embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In the prior art, manual statistics and analysis are carried out on data generated in the commissioning process by manpower. When the commissioning data is counted manually, accurate statistics is not easy to be carried out under the scene with high commissioning frequency; when the commissioning data is manually analyzed, subjective ideas are easily introduced, and accurate analysis results are not easily obtained; in addition, the above statistics and analysis operations consume too much labor cost and are not easy to be flexibly popularized. In order to solve the above technical problem, in some embodiments of the present application, a solution is provided, which will be exemplarily described below with reference to the accompanying drawings.

Fig. 1 is a schematic flowchart of a data processing system according to an exemplary embodiment of the present application, and as shown in fig. 1, the method includes:

step 101, acquiring a commissioning value for automatically commissioning equipment; the commissioning values include recommended values for each of at least one commissioning operation of the first operational parameter.

Step 102, detecting operation data of the equipment under the automatic commissioning, and acquiring an actual value of the first operation parameter under the at least one commissioning operation from the operation data.

103, analyzing the commissioning effect of the first operation parameter according to the recommended value of the at least one commissioning operation of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

The equipment refers to a general term of labor data and material data which can be used by individuals or enterprises for a long time in production and basically keep the original physical form and function in repeated use.

The implementation form of the device is different in different production scenarios, and the following exemplary description is provided. For example, in the cement manufacturing industry, a typical plant may include: cement rotary kiln, cyclone preheater, cooler, etc. For example, in the steel production industry, a typical plant may include: blast furnace, hot-blast furnace, converter, electric furnace, refining furnace, conticaster, etc. For example, in the chip manufacturing industry, a typical device may include: photoetching machine, scribing machine, die bonder, wire bonder and other equipment; for example, in the food processing industry, a typical apparatus may include: quick-freezing equipment, sorting equipment, cleaning equipment, sterilizing equipment, a food canning machine, an automatic capping machine, a labeling machine, a box filling machine, an empty package detection machine and the like. As another example, in the chemical industry, a typical production facility may include: fans, compressors, pumps, separation equipment, electrolyzers, reactors, filters, crushers, centrifugal separators, rotary kilns, blenders, dryers and the like.

Commissioning refers to a process of configuring a set value for an operation parameter of a device, making the device have an operation condition, and then commissioning a working system to operate. The automatic commissioning refers to adopting a specific algorithm, automatically calculating a proper value for the operation parameter of the equipment, and directly or indirectly issuing a control instruction to the commissioned equipment according to the value calculated by the algorithm so as to automatically control the equipment to operate in a set mode.

For example, in a typical automatic commissioning scenario, data related to the equipment, such as operational data, environmental data, production demand data, etc., may be acquired in real time; next, based on the set automatic commissioning algorithm and the above-described related data, a parameter value required for the operating parameter of the equipment at a future time is predicted. And then, the calculated parameter value is transmitted to an APC system, and the APC system controls the equipment to operate according to the calculated parameter value.

The operation parameters of the equipment comprise any one or more operation parameters on which the operation process of the equipment depends. Such as temperature parameters, humidity parameters, pressure parameters, rotational speed parameters, power parameters, and the like. The first operating parameter refers to any operating parameter, and the term "first" is used herein for convenience of description only.

Among them, the value of the operation parameter issued to the device for realizing the automatic commissioning may be referred to as a commissioning value. In the process of automatic commissioning, one or more commissioning operations may be performed, and different commissioning operations may recommend different parameter values for the same operation parameter, which is not limited in this embodiment.

For example, the automatic commissioning includes 3 commissioning operations corresponding to the temperature parameter, the first commissioning operation recommends a first temperature value for the temperature parameter, the second commissioning operation recommends a second temperature value for the temperature parameter, and the third commissioning operation recommends a third pressure value for the temperature parameter.

Generally, after the automatic commissioning of the equipment, the equipment may be operated according to the recommended values of the operating parameters. In some scenes, after automatic operation, the operation effect of the equipment is not ideal, or the operation effect of the equipment does not meet the production requirement of the user, and the user can perform manual intervention. The manual intervention refers to manually correcting the parameter value of the operating parameter of the equipment. In this case, the apparatus may be operated according to the manually corrected parameter values.

