阅读说明：本技术 基于工业物联网采集设备数据的数据采集方法 (Data acquisition method based on industrial Internet of things acquisition equipment data ) 是由 李精华 陈宏海 卢兴材 于 2021-08-27 设计创作，主要内容包括：本公开描述了一种基于工业物联网采集设备数据的数据采集方法,包括：获取工业设备需要采集的多个参数,并根据各个参数的用途将多个参数至少划分为第一类参数和第二类参数,云盒配置为将第一类参数的数据经由第一子通讯路径以第一频率上传到边缘服务器,将第二类参数的数据经由第一通讯路径以第二频率经上传到云端,第一类参数的数据经由第二子通讯路径以第三频率上传到云端,第一频率大于第二频率,并且若云端在预设时间内未接收到第一类参数的数据,则云盒将第一类参数的数据经由第一通讯路径以第二频率上传到云端。根据本公开的数据采集方法,能够提供一种能够及时并且连续采集设备的关键运行参数的数据采集方法。(The disclosure describes a data acquisition method based on industrial internet of things data acquisition equipment, comprising: the method comprises the steps that a plurality of parameters needing to be collected by the industrial equipment are obtained, the parameters are divided into at least a first type of parameters and a second type of parameters according to the purpose of each parameter, the cloud box is configured to upload data of the first type of parameters to an edge server through a first sub-communication path at a first frequency, upload data of the second type of parameters to a cloud end through the first communication path at a second frequency, upload data of the first type of parameters to the cloud end through the second sub-communication path at a third frequency, the first frequency is higher than the second frequency, and if the cloud end does not receive the data of the first type of parameters within preset time, the cloud box uploads the data of the first type of parameters to the cloud end through the first communication path at the second frequency. According to the data acquisition method disclosed by the invention, the data acquisition method capable of timely and continuously acquiring the key operation parameters of the equipment can be provided.)

1. A data acquisition method for acquiring equipment data based on an industrial Internet of things is a data acquisition method for uploading data from an equipment terminal with industrial equipment and a cloud box to a cloud terminal, wherein the cloud box is communicated with the industrial equipment and is used for acquiring data of a plurality of parameters of the industrial equipment, the cloud box is communicated with the cloud terminal at least through a first communication path and a second communication path, and the second communication path comprises a first sub-communication path from the cloud box to an edge server and a second sub-communication path from the edge server to the cloud terminal, and the data acquisition method is characterized by comprising the following steps: acquiring a plurality of parameters required to be acquired by the industrial equipment, dividing the parameters into at least a first type of parameter and a second type of parameter according to the purpose of each parameter, wherein the first type of parameter is used for evaluating the real-time working state of the industrial equipment, the second type of parameter is used for analyzing the stability of the industrial equipment, the cloud box acquires data of the parameters of the industrial equipment, the cloud box is configured to upload the data of the first type of parameter to the edge server through the first sub-communication path at a first frequency, upload the data of the second type of parameter to the cloud end through the first communication path at a second frequency, upload the data of the first type of parameter to the cloud end through the second sub-communication path at a third frequency, and the first frequency is higher than the second frequency, and if the data of the first type of parameter is not received by the cloud end within a preset time, the cloud box uploads the data of the first type of parameters to the cloud end via the first communication path at the second frequency.

2. The data acquisition method according to claim 1, characterized in that:

the cloud end is provided with a configuration unit, a first processing unit and a first reading unit, the configuration unit is used for configuring a data acquisition protocol of the industrial equipment, the data acquisition protocol comprises the first type of parameters, the second type of parameters, the first frequency and the second frequency, the first type of parameters are uploaded to the cloud end through a second communication path, the second type of parameters are uploaded to an instruction of the cloud end through a first communication path, and the configuration unit issues the data acquisition protocol to the cloud box through the first reading unit.

3. The data acquisition method according to claim 1, characterized in that:

the first type of parameter is a key operating parameter of the industrial equipment, and the second type of parameter is a non-key operating parameter of the industrial equipment.

4. A data acquisition method according to claim 1 or 3, characterized in that:

the first frequency is greater than a first preset value, and the second frequency is not greater than a second preset value.

5. The data acquisition method of claim 2, wherein:

the cloud box comprises a second processing unit, a second transceiver unit and a second reading unit,

the first reading unit issues the data acquisition protocol to the second transceiving unit, the second transceiving unit sends the data acquisition protocol to the second processing unit, and the second processing unit analyzes the data acquisition protocol and issues the analyzed data acquisition protocol to the industrial equipment through the second reading unit.

6. The data acquisition method according to claim 1, characterized in that:

the second frequency is the same as the third frequency.

7. The data acquisition method of claim 5, wherein:

the industrial equipment is provided with a controller, and the controller is in wired connection with the cloud box; the second reading unit sends the analyzed data to the controller, the controller receives and identifies the analyzed data to realize data exchange with the industrial equipment,

the industrial equipment inputs the data of the parameters to the controller, the controller uploads the input data of the parameters to the second reading unit, and the second reading unit sends the data of the parameters to the second processing unit.

8. The data acquisition method of claim 6, wherein:

the equipment end also comprises a sensor, the sensor is arranged on the industrial equipment and is connected with the second processing unit and the controller,

the controller collects data for the plurality of parameters based on the sensor,

the second processing unit divides the plurality of acquired parameters into at least the first kind of parameters and the second kind of parameters based on the sensor,

the second processing unit uploads the second type of parameters to the cloud via the second transceiving unit at the second frequency,

the second processing unit uploads the first type of parameters to the edge server through the second transceiver unit at the first frequency, and the edge server uploads the first type of parameters to the cloud end at the third frequency.

9. The data acquisition method according to claim 1, characterized in that:

and when the second communication path does not keep communication within a preset time, the cloud end sends an abnormal warning.

