阅读说明：本技术 基于人工智能技术的化工园区视觉识别应用系统 (Chemical industry park visual identification application system based on artificial intelligence technology ) 是由 柏益尧 谢立 董潍龙 徐秀明 郑承兵 陆婷婷 路倩倩 鲍培 于 2021-08-03 设计创作，主要内容包括：本发明提供了基于人工智能技术的化工园区视觉识别应用系统,包括：承载有人工智能视频识别算法的算法承载服务器、承载有视觉识别应用的平台服务器、传感器、摄像头、声光电报警器,其中,视觉识别应用包括：预警报警记录模块、预警报警处理填报模块、消息通知模块。解决了在园区日常管理中,缺乏人力值守和数据资源利用,工作人员通过观测每一路视频来发现报警事件变得非常困难的问题,具有通过人工智能算法能够及时识别风险问题的优点。(The invention provides a chemical industry park visual identification application system based on artificial intelligence technology, comprising: the algorithm that bears artificial intelligence video identification algorithm bears server, bears platform server, sensor, camera, the audible-visual-electricity alarm that visual identification used, and wherein, visual identification uses and includes: the early warning device comprises an early warning recording module, an early warning processing and filling module and a message notification module. The problem of in the daily management in garden, lack power value on duty and data resource utilization, the staff finds the alarm incident through observing each way video and becomes very difficult is solved, has the advantage that can in time discern the risk problem through artificial intelligence algorithm.)

1. Chemical industry park visual identification application system based on artificial intelligence technique, its characterized in that includes:

an algorithm bearing server which bears a smoke flame recognition algorithm recognition model, a personnel off duty recognition algorithm recognition model, a personnel intrusion recognition algorithm recognition model and a tool recognition algorithm recognition model,

a platform server carrying a visual recognition application,

a sensor for acquiring and transmitting the pollution condition in each chemical warehouse in real time to the visual identification application,

a camera for video monitoring of personnel working area, safety limited space and each chemical warehouse and transmitting to visual identification application,

the acousto-optic electric alarm is used for alarming abnormal conditions and is positioned in each area of the park,

wherein the visual recognition application comprises:

a early warning record module that is used for discerning, early warning and processing to the condition of appearing, personnel's off duty condition, specific region personnel break into the condition and personnel not dress the condition as required of inflammable and explosive region smog flame, early warning record module includes: a safety early warning sub-module for identifying and processing the condition of non-dressing, off-duty and personnel intrusion which are recorded by video, a fire-fighting alarm sub-module for identifying and early warning the condition of smoke and flame in an inflammable and explosive area, a data off-line alarm sub-module for identifying and early warning when the data transmission of a camera and a sensor is in problem,

the early warning processing and filling module is used for classifying, informing, processing and filling abnormal conditions recorded by the early warning recording module, and comprises: a safety early warning processing and filling sub-module for processing and filling or ignoring the condition of not dressing, off-duty and personnel intrusion according to the actual condition, a fire fighting processing and filling sub-module for processing and filling or ignoring the condition of smoke and flame according to the actual condition, an off-line processing and filling sub-module for processing and filling or ignoring the problem of data transmission of a camera and a sensor according to the actual condition,

a message notification module for managing alarm conditions and alarm notifications, the message notification module comprising: a message push management submodule for managing alarm types, a safety early warning alarm configuration submodule for managing alarm rules,

a database for storing various types of early warning condition history records,

and the early warning prediction module is used for analyzing the historical records of various early warning occurrences to predict the occurrence probability of each early warning situation in each time period in the camera monitoring area.

2. The artificial intelligence technology-based chemical industry park vision recognition application system of claim 1, wherein the early warning prediction module comprises: and the early warning analysis submodule analyzes the input historical records of various early warning occurrences through the BP network model.

3. The artificial intelligence technology-based visual identification application system for a chemical industry park as claimed in claim 1, wherein the message notification module further comprises: and the early warning and alarming notification submodule is used for managing the notification mode.