In order to analyze the commissioning effect of the automatic commissioning, the actual values of the operating parameters of the equipment under each commissioning operation can be acquired in the process of carrying out the automatic commissioning. Wherein the actual value is obtained by sampling the actual operation state of the equipment. For each commissioning operation, the commissioning effect corresponding to the commissioning operation can be analyzed according to the recommended value and the actual value corresponding to the commissioning operation. Based on the commissioning effect corresponding to each commissioning operation of the operation parameters, the overall commissioning effect of the operation parameters can be analyzed.

When the commissioning effect is analyzed, the manual intervention condition, the reason of the manual intervention, the operation parameters of the manual intervention and the like in the automatic commissioning can be analyzed. The commissioning effect obtained by the analysis can be used for quantifying the effect of the automatic commissioning algorithm so as to be further used for optimizing the automatic commissioning algorithm.

In this embodiment, when the device is automatically put into operation, the operation data of the device in the automatic operation is detected, and the actual value of the operation parameter after the operation is obtained; based on the recommended value and the actual value of the operation parameter corresponding to the commissioning operation, the commissioning effect of the operation parameter can be automatically analyzed, the intelligent analysis of the commissioning effect is realized, the flexibility is higher, and the reliability of the analysis result is greatly improved.

In the above and following embodiments of the present application, after the commissioning effect corresponding to the first operation parameter is obtained through analysis, the commissioning effect can be further visually displayed. For example, a page may be presented on which at least one commissioning operation of the first operating parameter is visually presented. And responding to the selected operation of the target commissioning operation in the at least one commissioning operation, and displaying commissioning detail data corresponding to the target commissioning operation.

Visualization (Visualization) is a process of converting data into graphics or images by using computer graphics and image processing techniques, and displaying the graphics or images on a screen. For example, the analytical effect may be presented by a data chart, which may include: bar charts (histograms), line charts, pie charts, bar charts, radar charts, funnel charts, data maps, waterfall charts, and the like. Figure 2a illustrates one exemplary implementation of using a line graph to demonstrate commissioning effects. As shown in fig. 2a, a number of commissioning operations are highlighted on the line graph.

The target commissioning operation may be any commissioning operation selected by the user. Optionally, when the commissioning effect corresponding to the target commissioning operation is displayed, a floating window may be displayed on the page, and commissioning detail data corresponding to the target commissioning operation, such as the recommended value, the actual value, and the commissioning time shown in fig. 2a, is displayed in the floating window. Or, the detail page may be displayed, and the commissioning detail data corresponding to the target commissioning operation is displayed on the detail page, which is not illustrated.

Optionally, the execution subject of the above and following embodiments of the present application may be implemented as a cloud computing platform. In some scenarios, a user may access the cloud computing platform through a browser, and the cloud computing platform may display the commissioning effect of the automatic commissioning through a webpage provided by the browser. In other scenarios, the cloud computing platform may issue the commissioning effect to a terminal device of the user, such as a mobile phone, a tablet computer, a computer device, and the like of the user side. The terminal device may show the commissioning effect through a page provided by an application or a plug-in running thereon, which is not limited in this embodiment.

In some optional embodiments, an optional implementation of the operation data of the detection device in the automatic commissioning may be implemented as: and in the automatic commissioning process, the operation data of the equipment is automatically sampled. The sampling operation may be implemented based on various sampling devices, such as a sensor, and the embodiment is not limited.

Optionally, in the automatic commissioning process, according to a set sampling frequency, sampling a parameter value of a first operating parameter of the device; wherein the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation. Furthermore, it is possible to ensure that the actual operating data of the device after each commissioning operation is sampled.

Or, alternatively, the parameter value of the first operating parameter may be sampled within a set time range after each commissioning operation of the first operating parameter is performed. For example, the parameter value of the first operating parameter may be sampled 3 seconds or 5 seconds after each commissioning. The set time range may be determined according to a time interval between two adjacent commissioning operations, which is not limited in this embodiment.

Based on the embodiment, even under the condition of high automatic commissioning frequency, the actual operation data of the equipment can be acquired in time, the automatic analysis of commissioning effect is realized, and the analysis difficulty caused by high-frequency commissioning is overcome.

After the parameter value of the first operating parameter is sampled, a plurality of sampling points can be obtained. In some optional embodiments, optionally, the plurality of sampling points obtained by sampling and the record node corresponding to at least one commissioning operation of the first operating parameter may be combined according to a time correspondence, so as to obtain combined data.

And the recording node corresponding to each commissioning operation is used for recording commissioning time, identification of the commissioned equipment, identification of the commissioned operation parameter, recommended value of the operation parameter and the like corresponding to the commissioning operation. For example, a record node corresponding to a certain commissioning operation may be: the head coal value of the first boiler is set to N at time T.