10. The data acquisition method according to claim 1, characterized in that:

the cloud end receives and processes the data of the first type of parameters and the data of the second type of parameters,

the cloud monitors the industrial equipment based on the first type of parameters and remotely monitors and analyzes the industrial equipment based on the second type of parameters;

and the edge server receives and processes the data of the first type of parameters and monitors the industrial equipment in real time based on the first type of parameters.

Technical Field

The disclosure relates to the technical field of Internet of things, in particular to a data acquisition method based on industrial Internet of things data acquisition equipment.

Background

In the era of industrial internet of things, digitalization is a trend of manufacturing industry, and a factory workshop needs to realize digitalization, networking and intellectualization, so that the problem of data acquisition is solved in the first step. Therefore, how to efficiently collect data of industrial equipment parameters becomes the key of the digital solution.

In the existing data acquisition method, the basic technology of the data acquisition link is relatively mature, and generally, data of all real-time performance parameters of industrial equipment are acquired at an equipment end, the data of all the real-time performance parameters are uniformly uploaded to a cloud end, then data stream changes of single real-time performance parameters are observed one by one at the cloud end, and whether the acquisition frequency of the real-time performance parameters needs to be adjusted or not is judged according to a preset data threshold. However, the data acquisition method has many disadvantages, different networking modes, communication modes and communication protocols are combined to generate certain limitations, uploading of all real-time performance parameters causes data packets to be too large, and load of a cloud end is increased. Meanwhile, interference of other data cannot be eliminated, and data of critical real-time performance parameters are difficult to upload to the cloud in time.

Disclosure of Invention

The present disclosure has been made in view of the above-mentioned state of the art, and an object thereof is to provide a data acquisition method capable of timely and continuously acquiring key operating parameters of a device.

To this end, a first aspect of the present disclosure provides a data acquisition method for uploading data from a device side having an industrial device and a cloud box to a cloud side, where the cloud box is in communication with the industrial device and is configured to acquire data of a plurality of parameters of the industrial device, and the cloud box is in communication with the cloud side through at least a first communication path and a second communication path, and the second communication path includes a first sub-communication path from the cloud box to an edge server and a second sub-communication path from the edge server to the cloud side, where the data acquisition method includes: acquiring a plurality of parameters required to be acquired by the industrial equipment, dividing the parameters into at least a first type of parameter and a second type of parameter according to the purpose of each parameter, wherein the first type of parameter is used for evaluating the real-time working state of the industrial equipment, the second type of parameter is used for analyzing the stability of the industrial equipment, the cloud box acquires data of the parameters of the industrial equipment, the cloud box is configured to upload the data of the first type of parameter to the edge server through the first sub-communication path at a first frequency, upload the data of the second type of parameter to the cloud end through the first communication path at a second frequency, upload the data of the first type of parameter to the cloud end through the second sub-communication path at a third frequency, and the first frequency is higher than the second frequency, and if the data of the first type of parameter is not received by the cloud end within a preset time, the cloud box uploads the data of the first type of parameters to the cloud end via the first communication path at the second frequency.

According to the data acquisition method, interference of other data can be eliminated by building at least two communication paths from the cloud box to the cloud end, the first type of parameters of the industrial equipment are uploaded to the edge server in time through the first sub-communication path, and the edge server carries out localized processing on the first type of parameters on the industrial site. Specifically, the edge server performs partial or complete preprocessing on the acquired data of the first type of parameters, analyzes and operates according to a configured algorithm, and performs data presentation on the analyzed result locally and instantly. Meanwhile, the edge server can filter useless data, so that the bandwidth of data transmission can be reduced, and the load of a cloud end can be relieved. In addition, the second type of parameters of the equipment are more, and the second type of parameters are uploaded to the cloud end through the first communication path by configuring the lower acquisition frequency of the second type of parameters, so that the data transmission flow can be saved. When the second communication path is abnormal, the data acquisition of the first type of parameters and the data acquisition of the second type of parameters are automatically switched to the first communication path, under the condition, the continuous acquisition of the data of the first type of parameters can be realized, and the condition that the equipment cannot be monitored due to the data loss of the key operation parameters is avoided. The cloud participates in the monitoring of the equipment according to the first type of parameters of the equipment to judge whether the equipment works normally, and performs remote monitoring and post analysis on the equipment according to the second type of parameters.

In addition, in the data acquisition method according to the present disclosure, optionally, the cloud includes a configuration unit, a first processing unit, and a first reading unit, the configuration unit is configured to configure a data acquisition protocol of the industrial device, the data acquisition protocol includes the first type of parameter, the second type of parameter, the first frequency and the second frequency, and an instruction that the first type of parameter is uploaded to the cloud via a second communication path and the second type of parameter is uploaded to the cloud via a first communication path, and the configuration unit issues the data acquisition protocol to the cloud box via the first reading unit. In this case, the cloud box can implement data collection for the industrial device according to the data collection protocol.

In addition, in the data acquisition method according to the present disclosure, optionally, the first type of parameter is a key operation parameter of the industrial equipment, and the second type of parameter is a non-key operation parameter of the industrial equipment. Therefore, the working state of the industrial equipment can be evaluated according to the first type of parameters, and the stability of the industrial equipment can be analyzed according to the second type of parameters.

In addition, in the data acquisition method according to the present disclosure, optionally, the first frequency is greater than a first preset value, and the second frequency is not greater than a second preset value. Under the condition, the first type of parameters can be uploaded to the edge server in time, the edge server can participate in real-time monitoring of the industrial equipment according to a monitoring algorithm, delay of a computing system is reduced, meanwhile, the second type of parameters are collected at a lower frequency, bandwidth of data transmission can be reduced, and load of a cloud end is relieved.

In addition, in the data acquisition method according to the present disclosure, optionally, the cloud box includes a second processing unit, a second transceiver unit, and a second reading unit, the first reading unit issues the data acquisition protocol to the second transceiver unit, the second transceiver unit sends the data acquisition protocol to the second processing unit, and the second processing unit parses the data acquisition protocol and issues the parsed data acquisition protocol to the industrial device via the second reading unit. Therefore, the cloud box can realize data acquisition of the industrial equipment according to specific contents under the data acquisition protocol.