4. The artificial intelligence technology-based chemical industry park vision recognition application system of claim 1, wherein the vision recognition application further comprises: and the enterprise on-duty reporting module is used for arranging the staff to carry out on-duty and timely verifying, processing and feeding back the video identification early warning information sent by the system.

5. The artificial intelligence technology-based chemical industry park vision recognition application system of claim 1, wherein the vision recognition application further comprises: and the early warning and alarm counting module compares, counts and displays various early warning and alarms according to the occurrence frequency, the occurrence time period and the response degree.

6. The artificial intelligence technology-based visual identification application system for the chemical industry park as claimed in claim 5, wherein the early warning and alarming statistics module comprises: the early warning and comparing submodule is used for comparing the occurrence frequency, the occurrence time period and the response degree of various early warning and alarming in the jurisdiction range through two aspects of a park and an enterprise, and the early warning and alarming trend submodule is used for displaying the content of the early warning and comparing submodule in a trend mode through an image.

7. The artificial intelligence technology-based visual identification application system for the chemical industry park as claimed in claim 1, wherein the early warning recording module is used for judging the early warning situation by calling a recognition model in an algorithm bearing server.

8. The artificial intelligence technology-based chemical industry park vision recognition application system of claim 1, wherein the vision recognition application further comprises: and the early warning and warning map module is used for video sound, light, electricity early warning and rolling broadcast.

9. An artificial intelligence technology based chemical industry park vision recognition application system as claimed in any one of claims 1 to 8, wherein the workflow of the vision recognition application includes the following steps:

s1, uploading the shot content to a visual recognition application in real time by the camera in the garden, and recognizing and judging the shot content by the visual recognition application by calling an algorithm server recognition model;

s2, after the early warning condition is identified by the identification model, the audible and visual electric alarm gives an alarm;

s3, the person on duty in the park can check the specific situation through an early warning and alarming graph module, then select to check on line or off line according to the specific situation, if all are normal after checking, fill in the processing situation through an early warning and alarming recording module;

s4, if the risk problem exists, informing the enterprise to process and dispose, and informing the gridder of the branch management enterprise to track and monitor;

and S5, if the risk problem is not effectively processed or the risk problem is upgraded, repeating the step S4, and if the risk problem is effectively processed, filling the processing condition through an early warning and alarm recording module.

Technical Field

The invention relates to the technical field of artificial intelligence, in particular to a chemical industry park visual identification application system based on artificial intelligence technology.

Background

Dangerous chemical enterprises belong to high-risk industries and are easy to generate safety production accidents. With the rapid development of video monitoring technology in recent years, a plurality of policy documents are released by the country, and all the policy documents require the chemical enterprises to strengthen video monitoring and implement whole-process monitoring on the security of operation places and factories. The provisional regulations on major dangerous source supervision and management of dangerous chemicals (the national institute of safety and supervision order No. 40) and the guide rules on investigation and treatment of the potential safety risks of dangerous chemical enterprises are provided: a video monitoring system is arranged in a place or a facility for storing highly toxic substances in a major hazard source; basic requirements of safety technology of dangerous chemical business enterprises (GB 18265-2019): the dangerous chemical warehouse is to establish a full-coverage video monitoring system in the warehouse area.

According to the latest statistical data of China petrochemical union, by 2018, 676 chemical industrial parks and industrial parks taking petroleum and chemical industry as main industries exist in national key chemical industrial parks, 23306 chemical industrial enterprises are in total, the number of the chemical industrial enterprises is large, the number of video monitors of each chemical industrial enterprise is large, the number of the video monitors is dozens if the video monitors are small, the number of the video monitors is hundreds or thousands if the video monitors are large, and the video monitors are difficult to be fully utilized through manpower.

The development of the informatization of the chemical industry park really builds the chemical industry park into a platform with deep integration of industrialization and informatization, and is important content of the standard construction of the chemical industry park. On the basis of informatization and intelligent development of the chemical industry park, the visual identification application system of the chemical industry park based on the artificial intelligence technology has good development background and wide popularization value.