Wherein, the merging may include: and mixing the sampling points and the recording nodes, and rearranging the mixed points according to the time sequence. That is, the merged data includes recording nodes and sampling points arranged in order of time.

Next, for any one of the at least one commissioning operation, a set ordered sampling point after the recording node corresponding to the commissioning operation is determined from the merged data as a target sampling point. And then, determining an actual value corresponding to the commissioning operation according to the operation data corresponding to the target sampling point.

Optionally, the set ordering may be the first, the second, or the third, and may be determined according to the sampling interval and the control response time of the device, which is not limited in this embodiment. Wherein, the control response time of the equipment refers to the time interval of operating the equipment according to the recommended value after the equipment is put into operation. For example, when the control reaction time of the device is short, the device may quickly receive the recommended value and operate according to the recommended value after performing the commissioning operation. At this time, if the sampling time is longer than the control response time of the device, the operation data corresponding to the first sampling point after the recording node may be used as the actual value corresponding to the commissioning operation.

A typical merge operation may be illustrated in fig. 2b, where in fig. 2b the circles represent the recorded nodes of the commissioning operation of the first operational parameter and the dots represent the sample points of the actual values of the first operational parameter. And combining the plurality of recording boundary nodes and the sampling points according to the commissioning time corresponding to the commissioning operation and the sampling time corresponding to the sampling points, so as to obtain the relation of the recording nodes and the sampling points in the time sequence.

For example, for the recording node a, the first sampling point B after the recording node a may be determined from the merged data; and then, acquiring a parameter value corresponding to the sampling point B as an actual value of commissioning operation corresponding to the recording node A. Alternatively, the second sample point C after the recording node a may be determined from the merged data. And then, acquiring a parameter value corresponding to the sampling point C as an actual value of the commissioning operation corresponding to the recording node A.

Optionally, in some scenarios, the execution main body of the embodiment of the present application is implemented as an electronic device having a data sampling function and a calculation function. In this scenario, the electronic device contains at least two modules, namely: the device comprises a sampling module, a storage module and a calculation module. The sampling module can sample parameter values of operating parameters in the operating process of the equipment and write sampled data into the storage module. The calculation module can acquire sampling data from the storage module and acquire actual values of the operation parameters corresponding to each commissioning operation from the sampling data.

Optionally, in other scenarios, when the execution subject of the embodiment of the present application is a cloud computing platform, the device for sampling the parameter value of the operation parameter of the device may be implemented as a data sampling device (e.g., multiple data sensors) of a third party. And uploading the sampled parameter values to a cloud computing platform by the sampling equipment of the third party, and storing the parameter values in a specified database on the cloud computing platform for subsequent analysis. The specific Database may be implemented as a Time Series Database (TSDB), a streaming data processing platform (e.g., Datahub), a message queue (e.g., Kafka), but the embodiment is not limited thereto.

Optionally, the cloud computing platform and the sampling device of the third party may establish a communication connection, and a specific communication connection manner may be determined according to an actual application scenario. In some exemplary embodiments, the server and the sampling device may communicate with each other wirelessly using wired communication. The WIreless communication mode includes short-distance communication modes such as bluetooth, ZigBee, infrared, WiFi (WIreless-Fidelity), long-distance WIreless communication modes such as LORA, and WIreless communication mode based on a mobile network. When the mobile network is connected through communication, the network format of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), 5G, WiMax, and the like.

In some alternative embodiments, the operation of analyzing the commissioning effect may include, but is not limited to: analyzing whether manual intervention is included in the automatic commissioning, analyzing the number of times of the manual intervention, analyzing the reason of the manual intervention, determining the operating parameters of the manual intervention and the like. The following are exemplary descriptions, respectively.

Optionally, the manually-intervened commissioning operation may be determined from the at least one commissioning operation according to a recommended value corresponding to each of the at least one commissioning operation of the first operating parameter and an actual value of the first operating parameter under the at least one commissioning operation. As can be appreciated from the definition of human intervention, after a commissioning operation is manually dried, the device may not operate according to the recommended value of the commissioning. Based on this, whether there is human intervention can be analyzed by analyzing the difference between the recommended value corresponding to each commissioning operation and the actual value of the equipment.

In some scenarios, for any commissioning operation, if the recommended value and the actual value corresponding to the commissioning operation are different, it may be determined that the commissioning operation was manually intervened.