In addition, in the data acquisition method according to the present disclosure, optionally, the second frequency is the same as the third frequency. Therefore, the first type of parameters can be reported to the cloud end through the second sub-communication path at a low frequency.

In addition, in the data acquisition method according to the present disclosure, optionally, the industrial device has a controller, and the controller is connected to the cloud box by wire; the second reading unit issues the analyzed data to the controller, the controller receives and identifies the analyzed data to realize data exchange with the industrial equipment, the industrial equipment inputs the data of the parameters to the controller, the controller uploads the input data of the parameters to the second reading unit, and the second reading unit sends the data of the parameters to the second processing unit. Therefore, the controller can realize data exchange with the industrial equipment according to the analyzed data under the data acquisition protocol, and the second processing unit can process the acquired data of the plurality of parameters.

In addition, in the data acquisition method related to the present disclosure, optionally, the device side further includes a sensor, the sensor is mounted on the industrial equipment and is connected with the second processing unit and the controller, the controller collects data of the plurality of parameters based on the sensor, the second processing unit divides the collected plurality of parameters into at least the first kind of parameters and the second kind of parameters based on the sensor, the second processing unit uploads the second type of parameters to the cloud via the second transceiving unit at the second frequency, the second processing unit uploads the first type of parameters to the edge server via the second transceiving unit at the first frequency, and the edge server uploads the first type of parameters to the cloud end at the third frequency. From this, can upload first type parameter and second type parameter to the high in the clouds according to the frequency of predetermineeing according to the type of parameter to through setting up two communication paths of cloud box to high in the clouds, can effectually get rid of the interference of other data, monitor or monitor the analysis to industrial equipment according to the usage of a plurality of parameters.

In addition, in the data acquisition method related to the disclosure, optionally, when the second communication path does not maintain communication within a preset time, the cloud sends an exception warning, so that relevant operation and maintenance personnel can find an equipment exception or an exception of the data acquisition path in time, maintain the equipment or the data acquisition path in time, and can acquire data of the first type of parameters in real time through the second communication path, and the edge server can perform localized processing on the data of the first type of parameters.

In addition, in the data acquisition method according to the present disclosure, optionally, the cloud receives and processes the data of the first type of parameter and the data of the second type of parameter, and the cloud monitors the industrial device based on the first type of parameter and remotely monitors and performs post-analysis on the industrial device based on the second type of parameter; and the edge server receives and processes the data of the first type of parameters and monitors the industrial equipment in real time based on the first type of parameters. Under the condition, the real-time working state of the industrial equipment can be visually observed, and operation and maintenance personnel can also analyze the abnormal warning in time so as to keep the data acquisition of the industrial equipment in a stable and controllable state all the time.

According to the data acquisition method disclosed by the invention, the data acquisition method capable of timely and continuously acquiring the key operation parameters of the equipment can be provided.

Drawings

The disclosure will now be explained in further detail by way of example only with reference to the accompanying drawings, in which:

fig. 1 is a schematic diagram of an acquisition path showing the data acquisition method according to the present embodiment.

Fig. 2 is a block diagram showing an apparatus side of the data acquisition method according to the present embodiment.

Fig. 3 is a flowchart showing a data acquisition method according to the present embodiment.

Fig. 4 is a block diagram illustrating a cloud terminal according to the present embodiment.

Fig. 5 is a block diagram showing a cloud box according to the present embodiment.

Fig. 6 shows a normal data communication path according to the present embodiment.

Fig. 7 shows an abnormal data communication path according to the present embodiment.

Detailed Description

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same components are denoted by the same reference numerals, and redundant description thereof is omitted. The drawings are schematic and the ratio of the dimensions of the components and the shapes of the components may be different from the actual ones.

It is noted that the terms "comprises," "comprising," and "having," and any variations thereof, in this disclosure, for example, a process, method, system, article, or apparatus that comprises or has a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include or have other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In addition, the headings and the like referred to in the following description of the present disclosure are not intended to limit the content or scope of the present disclosure, but merely serve as a reminder for reading. Such a subtitle should neither be understood as a content for segmenting an article, nor should the content under the subtitle be limited to only the scope of the subtitle.

The embodiment relates to a data acquisition method based on data of an industrial internet of things acquisition device, which is a data acquisition method for uploading data from a device terminal with industrial equipment and a cloud box to a cloud end, and is sometimes referred to as a data acquisition method hereinafter. In the present disclosure, the device may be an industrial device, for example, an air compressor, but the data acquisition method according to the present disclosure may also be applied to other devices requiring data acquisition. By the data acquisition method, the data of the key operation parameters of the equipment can be acquired timely and continuously. Hereinafter, the data collection method according to the present embodiment will be described in detail with reference to the drawings.

Fig. 1 is a schematic diagram of an acquisition path showing the data acquisition method according to the present embodiment. In some examples, the acquisition path may include device end 1 and cloud end 2. Fig. 2 is a block diagram showing an apparatus side of the data acquisition method according to the present embodiment.

In this embodiment, the data collection method may be a data collection method for uploading data from the device side 1 to the cloud side 2. In some examples, the device end 1 may include an industrial device 11 and a cloud box 12, the cloud box 12 may be in communication with the industrial device 11 and may be used to collect data for a plurality of parameters of the industrial device 11. In some examples, the cloud box 12 may communicate with the cloud 2 through at least two communication paths. In some examples, the two communication paths may include a first communication path L1 and a second communication path L2. In some examples, the first communication path L1 may be that the cloud box 12 uploads the collected data directly to the cloud end 2.

In some examples, the second communication path L2 may include a first sub communication path L21 and a second sub communication path L22, the first sub communication path L21 may be that the cloud box 12 uploads the collected data to the edge server 3, and the second sub communication path L22 may be that the edge server 3 uploads the collected data to the cloud 2.