However, as the number of cameras has increased rapidly, the large amount of video data has presented challenges to the effective use of real-time surveillance alarms and video data. In the daily management of the campus, the campus does not have enough manpower to watch and utilize data resources, and it becomes very difficult for workers to find alarm events by observing each video.

Disclosure of Invention

The technical problem solved by the invention is as follows: in the daily management of the campus, the campus does not have enough manpower to watch and utilize data resources, and it becomes very difficult for workers to find alarm events by observing each video.

The technical scheme of the invention is as follows:

chemical industry park visual identification application system based on artificial intelligence technique includes:

an algorithm bearing server which bears a smoke flame recognition algorithm recognition model, a personnel off duty recognition algorithm recognition model, a personnel intrusion recognition algorithm recognition model and a tool recognition algorithm recognition model,

a platform server carrying a visual recognition application,

a sensor for acquiring and transmitting the pollution condition in each chemical warehouse in real time to the visual identification application,

a camera for video monitoring of personnel working area, safety limited space and each chemical warehouse and transmitting to visual identification application,

the acousto-optic electric alarm is used for alarming abnormal conditions and is positioned in each area of the park,

wherein the visual recognition application comprises:

a early warning record module that is used for discerning, early warning and processing to the condition of appearing, personnel's off duty condition, specific region personnel break into the condition and personnel not dress the condition as required of inflammable and explosive region smog flame, early warning record module includes: a safety early warning sub-module for identifying and processing the condition of non-dressing, off-duty and personnel intrusion which are recorded by video, a fire-fighting alarm sub-module for identifying and early warning the condition of smoke and flame in an inflammable and explosive area, a data off-line alarm sub-module for identifying and early warning when the data transmission of a camera and a sensor is in problem,

the early warning processing and filling module is used for classifying, informing, processing and filling abnormal conditions recorded by the early warning recording module, and comprises: a safety early warning processing and filling sub-module for processing and filling or ignoring the condition of not dressing, off-duty and personnel intrusion according to the actual condition, a fire fighting processing and filling sub-module for processing and filling or ignoring the condition of smoke and flame according to the actual condition, an off-line processing and filling sub-module for processing and filling or ignoring the problem of data transmission of a camera and a sensor according to the actual condition,

a message notification module for managing alarm conditions and alarm notifications, the message notification module comprising: a message push management submodule for managing alarm types, a safety early warning alarm configuration submodule for managing alarm rules,

a database for storing various types of early warning condition history records,

and the early warning prediction module is used for analyzing the historical records of various early warning occurrences to predict the occurrence probability of each early warning situation in each time period in the camera monitoring area.

Further, the early warning prediction module comprises: and the early warning analysis submodule analyzes the input various early warning occurrence history records through a BP network model, and the BP network model is constructed by a BP algorithm and optimized by a genetic algorithm.

A BP Network (Back-ProPagation Network) is also called a Back ProPagation neural Network, through training of sample data, a Network weight value and a threshold value are continuously corrected to enable an error function to descend along a negative gradient direction to approach to expected output, but the Back ProPagation neural Network has the problem of low convergence speed due to the fact that iteration times are large, therefore, a genetic algorithm is firstly adopted to optimize the Back ProPagation neural Network, and the Back ProPagation neural Network can obtain an optimal solution in fewer iteration times.

Further, the message notification module further comprises: the early warning and alarming notification submodule is used for managing the notification mode, and a user can configure the early warning and alarming condition according to the actual condition of the park, so that the platform can adaptively finish the early warning work in the application process.

Further, the visual recognition application further comprises: the enterprise on-duty reporting module is used for arranging staff to carry out on duty, timely verifying, processing and feeding back video identification early warning information sent by the system, and provides checking for early warning by the enterprise on-duty reporting module, so that early warning conditions can be quickly solved.