In other scenes, the precision problem of the sampling equipment is considered, and the difference value between the recommended value and the actual value of any commissioning operation can be calculated; and if the difference is larger than the statistical threshold of the first operation parameter, determining the commissioning operation as a manually-intervened commissioning operation. The statistical threshold of the first operating parameter may be an empirical value, and a user may set different statistical thresholds for different operating parameters. For example, empirically, the statistical threshold corresponding to the temperature parameter may be set to 0.5, and the statistical threshold corresponding to the pressure parameter may be set to 1, which is not limited in this embodiment.

Optionally, in some scenarios, the respective statistical threshold value of each operating parameter may be calculated according to the historical commissioning record. Taking the first operation parameter as an example, the historical recommended value and the historical actual value of the first operation parameter can be obtained from the historical commissioning record when no manual intervention exists; and then, calculating a parameter value floating range of the first operating parameter without manual intervention according to the historical recommended value and the historical actual value, and determining a statistical threshold value of the first operating parameter according to the operating data floating range.

The operation parameters may include temperature parameters, humidity parameters, pressure parameters, rotation speed parameters, power parameters, and the like. In some scenarios, when the sensor is used to detect the operation parameter of the device, the operation parameter may be referred to as a point location of the sensor or a measurement point of the sensor.

For example, assuming that the operating parameter is a temperature parameter, a historical recommended temperature value and an actual operating temperature value may be obtained without human intervention, and a floating range of the temperature value may be calculated according to a difference between the historical recommended temperature value and the actual operating temperature value. The floating range of temperature values is then used as a statistical threshold for the commissioning operation. This will be described below with reference to a specific example.

For example, assuming that commissioning operation is performed on the temperature parameter of the device, the difference between the historically recommended temperature value and the actually operating temperature value is 0.05 ℃ without human intervention, and 0.05 ℃ may be used as the statistical threshold of the temperature parameter. That is, if the difference between the recommended value and the actual value of a certain commissioning operation corresponding to the temperature parameter is greater than 0.05 ℃, the commissioning operation may be considered to be subject to manual intervention.

It should be noted that, in some scenarios, when the statistical threshold is calculated according to the historical commissioning records, the granularity of the historical commissioning records may be further subdivided to obtain the respective historical commissioning records of each type of device, and the statistical threshold corresponding to each type of device is calculated according to the respective historical commissioning records of each type of device. Based on the mode, the reaction capability of different types of equipment to automatic operation is fully considered, and the accuracy of the statistical result is improved.

Based on the above, optionally, when the statistical threshold corresponding to the first operation parameter is obtained, the type of the device to which the first operation parameter belongs (i.e., the type of the commissioned device) may be obtained. Then, a target historical commissioning record matched with the type of the equipment is obtained from the historical commissioning records, and a historical recommended value and a historical actual value of the first operation parameter without human intervention are obtained from the target historical commissioning record. And then, calculating a parameter value floating range of the first operating parameter according to the historical recommended value and the historical actual value, and determining a statistical threshold value of the first operating parameter according to the parameter value floating range.

For example, if there is no manual intervention in the blast furnace, the difference between the historically recommended temperature value of the blast furnace and the actual operating temperature value of the blast furnace is 0.01 ℃, and then 0.01 ℃ may be used as the statistical threshold corresponding to the temperature parameter of the blast furnace. For another example, if the difference between the historically recommended sintering furnace temperature value and the actual operating temperature value of the sintering furnace is 0.03 ℃ without human intervention, 0.03 ℃ may be used as the statistical threshold corresponding to the temperature parameter of the sintering furnace.

Based on the above, when the commissioning operation is the recommended temperature value of the blast furnace, the difference between the recommended temperature value of the commissioning operation and the actual temperature value of the blast furnace can be obtained, and if the absolute value of the difference is greater than 0.01 ℃, the commissioning operation can be considered to be subjected to manual intervention. When the commissioning operation is the recommended temperature value of the sintering furnace, the difference value between the recommended temperature value of the commissioning operation and the actual temperature value of the sintering furnace can be obtained, and if the absolute value of the difference value is greater than 0.03 ℃, the commissioning operation can be considered to be subjected to manual intervention.