In the present embodiment, data of parameters of the industrial equipment 11 is acquired, and a plurality of parameters that the industrial equipment 11 needs to acquire may be acquired in advance. In some examples, the plurality of parameters may be divided into at least a first class of parameters and a second class of parameters according to the usage of the respective parameters of the industrial equipment 11. In some examples, the first type of parameter may be used to assess the real-time operating state of the industrial equipment 11. In some examples, the second type of parameter may be used to analyze the stability of the industrial equipment 11.

In addition, the cloud box 12 may collect data for a plurality of parameters of the industrial equipment 11. In some examples, the cloud box 12 may be configured to upload the first type of parameter to the edge server 3 via the first sub-communication path L21, and the cloud box 12 may be configured to upload the first type of parameter to the edge server 3 at the first frequency. In some examples, the edge server 3 may perform localized processing on the data of the first type of parameters, which may include, for example, cleaning, screening, filtering, parsing, and the like of the data. Thus, the edge server 3 can monitor the working state of the equipment in real time based on the collected data of the first type of parameters.

In some examples, the cloud box 12 may be configured to upload the second type of parameter to the cloud 2 via the first communication path L1. In some examples, cloud box 12 may also be configured to upload the second type of parameter to cloud 2 via second communication path L2. Specifically, the cloud box 12 may upload the second type of parameters to the edge server 3 via the first sub-communication path L21 at the second frequency, and the edge server 3 may upload the second type of parameters to the cloud end 2 via the second sub-communication path L22 at the second frequency. In this case, the cloud 2 monitors and analyzes the operational stability of the industrial device 11 based on the second type of parameter.

In some examples, the first frequency may be greater than the second frequency. In this case, by building at least two communication paths from the cloud box 12 to the cloud end 2, interference of other data can be eliminated, and the first type of parameters of the industrial equipment 11 are uploaded to the edge server 3 through the first sub-communication path L21 in time. In some examples, the second type of parameter may be uploaded to the cloud 2 through the first communication path L1, and may also be uploaded to the cloud 2 through the second communication path L2. In this case, by configuring a lower acquisition frequency for the second type of parameters, the bandwidth of data transmission can be reduced, and the load of the cloud 2 can be reduced.

In this embodiment, if the cloud end 2 does not receive the data of the first type parameter within the preset time, the cloud box 12 may upload the first type parameter to the cloud end 2 via the first communication path L1. In some examples, the frequency of uploading the first type parameter to the cloud end 2 by the cloud box 12 via the first communication path L1 may be the second frequency. Under the condition, the continuous acquisition of the data of the first type of parameters can be realized, and the condition that the equipment cannot be monitored due to data loss is avoided. Hereinafter, a data acquisition method based on data of an industrial internet of things acquisition device according to the embodiment will be described in detail with reference to the accompanying drawings.

Fig. 3 is a flowchart showing a data acquisition method according to the present embodiment.

Referring to fig. 3, a data acquisition method according to the present disclosure may include the steps of: the method includes the steps of acquiring parameters to be acquired, dividing parameter types according to parameter purposes (step S100), acquiring data of multiple parameters of the industrial equipment 11 by the cloud box 12 (step S200), uploading the acquired parameters to the cloud end 2 by the cloud box 12 (step S300), and adjusting uploading paths of the parameters (step S400).

In the present disclosure, data of a plurality of parameters of the industrial equipment 11 can be acquired by using the measurement method according to the present embodiment. By the data acquisition method, the data of the first type parameters of the equipment can be acquired in time and can be continuously acquired.

Fig. 4 is a block diagram illustrating a cloud terminal according to the present embodiment. In some examples, a data collection protocol for the industrial device 11 may be configured at the cloud 2 prior to data collection for the industrial device 11. In some examples, the data collection protocol of the industrial equipment 11 may be configured at the remote end. In this case, the cloud box 12 may collect data of the industrial device 11 according to a data collection protocol, and upload the collected data to the cloud end 2 according to the data collection protocol.

As described above, the data acquisition method may include step S100. In some examples, step S100 may include obtaining parameters that need to be acquired and dividing parameter types according to parameter usage.

Specifically, the method may include acquiring a plurality of parameters that the industrial equipment 11 needs to collect, and the plurality of parameters may be divided into a plurality of types according to uses of the plurality of parameters. In some examples, the parameters that the industrial equipment 11 needs to collect may include operating conditions, discharge pressure, discharge temperature, oil filter usage time, oil separator usage time, and the like. In some examples, the parameters that the industrial equipment 11 needs to acquire may also include other parameters. Thereby, a plurality of parameters that the industrial device 11 needs to acquire can be acquired.

In some examples, the plurality of parameters may be divided into at least a first class of parameters and a second class of parameters according to parameter usage. In some examples, the first type of parameter may be a key operating parameter of the industrial equipment 11, which is a necessary parameter for real-time monitoring of the industrial equipment 11, for example, the first type of parameter may include an operating state, an exhaust pressure, an exhaust temperature, and the like. In some examples, monitoring the industrial equipment 11 requires continuous collection of data for key operating parameters. In some examples, the second type of parameter may be a non-critical operating parameter of the industrial equipment 11, and the monitoring analysis of the industrial equipment 11 requires the acquisition of the second type of parameter, for example, the second type of parameter may include oil filter usage time, oil separator usage time, and the like. In some examples, a first type of parameter may be used to assess the real-time operating state of the industrial equipment 11 and a second type of parameter may be used to analyze the stability of the industrial equipment 11. In this case, by classifying a plurality of parameters, it is possible to facilitate monitoring or monitoring analysis of the device according to the type of the parameter.

As described above, the data acquisition method may include step S200. In some examples, in step S200, the cloud box 12 may collect data for a plurality of parameters of the industrial equipment 11.