Still further, the visual recognition application further comprises: the early warning statistical module compares, counts and displays various early warning alarms according to the occurrence frequency, the occurrence time period and the response degree, and enables an administrator to visually check the actual conditions of various early warnings.

Preferably, the early warning alarm statistic module comprises: the system comprises an early warning alarm comparison submodule for comparing the occurrence frequency, the occurrence time period and the response degree of various early warning alarms in the jurisdiction range in two aspects of a park and an enterprise, and an early warning alarm trend submodule for displaying the content of the early warning alarm comparison submodule in a trend way through image pairs, wherein the two submodules are used for comparing and displaying early warning historical data, so that an administrator can visually check the actual conditions of various early warnings, and the subsequent park management mode can be conveniently adjusted.

Preferably, the early warning alarm recording module finishes the judgment of the early warning condition by calling the recognition model in the algorithm bearing server, and a mature artificial intelligence recognition algorithm can ensure the recognition accuracy and finish the closed-loop management of the park.

Preferably, the visual recognition application further comprises: a warning picture module that is used for video reputation warning and rolling to report, the user can directly look over the warning in real time through warning picture module and get the real-time condition in region, greatly reduced risk debugging cost.

Further preferably, the workflow of the visual recognition application comprises the steps of:

s1, uploading the shot content to a visual recognition application in real time by the camera in the garden, and recognizing and judging the shot content by the visual recognition application by calling an algorithm server recognition model;

s2, after the early warning condition is identified by the identification model, the audible and visual electric alarm gives an alarm;

s3, the person on duty in the park can check the specific situation through an early warning and alarming graph module, then select to check on line or off line according to the specific situation, if all are normal after checking, fill in the processing situation through an early warning and alarming recording module;

s4, if the risk problem exists, informing the enterprise to process and dispose, and informing the gridder of the branch management enterprise to track and monitor;

and S5, if the risk problem is not effectively processed or the risk problem is upgraded, repeating the step S4, and if the risk problem is effectively processed, filling the processing condition through an early warning and alarm recording module.

The invention has the beneficial effects that:

1. the problem that massive video data are difficult to view in real time through manpower and hidden dangers are found in time is solved;

2. a new mode of park and enterprise management is developed, video monitoring and video identification are carried out aiming at the key field of enterprise safety risk, and enterprise management standardization is promoted through invisible eyes and mouths;

3. the data is applied again, the video intelligent identification early warning alarm information is not the purpose, the purposes of finding hidden danger, solving hidden danger and improving the comprehensive management level are achieved through the video intelligent identification early warning alarm information, and the video monitoring of enterprises is really realized;

4. the invention identifies and reports various early warning conditions by calling the identification model in the algorithm bearing server, analyzes the historical data by the neural network after the historical data is obtained, predicts the occurrence probability of each time period in a future period of time of various early warning conditions, is convenient for a park manager to distribute personnel according to the prediction result, fundamentally reduces the occurrence probability of the early warning conditions, and greatly improves the solution efficiency when the early warning conditions occur.

Drawings

FIG. 1 is a flowchart of the operation of embodiment 2 of the present invention;

fig. 2 is a flowchart of the operation of embodiment 3 of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, 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 invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a plurality" typically includes at least two.

It should be understood that although the terms first, second, third, etc. may be used to describe … … in embodiments of the present invention, these … … should not be limited to these terms. These terms are used only to distinguish … …. For example, the first … … can also be referred to as the second … … and similarly the second … … can also be referred to as the first … … without departing from the scope of embodiments of the present invention.