It should be noted that, in some scenarios, when the commissioning effect of the operation parameter is analyzed, the commissioning switch value corresponding to the operation parameter may be further obtained. And the commissioning switch value is used for representing whether one side of the equipment is in an automatic commissioning state or not. The commissioning switch value can be acquired by set acquisition equipment. In general, the commissioning switch value of the operating parameter may be 1 or 0. If the commissioning switch value is 1, representing the automatic commissioning function of the started operation parameters at one side of the equipment; and if the commissioning switch is 0, representing the automatic commissioning function of the shutdown operation parameters of one side of the equipment. Wherein the operation of turning on or off the automatic commissioning may be performed by a user on the device side.

Continuing with the first operation parameter as an example, when analyzing any one commissioning operation corresponding to the first operation parameter, the commissioning switch value of the first operation parameter when performing the commissioning operation of this time may be obtained in advance. And then, judging whether the equipment starts the automatic commissioning function of the first operation parameter when the commissioning operation is executed according to the commissioning switch value. If the equipment starts the automatic commissioning function of the first operation parameter, whether the commissioning operation is manually intervened or not can be continuously judged according to the recommended value and the actual value of the commissioning operation. If the automatic commissioning function of the first operation parameter is not started, the commissioning operation has no statistical significance, and subsequent analysis operation can be omitted, so that the calculation amount is saved.

Based on the above embodiments, optionally, after analyzing whether the at least one commissioning operation of the first operating parameter is subject to the manual intervention, the number of manual interventions and the ratio of manual interventions may be calculated according to the number of commissioning operations of the manual interventions. For example, of the 15 commissioning operations of the first operating parameter, the commissioning operation of the manual intervention is 3, and the manual intervention rate is 20%.

Based on the above embodiment, optionally, after determining that a certain commissioning operation is manually dried, the reason for manual intervention corresponding to the commissioning operation may be further analyzed according to a range to which a difference value between a recommended value and an actual value corresponding to the commissioning operation belongs. Alternatively, the range may be a positive range or a negative range. For example, for commissioning operation R, if the difference between the recommended pressure value and the actual pressure value is positive, it may be determined that the corresponding human intervention reason is: the pressure is too high; on the contrary, if the difference between the recommended pressure value and the actual pressure value is a negative value, the corresponding human intervention reason can be determined as follows: the pressure is too low.

It should be understood that when the device is running, the environmental conditions may have an effect on the running process of the device. For example, when the ambient temperature is high, the D1 temperature is recommended for the sintering furnace to meet the sintering requirement without human intervention. If the temperature of the environment is low, the sintering requirement may not be met and manual intervention may occur if the D1 temperature is still recommended for the sintering furnace.

Based on this, in order to optimize the algorithm of automatic commissioning, optionally, for commissioning operation of manual intervention, environmental data of the device at the time of manual intervention may be further collected, so as to optimize the recommendation algorithm of the operation parameter according to the environmental data.

Optionally, the environmental data may include environmental data within a physical space in which the equipment is located, such as temperature, humidity, pressure, wind, etc. within the plant. The environmental data may be acquired by a variety of sensors deployed within the physical space in which the device is located. Optionally, the environmental data may also include operational data of other devices associated with the device. For example, for a certain device, the environment data may include the operation data of the upstream device and the operation data of the downstream device, and the embodiment is not limited thereto. Based on the above, the recommendation algorithm of automatic commissioning can be continuously optimized, so that the automatic commissioning can meet the production requirements better.

Fig. 3 is a schematic flowchart of a commissioning effect analysis method for an industrial device according to an exemplary embodiment of the present application, and as shown in fig. 3, the method includes:

301, acquiring a commissioning value adopted for automatically commissioning the industrial equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; the industrial equipment belongs to the field of process manufacturing.

Step 302, detecting operation data of the industrial equipment under the automatic commissioning, and obtaining an actual value of the first operation parameter under the at least one commissioning operation from the operation data.

Step 303, analyzing the commissioning effect of the first operation parameter according to the recommended value of the at least one commissioning operation of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

The flow manufacturing refers to a manufacturing process in which a workpiece is continuously passed through a series of processing apparatuses, and further, a chemical or physical change is generated in a raw material, thereby obtaining a product. In the process of flow manufacturing, the material has strong mobility, and more variables restricting the process flow exist, so that the automatic operation of industrial equipment in the field of flow manufacturing often has higher operation frequency.

The operation of detecting the operation data of the industrial equipment under automatic operation can be realized based on sampling the parameter values of the operation parameters of the industrial equipment under automatic operation. The sampling frequency can be flexibly adjusted according to the commissioning frequency so as to ensure that the actual value corresponding to each commissioning operation is acquired. Typically, the sampling frequency may be set greater than the commissioning frequency.