In some examples, the cloud box 12 may enable data collection for the industrial equipment 11 according to a data collection protocol. In some examples, referring to fig. 2 and 4, the data collection protocol of the industrial device 11 may be configured at the cloud end 2 and issued to the cloud box 12. In some examples, the data collection protocol of the industrial equipment 11 may be configured at the remote end. In some examples, the data collection protocol of the industrial equipment 11 may be configured at the edge server 3. Thus, the cloud box 12 can realize data acquisition of the industrial equipment 11 according to the data acquisition protocol

In some examples, the cloud 2 may have a configuration unit 21, a first processing unit 23, and a first reading unit 22. In some examples, the configuration unit 21 may be used to configure a data acquisition protocol of the industrial equipment 11. In some examples, the data collection protocol may include a first type of parameter, a second type of parameter, a first frequency and a second frequency, instructions for uploading the first type of parameter to the cloud 2 via the second communication path L2, and instructions for uploading the second type of parameter to the cloud 2 via the first communication path L1. In some examples, the data collection protocol may further include instructions for uploading the second type of parameters to the cloud 2 via the second communication path L2. In some examples, the configuration unit 21 may issue the configured data acquisition protocol to the cloud box 12 via the first reading unit 22.

In some examples, the data collection protocol may be delivered to the cloud box 12 via the first communication path L1 or the second communication path L2. In this case, the data acquisition protocol of the industrial device 11 can be configured at the cloud end 2 and issued to the cloud box 12, and the cloud box 12 can acquire the data of the industrial device 11 according to the data acquisition protocol.

Fig. 5 is a block diagram showing a cloud box according to the present embodiment. In some examples, the cloud box 12 may include a power supply unit 121, whereby power can be provided to other units 12. In some examples, the cloud box 12 may include a second processing unit 123, a second transceiver unit 124, and a second reading unit 122. Therefore, the cloud box 12 can receive and analyze the data acquisition protocol issued by the cloud end 2 and realize data acquisition of the industrial equipment 11 according to the specific content under the data acquisition protocol.

In some examples, the configuration unit 21 may issue the configured data acquisition protocol to the second processing unit 124 via the first reading unit 22, so that the data acquisition protocol can be issued from the cloud end 2 to the cloud box 12. In some examples, the second processing unit 124 may receive the data collection protocol issued by the cloud 2 and send the data collection protocol to the second processing unit 123. In some examples, the second processing unit 123 may parse the data collection protocol and send the parsed data to the industrial device 11 via the second reading unit 122. In this case, the cloud box 12 can realize data acquisition of the industrial device 11 according to the specific content in the analyzed data acquisition protocol, that is, the cloud box 12 can acquire data of the required parameters.

In some examples, the industrial device 11 may have a controller 111. In some examples, the controller 111 may be wired to the cloud box 12 to enable the cloud box 12 to communicate with the industrial device 11. In some examples, the controller 111 may be wired to the first reading unit 22. In some examples, the parsed data under the data collection protocol may be sent to the controller 111 via the first reading unit 22, and in some examples, the controller 111 may receive and recognize the parsed data to implement data exchange with the industrial device 11. In this way, the controller 111 can exchange data with the industrial equipment 11 based on the analyzed data under the data acquisition protocol.

In some examples, the controller 111 and the cloud box 12 may communicate using an industrial fieldbus RS 485. In some examples, controller 111 and cloud box 12 may communicate using RS232, CAN, or LAN communication. Thus, the collected data can be completely transmitted to the cloud box 12.

In some examples, the device side 1 may further include a sensing device (not shown) that may be mounted to the industrial device 11 and interface with the controller 111. In some examples, the controller 111 may collect data for a plurality of parameters based on the sensing device, thereby enabling collection of data for a desired plurality of parameters.

In some examples, data of a plurality of parameters of the industrial equipment 11 that need to be collected may be input into the controller 111 according to a data collection protocol, thereby enabling collection of data of a plurality of parameters of the industrial equipment 11. In some examples, the controller 111 may upload data of the input plurality of parameters to the cloud box 12. In some examples, the controller 111 may transmit the input data of the plurality of parameters to the second processing unit 123 via the first reading unit 22, whereby the second processing unit 123 can process the acquired data of the plurality of parameters.

In some examples, the cloud box 12 may be connected with a sensing device (not shown), which may be 1 or more. In some examples, the cloud box 12 may include a sensing unit 125. In some examples, connected to the sensing device may be a second processing unit 123. In some examples, the second processing unit 123 may divide the acquired plurality of parameters into a first type of parameter and a second type of parameter based on the sensing device or the sensing unit 125, and configure the uploading frequency of the first type of parameter and the second type of parameter according to the data acquisition protocol. In some examples, the second processing unit 123 may upload the first type of parameters to the cloud 2 via the second processing unit 124, and may upload the second type of parameters to the cloud 2 via the second processing unit 124. Therefore, the first type of parameters and the second type of parameters can be uploaded to the cloud end 2 according to the type of the parameters and preset frequency.

Fig. 6 shows a normal data communication path according to the present embodiment.

As described above, the data acquisition method may include step S300. In some examples, in step S300, the cloud box 12 may upload the acquired parameters to the cloud end 2. Specifically, the cloud box 12 may be configured to upload data of the first type parameter to the edge server 3 via the first sub-communication path L21 of the second communication path L2 at the first frequency, and then the edge server 3 may upload data of the first type parameter to the cloud 2 via the second sub-communication path L22 at the third frequency. In some examples, the cloud box 12 may upload the collected data of the second type of parameter to the cloud end 2 via the first communication path L1 at the second frequency. In some examples, the first frequency may be greater than the second frequency.

In some examples, cloud box 12 may communicate with cloud 2 via at least a first communication path L1 and a second communication path L2. In some examples, the first communication path L1 may include the cloud box 12 and the cloud end 2, and the cloud box 12 may upload the collected second type of parameters to the cloud end 2 via the first communication path L1. In some examples, the industrial device 11 has more second type parameters, and uploading the second type parameters from the cloud box 12 to the cloud 2 may cause a longer network delay. In some examples, the communication manner of the first communication path L1 may include a wired network or a wireless network, for example, the communication may be implemented through a wired network (LAN), that is, a LAN communication, where the LAN has a faster transmission speed and a more stable performance compared to other networks. In this case, the second type of parameters can be efficiently uploaded to the cloud 2. In some examples, it is preferable that the first communication path L1 can communicate with the cloud end 2 through a wireless network, such as 4G, and the 4G communication enables faster data transmission rate and higher communication quality. In this case, the second type of parameters can be uploaded to the cloud 2 more efficiently for monitoring and analysis of the industrial device 11. In some examples, the wireless network may also include 2G, 5G, or NB-LOT communications.