In a process manufacturing scenario, a higher sampling frequency may be set. Furthermore, even under the condition of high commissioning frequency, the actual value of the operation parameter under each commissioning operation can be accurately acquired; the effect of automatic commissioning can be accurately analyzed based on the recommended value of the operation parameter and the actual value of the operation parameter under commissioning operation, the difficulty of commissioning frequency (particularly high frequency) on commissioning effect analysis is overcome, and the flexibility of commissioning effect analysis operation is improved.

It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subjects of steps 101 to 103 may be device a; for another example, the execution subject of steps 101 and 102 may be device a, and the execution subject of step 103 may be device B; and so on.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 101, 102, etc., are merely used for distinguishing different operations, and the sequence numbers do not represent any execution order per se. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.

The method provided by each embodiment of the present application can be used for counting the automatic delivery effects of a plurality of delivery objects. For example, in the cement industry, the method can be used for counting the automatic commissioning effect of equipment such as a rotary cement kiln, a cyclone preheater, a cooler and the like. For example, in the steel production industry, the method can be used for counting the automatic operation effect of equipment such as a blast furnace, a hot blast stove, a converter, an electric furnace, a refining furnace, a continuous casting machine and the like. For example, in the chemical industry, the method can be used for counting the automatic operation effect of equipment such as a fan, a compressor, a pump, separation equipment, an electrolyzer, a reactor, a filter, a crusher, a centrifugal separator, a rotary kiln, a stirrer, a dryer and the like. The data processing method provided by the embodiment of the present application will be further described below with reference to fig. 4.

Assuming that at the time T1, the cloud computing platform automatically operates once based on the recommendation algorithm, and adjusts the "first coal setting value" of the rotary cement kiln from 10 to 11. At time T1+1, the APC system receives an adjustment command and adjusts the "head coal setpoint" in the APC from 10 to 11. Assume that, at time T2, the recommended value of the recommended algorithm in the cloud computing platform is to adjust the "head coal set point" from 11 to 12. At time T2+1, the APC system receives an adjustment command and adjusts the "head coal setpoint" in the APC from 10 to 11.

And then, acquiring actual operation data of the rotary cement kiln fed back by the DCS, and sampling the head coal value of the rotary cement kiln in the actual operation data. And after the sampling data are obtained, acquiring the head coal value of the rotary cement kiln at the T1+1 moment and the head coal value of the rotary cement kiln at the T2+1 moment from the sampling data. As shown in fig. 4, if the head coal value of the rotary cement kiln is 11 at time T1+1, it is considered that APC has accepted 11, and when the next operation is performed, the APC is still unchanged, and it is recorded that no human intervention is required for the operation. If at time T2+1 the rotary cement kiln had a head coal value of 13, which was not the expected value of 12, then it may be recorded that the commissioning was manually intervened.

In addition to the data processing method described in the foregoing embodiments, the present application provides a data processing apparatus.

Fig. 5 is a schematic structural diagram of a data processing apparatus according to an exemplary embodiment of the present application, and as shown in fig. 5, the apparatus includes:

a data obtaining module 501, configured to: acquiring a commissioning value for automatically commissioning equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; detecting operation data of the equipment under the automatic commissioning, and acquiring an actual value of the first operation parameter under the at least one commissioning operation from the operation data; an analysis module 502 for: and analyzing the commissioning effect of the first operation parameter according to the recommended value of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

Further optionally, the system further includes a result output module 503, specifically configured to: visually displaying the at least one commissioning operation on a page; and responding to the selected operation of the target operation in the at least one operation, and displaying the operation detail data corresponding to the target operation.

Further optionally, when detecting the operation data of the device in the automatic commissioning, the data obtaining module 501 is specifically configured to: in the automatic commissioning process, sampling the parameter value of the first operation parameter according to a set sampling frequency; the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation; or sampling the parameter value of the first operation parameter within a set time range after the commissioning operation of the first operation parameter is executed each time.

Further optionally, when the data obtaining module 501 obtains the actual value of the first operation parameter in each of the at least one commissioning operation from the operation data, it is specifically configured to: acquiring a plurality of sampling points obtained by sampling parameter values of the first operating parameters; combining the plurality of sampling points and the recording nodes corresponding to the at least one commissioning operation according to the time correspondence to obtain combined data; for any one commissioning operation in the at least one commissioning operation, determining a set ordered sampling point behind a recording node corresponding to the commissioning operation from the merged data, and taking the sampling point as a target sampling point; and determining an actual value corresponding to the commissioning operation according to the parameter value corresponding to the target sampling point.