In some examples, the second communication path L2 may include the cloud box 12, the edge server 3, and the cloud 2. In some examples, the second communication path L2 may include a first sub-communication path L21 and a second sub-communication path L22. In some examples, the path for uploading data from the cloud box 12 to the edge server 3 may be the first sub communication path L21, and the path for uploading data from the edge server 3 to the cloud box 2 may be the second sub communication path L22. In some examples, the cloud box 12 may upload the collected first type parameters to the cloud end 2 via the second communication path L2. In this case. The edge server 3 can monitor the industrial device 11 in real time based on the data of the first type of parameters, and the cloud end 2 can participate in monitoring the industrial device 11 based on the data of the first type of parameters.

In some examples, cloud 2 may receive the second type of parameters uploaded by cloud box 12 via first communication path L1 and second communication path L2, and specifically, cloud box 12 may upload the collected second type of parameters to cloud 2 via first communication path L1, and cloud box 12 may also upload the collected second type of parameters to cloud 2 via second communication path L2. In this case, the cloud 2 can determine consistency of data uploading based on the second type of parameters from the first communication path L1 and the second type of parameters from the second communication path L2, and has a certain verification effect.

Specifically, in some examples, the cloud box 12 may upload the collected data of the first type of parameter to the edge server 3 via the first sub-communication path L21, and the edge server 3 may perform localized processing on the data of the first type of parameter, which may include, for example, cleaning, screening, filtering, parsing, and the like on the data. In this case, the edge server 3 can perform analysis operation on the collected data of the first type parameters according to the configured algorithm, and present the calculation result locally. In some examples, the edge server 3 may upload the collected data of the first type of parameter to the cloud 2 periodically via the second sub-communication path L22. Thus, the cloud 2 can record data of the first type of parameters and participate in monitoring of the industrial device 11 based on the data of the first type of parameters. In some examples, the cloud 2 may obtain data of the edge server 3 on demand.

In some examples, the communication mode of the second communication path L2 may implement the communication between the cloud box 12 and the edge server 3 through a private wireless network, such as a Lora mode, and the communication between the edge server 3 and the cloud 2 may be implemented through a wide area network. In some examples, the cloud box 12 may upload the collected second type of parameters to the cloud end 2 via the second communication path L2. In some examples, the edge server 3 may upload all of the data for the second type of parameters to the cloud 2. In other examples, the second type of parameters of the device are more, and the server 3 may perform preprocessing operation on the collected data of part of the second type of parameters, filter some useless data, and upload the filtered second type of parameters to the cloud 2. In this case, the second type of parameters are preprocessed by the edge server 3, so that interference of other data can be eliminated, and useful information can be uploaded to the cloud 2.

In some examples, the frequency of uploading the first type parameters to the edge server 3 via the first sub-communication path L21 by the cloud box 12 may be a first frequency, and the frequency of uploading the first type parameters to the cloud end 2 via the second sub-communication path L22 by the edge server 3 may be a third frequency. In some examples, the frequency of uploading the second type of parameters to the cloud end 2 via the first communication path L1 by the cloud box 12 may be the second frequency, and the frequency of uploading the second type of parameters to the cloud end 2 via the second communication path L2 may also be the second frequency. In this case, by setting different uploading frequencies for the parameters, the data communication flow can be effectively saved. And through setting up two communication paths of cloud box 12 to high in the clouds 2, can effectually get rid of the interference of other data, monitor or monitor the analysis to industrial equipment 11 according to the usage of a plurality of parameters.

In some examples, the first type of parameters of the industrial equipment 11 is less but the upload frequency requirement is higher, and the second type of parameters of the industrial equipment 11 is more but the upload frequency requirement is lower. In some examples, the first frequency may be greater than the second frequency. Under the condition, the interference of data of other parameters can be eliminated, the first type of parameters of the industrial equipment 11 can be uploaded to the edge server 3 in time, so that the industrial equipment 11 can be monitored in real time, different acquisition frequencies are set for different parameters, the acquisition of key data can be improved, and meanwhile, the data acquisition flow is saved.

In some examples, the first frequency may be greater than a first preset value. In some examples, monitoring the industrial equipment 11 requires real-time collection of data for the first type of parameter, so the cloud box 12 may report the first type of parameter to the edge server 3 at a high frequency. Thereby, the edge server 3 can participate in real-time monitoring of the industrial equipment 11 according to the monitoring algorithm, reducing the delay of the computing system.

In some examples, the first preset value may be 1 second/time, 1.5 seconds/time, 2 seconds/time, 2.5 seconds/time, 3 seconds/time, or the like. In this case, the first type of parameters can be uploaded to the edge server 3 in time and the industrial equipment 11 can be monitored in real time.

In some examples, the second frequency may not be greater than the second preset value. In some examples, box 12 may report the second type of parameter to cloud 2 at a low frequency. In some examples, the cloud box 12 may report the second type of parameter to the edge server 3 at a low frequency, and the edge server 3 reports the second type of parameter to the cloud end 2 at a low frequency, and the cloud end 2 remotely monitors and analyzes the industrial device 11 afterwards according to the second type of parameter. In some examples, the second preset value may be 30 seconds/time, 60 seconds/time, 90 seconds/time, 120 seconds/time, 150 seconds/time, 180 seconds/time, or the like. In this case, collecting the second type of parameters at a lower frequency can reduce the bandwidth of data transmission and reduce the load on the cloud 2.

In some examples, the frequency at which the edge server 3 reports the first type of parameter to the cloud 2 (i.e., the third frequency) may be the same as the second frequency. Therefore, the first type of parameters can be reported to the cloud 2 at a low frequency through the second sub-communication path L22.