Further optionally, when analyzing the commissioning effect of the first operation parameter according to the recommended value of each of the at least one commissioning operation of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation, the analysis module 502 is specifically configured to: determining a manually-intervened commissioning operation from the at least one commissioning operation according to the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation; and analyzing the number of manual interventions in the at least one commissioning operation according to the commissioning operation of the manual interventions.

Further optionally, the analysis module 502, when determining a manually-intervened commissioning operation from the at least one commissioning operation according to the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation, is specifically configured to: calculating a difference between a recommended value and an actual value of the commissioning operation for any of the at least one commissioning operation; and if the difference is larger than the statistical threshold of the first operation parameter, determining that the commissioning operation is a commissioning operation of manual intervention.

Further optionally, the method further comprises: the threshold maintenance module 504 is specifically configured to: acquiring a historical recommended value and a historical actual value of the first operating parameter without manual intervention from a historical commissioning record; calculating a parameter value floating range of the first operation parameter without manual intervention according to the historical recommended value and the historical actual value; and determining a statistical threshold value of the first operating parameter according to the parameter value floating range.

Further optionally, when obtaining the historical recommended value and the historical actual value of the first operating parameter without human intervention from the historical commissioning record, the threshold maintenance module 504 is specifically configured to: obtaining a target historical commissioning record matched with the type of the equipment from the historical commissioning records; and acquiring a historical recommended value and a historical actual value of the first operation parameter without manual intervention from the target historical commissioning record.

Further optionally, the analysis module 502 is further configured to: and if the commissioning operation is a commissioning operation of manual intervention, analyzing a manual intervention reason corresponding to the commissioning operation according to a numerical range to which a difference value between a recommended value and an actual value of the commissioning operation belongs.

Further optionally, the analysis module 502 is further configured to: and aiming at the commissioning operation of the manual intervention, collecting environmental data of the equipment at the time of the manual intervention so as to optimize the recommendation algorithm of the first operation parameter according to the environmental data.

In this embodiment, when the device is automatically put into operation, the operation data of the device in automatic operation is detected, and the actual value of the operation parameter after operation is obtained; based on the recommended value and the actual value of the operation parameter corresponding to the commissioning operation, the commissioning effect of the operation parameter can be automatically analyzed, the intelligent analysis of the commissioning effect is realized, the flexibility is higher, and the reliability of the analysis result is greatly improved.

In some scenarios, the apparatus shown in fig. 5 may also be used to perform a commissioning effect analysis method of an industrial device. The data obtaining module 501 is configured to: acquiring a commissioning value for automatically commissioning the industrial equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; the industrial equipment belongs to the field of process manufacturing; detecting operation data of the industrial equipment under the automatic operation, and acquiring an actual value of the first operation parameter under the at least one operation from the operation data; an analysis module 502 for: and analyzing the commissioning effect of the automatic commissioning according to the recommended value of the at least one commissioning operation and the actual value corresponding to the at least one commissioning operation.

Fig. 6 is a schematic structural diagram of a data processing apparatus according to an exemplary embodiment of the present application, and as shown in fig. 6, the data processing apparatus includes: memory 601, processor 602, and display component 603.

The memory 601 is used for storing computer programs and may be configured to store other various data to support operations on the data processing apparatus. Examples of such data include instructions for any application or method operating on the data processing device, contact data, phonebook data, messages, pictures, videos, and the like.

The memory 601 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

A processor 602, coupled to the memory 601, for executing the computer programs in the memory 601 to: acquiring a commissioning value for automatically commissioning equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; detecting operation data of the equipment under the automatic commissioning, and acquiring an actual value of the first operation parameter under the at least one commissioning operation from the operation data; and analyzing the commissioning effect of the first operation parameter according to the recommended value of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation.

Further optionally, the data processing apparatus further comprises: a component 603 is displayed. The processor 602 is further configured to: visually presenting the at least one commissioning operation on a page through a display component 603; and responding to the selected operation of the target operation in the at least one operation, and displaying the operation detail data corresponding to the target operation.

Further optionally, when detecting the operation data of the device in the automatic commissioning, the processor 602 is specifically configured to: in the automatic commissioning process, sampling the parameter value of the first operation parameter according to a set sampling frequency; the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation; or sampling the parameter value of the first operation parameter within a set time range after the commissioning operation of the first operation parameter is executed each time.

Further optionally, when obtaining the actual value of the first operation parameter under each of the at least one commissioning operation from the operation data, the processor 602 is specifically configured to: acquiring a plurality of sampling points obtained by sampling parameter values of the first operating parameters; combining the plurality of sampling points and the recording nodes corresponding to the at least one commissioning operation according to the time correspondence to obtain combined data; for any one commissioning operation in the at least one commissioning operation, determining a set ordered sampling point behind a recording node corresponding to the commissioning operation from the merged data, and taking the sampling point as a target sampling point; and determining an actual value corresponding to the commissioning operation according to the parameter value corresponding to the target sampling point.

Further optionally, when analyzing the commissioning effect of the first operation parameter according to the recommended value of each of the at least one commissioning operation of the first operation parameter and the actual value of the first operation parameter under the at least one commissioning operation, the processor 602 is specifically configured to: determining a manually-intervened commissioning operation from the at least one commissioning operation according to the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation; and analyzing the number of manual interventions in the at least one commissioning operation according to the commissioning operation of the manual interventions.

Further optionally, the processor 602, when determining a manually-intervened commissioning operation from the at least one commissioning operation according to the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation, is specifically configured to: calculating a difference between a recommended value and an actual value of the commissioning operation for any of the at least one commissioning operation; and if the difference is larger than the statistical threshold of the first operation parameter, determining that the commissioning operation is a commissioning operation of manual intervention.

Further optionally, the processor 602 is further configured to: acquiring a historical recommended value and a historical actual value of the first operating parameter without manual intervention from a historical commissioning record; calculating a parameter value floating range of the first operation parameter without manual intervention according to the historical recommended value and the historical actual value; and determining a statistical threshold value of the first operating parameter according to the parameter value floating range.

Further optionally, when obtaining the historical recommended value and the historical actual value of the first operating parameter without human intervention from the historical commissioning record, the processor 602 is specifically configured to: obtaining a target historical commissioning record matched with the type of the equipment from the historical commissioning records; and acquiring a historical recommended value and a historical actual value of the first operation parameter without manual intervention from the target historical commissioning record.

Further optionally, the processor 602 is further configured to: and if the commissioning operation is a commissioning operation of manual intervention, analyzing a manual intervention reason corresponding to the commissioning operation according to a numerical range to which a difference value between a recommended value and an actual value of the commissioning operation belongs.

Further optionally, the processor 602 is further configured to: and aiming at the commissioning operation of the manual intervention, collecting environmental data of the equipment at the time of the manual intervention so as to optimize the recommendation algorithm of the first operation parameter according to the environmental data.

Further, as shown in fig. 6, the data processing apparatus further includes: communication components 604, power components 605, and the like. Only some of the components are schematically shown in fig. 6, and it is not intended that the data processing apparatus includes only the components shown in fig. 6.

Wherein the communication component 604 is configured to facilitate wired or wireless communication between the device in which the communication component resides and other devices. The device in which the communication component is located may access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G, or 5G, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component may be implemented based on Near Field Communication (NFC) technology, Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

The power supply 605 provides power to various components of the device in which the power supply is located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.

In this embodiment, when the device is automatically put into operation, the operation data of the device in automatic operation is detected, and the actual value of the operation parameter after operation is obtained; based on the recommended value and the actual value of the operation parameter corresponding to the commissioning operation, the commissioning effect of the operation parameter can be automatically analyzed, the intelligent analysis of the commissioning effect is realized, the flexibility is higher, and the reliability of the analysis result is greatly improved.

In some scenarios, the apparatus shown in fig. 6 may be further configured to perform a commissioning effect analysis method of an industrial apparatus, and in particular, the processor 602 is configured to: acquiring a commissioning value for automatically commissioning the industrial equipment; the commissioning values comprise recommended values for each of at least one commissioning operation of the first operational parameter; the industrial equipment belongs to the field of process manufacturing; detecting operation data of the industrial equipment under the automatic operation, and acquiring an actual value of the first operation parameter under the at least one operation from the operation data; and analyzing the commissioning effect of the automatic commissioning according to the recommended value of the at least one commissioning operation and the actual value corresponding to the at least one commissioning operation.

Accordingly, the present application further provides a computer readable storage medium storing a computer program, where the computer program is capable of implementing the steps that can be executed by the data processing device in the foregoing method embodiments when executed.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.