In some examples, the cloud 2 may perform remote OTA or other remote operations on the edge server 3. In this case, the cloud 2 can synchronize and update the algorithm of the edge server 3.

Fig. 7 shows an abnormal data communication path according to the present embodiment.

As described above, the data acquisition method may include step S400. In some examples, in step S400, an upload path to adjust parameters may be included.

Specifically, if the cloud end 2 does not receive the data of the first type parameter within the preset time, the cloud box 12 may upload the data of the first type parameter to the cloud end 2 via the first communication path L1 at the second frequency. In this case, the data collection of the industrial equipment 11 is all switched to the first communication path L1. In this case, the first type parameter and the second type parameter are both uploaded to the cloud 2 through the first communication path L1.

In some examples, if the cloud end 2 does not receive the data of the first type parameter within a preset time, the cloud box 12 may automatically switch the communication path of the data of the first type parameter. In some examples, the cloud box 12 may switch the communication path of the first type parameter from the second communication path L2 to the first communication path L1. In some examples, if the cloud end 2 does not receive the data of the first type of parameter within the preset time, the cloud box 12 may upload the first type of parameter and the second type of parameter to the cloud end 2 via the first communication path L1 at the same time, and the uploading frequency of the first type of parameter and the uploading frequency of the second type of parameter may be the second frequency. In some examples, monitoring the industrial equipment 11 requires continuous acquisition of data for the first type of parameter. In this case, by adjusting the communication path of the first type parameter, the first type parameter of the industrial device 11 can be continuously collected to monitor the industrial device 11.

In some examples, the preset time may be 10 to 20 seconds. For example, the preset time may be 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, or the like. In this case, the smaller the preset time is, when the second communication path L2 is abnormal, the more timely the first type of parameter can be switched to the first communication path L1 to continuously collect the first type of parameter.

In some examples, when the second communication path L2 does not maintain communication for a preset time, the cloud 2 may issue an exception alert, and the relevant operation and maintenance personnel may perform exception handling on the industrial device 11 or the second communication path L2 based on the exception alert. Therefore, related operation and maintenance personnel can find the equipment abnormality or the abnormality of the data acquisition path in time, repair the equipment or the data acquisition path in time, acquire data of the first type of parameters in real time through the second communication path L2, and the edge server 3 can perform localized processing on the data of the first type of parameters.

In some examples, if the second communication path L2 returns to normal, the uploading of the first type of parameters may be switched to the second communication path L2 again, and the second type of parameters may also be uploaded to the cloud 2 via the second communication path L2. This enables the data collection of the industrial equipment 11 to be maintained in a stable and controllable state at all times.

In some examples, the cloud 2 may receive and process data of the first type of parameters and data of the second type of parameters, which are sent to the first processing unit 23 via the first reading unit 22. In some examples, the first processing unit 23 may process the data of the parameters, such as store, analyze, and count, to display the operation status of the industrial equipment 11 in a configuration manner, and may notify the relevant operation and maintenance personnel of the abnormal warning in time. In some examples, the cloud 2 may participate in monitoring of the industrial device 11 based on the first type of parameter, and perform remote monitoring and post-incident analysis on the industrial device 11 based on the second type of parameter. Under the condition, the working state of the industrial equipment 11 can be visually observed, and the operation and maintenance personnel can also analyze the abnormal warning in time so as to keep the data acquisition of the industrial equipment 11 in a stable and controllable state all the time.

In some examples, the cloud 2 further includes a first transceiver (not shown), and the data processed by the first processing unit 23 is uploaded to the mobile terminal via the first transceiver. In some examples, the mobile terminal may include PC terminals or APP terminals of a plurality of device users, and the device users can know the operation state of the industrial device 11 without time or place limitation based on the PC terminals or APP terminals. In some examples, multiple device users can form a customer relationship management system (CRM system) based on internet of things data through a PC terminal or an APP terminal, and the CRM system can draw scientific conclusions through big data technology. Therefore, the enterprise can know the requirements of the customers better based on the CRM system, and the acceptance of the customers to the enterprise is deepened.

In some examples, according to the data acquisition method in the embodiment, dual-mode monitoring of the industrial device in the intelligent control system can be realized based on the first communication path L1 and the second communication path L2, that is, the dual-mode monitoring method of the industrial device based on edge monitoring and cloud 2 monitoring can be used for realizing centralized monitoring of a plurality of industrial devices, and the effects of overall voltage stabilization and energy saving can be realized through cooperative scheduling of the intelligent control system.

In some examples, the intelligent control system may include multiple pieces of industrial equipment, for example, may include multiple air compressors and pipeline pressure transmitters. In some examples, a dual-mode monitoring method may include:

in some examples, cloud boxes 12 with two communication modes may be installed at multiple air compressors and at pipeline pressure transmitters, and in some examples, a first monitoring link and a second monitoring link may be established through a first communication path L1 and a second communication path L2. In some examples, the first monitoring link is secondary monitoring and the second monitoring link is primary monitoring. In some examples, the first monitoring link is cloud box 12 to cloud 2, and the second monitoring link is cloud box 12 to cloud 2 via edge server 3.

In some examples, a data collection protocol for each device may be defined at the cloud 2, where the key operating parameters of the air compressor may include operating state, exhaust pressure, exhaust temperature, and the like, and the non-key operating parameters may include oil filter usage time, oil separator usage time, and the like, phase a current, phase B current, phase C current, and main motor frequency, and the like. The critical operating parameters of the pressure transmitter may include the parent pipe pressure and non-critical operating parameters may be absent.

In some examples, the data collection protocol of each device may be issued from the cloud 2 to the cloud box 12, thereby enabling data collection of the devices. In some examples, in the first communication path L1, the cloud box 12 may report the non-critical operating parameters to the cloud end 2 at the second frequency. In some examples, in the second communication path L2, the cloud box 12 may report the non-critical operating parameters to the edge server 3 at the second frequency, and the edge server 3 may report the non-critical operating parameters to the cloud end 2 at the second frequency for remote monitoring and post-hoc analysis. In some examples, the cloud 2 may perform remote OTA or other remote operations on the edge server program. In some examples, the cloud box 12 may report the key operating parameters to the edge server 3 according to the first frequency for real-time monitoring of the device, the edge server 3 may report the key operating parameters to the cloud end 2 according to the third frequency, and the cloud end 2 may participate in monitoring of the device according to the monitoring algorithm.

In some examples, cloud monitoring may be delayed from edge server monitoring. Specifically, when the monitoring of the edge server is normal, the cloud monitoring cannot be triggered, and if the monitoring of the edge server is abnormal, the monitoring of the system is switched to the cloud monitoring. Under the condition, the cloud monitoring can be used as a second monitoring level to participate in the monitoring of the equipment, and the production abnormity caused by the out-of-control equipment is prevented.

In some examples, the edge server 3 pressure lower limit may be set to trigger edge server monitoring. In some examples, the lower pressure limit value of the edge server 3 may be a third preset value. In some examples, the third preset value may be 5bar to 8bar, for example the third preset value may be 5bar, 5.5bar, 6bar, 6.5bar, 7bar, 7.5bar, 8bar, or the like. In some examples, if the data of the main pipe pressure of the pressure transmitter that gathers is less than the third preset value, edge server monitoring can be triggered to edge server 3 can send instruction to idle equipment, lets idle equipment in time start, and the pressure value of intelligence accuse system can not further descend this moment. Therefore, the pressure value of the intelligent control system can be controlled to be in a stable state, and the probability of production accidents is reduced.

In some examples, cloud monitoring may be triggered by setting a pressure lower limit for cloud 2. In some examples, the lower pressure limit of the cloud 2 may be a fourth preset value. In some examples, the third preset value may be greater than the fourth preset value. In some examples, the third preset value may be 4bar to 8bar, for example the third preset value may be 4bar, 5bar, 6bar, 7bar, or 8bar, etc. In some examples, if the monitoring of the edge server is normal, the edge server 3 may send a command to the idle industrial device and control the start-up thereof in time when the pressure value is lower than the third preset value. From this, can stabilize the pressure value of intelligence accuse system, the pressure value of intelligence accuse system can not further descend, can not trigger the high in the clouds control.

In some examples, if the edge server monitoring is abnormal, when the pressure value of the intelligent control system is lower than the third preset value, the edge server monitoring cannot be triggered, the edge server 3 cannot send a command to start the idle device in time, the pressure value will further decrease, and when the pressure value is lower than the fourth preset value, the cloud monitoring will be triggered. Under this condition, the high in the clouds control can be as reserve control, sends the instruction to idle equipment through first control link to make idle equipment start, prevent that the further low pressure of intelligent control system from causing the production accident.

In some examples, when the cloud box 12 monitors that the communication heartbeat interruption with the edge server 3 lasts for more than 10 seconds, it indicates that the second monitoring link has abnormal communication, and at this time, the cloud end 2 cannot collect the key data, the cloud box 12 may automatically report the key data to the cloud end 2 at the second frequency via the first communication path L1, and the monitoring and monitoring of the device are all switched to the link from the cloud box 12 to the cloud end 2. In this case, the critical parameters of the device can be continuously acquired to enable continuous monitoring of the device. In some examples, when the cloud box 12 monitors that the communication with the edge server 3 is resumed for more than 10 seconds, the cloud box 12 may receive an inquiry instruction from the edge server 3, update the indication bit with the message of the 4G communication, and stop reporting the 4G communication after Ts. In some examples, Ts may be 5 to 10 seconds, e.g., Ts may be 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, or 10 seconds, etc. Thereby, the cloud box 12 can be switched to a normal operating state.

Under the condition, the main and standby monitoring schemes of the device are realized, and when the communication of the second monitoring link is abnormal, the cloud box 12 automatically reports non-critical data to the cloud end 2, so that the continuity of the monitoring data is ensured. The utility model discloses be applicable to general industrial equipment control field, adopt the bimodulus monitoring scheme of edge control and high in the clouds control to edge control is given first place to, and when edge control is unusual, automatic switch-over high in the clouds control solves because the edge control link leads to the equipment to lose to ally oneself with the problem out of control unusually, effectively reduces the risk of producing the line shutdown.

According to the data acquisition method of the embodiment, interference of other data can be eliminated by building at least two communication paths from the cloud box 12 to the cloud end 2, the first type of parameters of the industrial equipment 11 are uploaded to the edge server 3 through the first sub-communication path L21 in time, and the edge server 3 carries out localized processing on the first type of parameters on an industrial site. Specifically, the edge server 3 performs partial or complete preprocessing on the acquired data of the first type of parameters, analyzes and operates according to a configured algorithm, and presents the analyzed result locally and immediately. Meanwhile, the edge server 3 can filter useless data, so that the bandwidth of data transmission can be reduced, and the load of the cloud end 2 can be relieved. In addition, the second type of parameters of the equipment are more, and the second type of parameters are uploaded to the cloud end 2 through the first communication path by configuring the lower acquisition frequency of the second type of parameters, so that the data transmission flow can be saved. When the second communication path L2 is abnormal, the data acquisition of the first type of parameters and the second type of parameters is automatically switched to the first communication path L1, in this case, the continuous acquisition of the data of the first type of parameters can be realized, and the problem that the equipment cannot be monitored due to the data loss of the key operation parameters is avoided. The cloud 2 participates in the monitoring of the equipment according to the first type of parameters of the equipment to judge whether the equipment works normally, and carries out remote monitoring and post analysis on the equipment according to the second type of parameters.

While the present disclosure has been described in detail in connection with the drawings and examples, it should be understood that the above description is not intended to limit the disclosure in any way. Those skilled in the art can make modifications and variations to the present disclosure as needed without departing from the true spirit and scope of the disclosure, which fall within the scope of the disclosure.