Example 1

Chemical industry park visual identification application system based on artificial intelligence technique includes:

an algorithm bearing server which bears a smoke flame recognition algorithm recognition model, a personnel off duty recognition algorithm recognition model, a personnel intrusion recognition algorithm recognition model and a tool recognition algorithm recognition model,

a platform server carrying a visual recognition application,

a sensor for acquiring and transmitting the pollution condition in each chemical warehouse in real time to a visual identification application,

a camera for video monitoring of personnel working area, safety limited space and each chemical warehouse and transmitting to visual identification application,

the acousto-optic electric alarm is used for alarming abnormal conditions and is positioned in each area of the park,

wherein the visual recognition application comprises:

a early warning record module that is used for discerning, early warning and processing to the condition of appearing, personnel's off the post condition, the specific region personnel condition of invading into and personnel are not dressing the condition as required to inflammable and explosive region smog flame, and early warning record module includes: a safety early warning sub-module for identifying and processing the condition of non-dressing, off-duty and personnel intrusion which are recorded by video, a fire-fighting alarm sub-module for identifying and early warning the condition of smoke and flame in an inflammable and explosive area, a data off-line alarm sub-module for identifying and early warning when the data transmission of a camera and a sensor is in problem,

the early warning processing and filling module is used for classifying, informing, processing and filling abnormal conditions recorded by the early warning recording module, and comprises: a safety early warning processing and filling sub-module for processing and filling or ignoring the condition of not dressing, off-duty and personnel intrusion according to the actual condition, a fire fighting processing and filling sub-module for processing and filling or ignoring the condition of smoke and flame according to the actual condition, an off-line processing and filling sub-module for processing and filling or ignoring the problem of data transmission of a camera and a sensor according to the actual condition,

a message notification module for managing alarm conditions and alarm notifications, the message notification module comprising: a message push management submodule for managing alarm types, a safety early warning alarm configuration submodule for managing alarm rules, an early warning alarm notification submodule for managing notification modes,

an enterprise on-duty reporting module used for arranging the staff to carry out on-duty and timely verifying, processing and feeding back the video identification early warning information sent by the system,

a database for storing various types of early warning condition history records,

the early warning prediction module is used for analyzing historical records of various early warnings so as to predict the occurrence probability of each early warning condition in each time period in a camera monitoring area, and comprises: and the early warning analysis submodule analyzes the input various early warning occurrence history records through a BP network model, and the BP network model is constructed by a BP algorithm and optimized by a genetic algorithm.

The input of the BP network model is history records of various early warning occurrences in a certain monitoring area, the output of the BP network model is prediction of the occurrence probability of various early warning situations in each time period of the area every day within 15 days in the future, the interval of each time period is 3 hours, a system administrator can inquire the occurrence probability of various early warning situations in the specific area within 15 days in the future through the early warning prediction module, after the prediction result is obtained, personnel arrangement in key time periods is completed through the enterprise on-duty report module, and therefore economic losses caused by untimely early warning processing and unreasonable personnel arrangement are reduced as far as possible.

The early warning and alarm recording module finishes the judgment of the early warning condition by calling an identification model in the algorithm bearing server.

The invention applies the intelligent video identification such as smoke, flame identification, personnel break-in identification, personnel off duty identification and tool identification to the management of chemical enterprises, and has the following main application scenes:

1. smoke, flame recognition scenario: chemical product warehouse of chemical industry enterprise, etc.

2. Human intrusion into the scene: whether a person intrudes into a specific area such as a safety-restricted space.

3. Person off duty scene: whether the personnel are on duty according to the rules in a specific area such as a production workshop or not.

4. The person sleeping scene is as follows: whether the person has the post sleeping behavior in a specific area such as a monitoring room.

5. Recognizing scenes by the tool: whether a person in the second door of the chemical enterprise wears a safety helmet or a safety garment.

Example 2

The embodiment is a workflow based on the visual recognition application of embodiment 1, and includes the following steps:

s1, uploading the shot content to a visual recognition application in real time by the camera in the garden, and recognizing and judging the shot content by the visual recognition application by calling an algorithm server recognition model;

s2, after the early warning condition is identified by the identification model, the audible and visual electric alarm gives an alarm;

s3, performing offline verification by the operator on duty in the park, and filling the processing condition through the early warning and alarm recording module if all the verification is normal;

s4, if the risk problem exists, informing the enterprise to process and dispose, and informing the gridder of the branch management enterprise to track and monitor;

and S5, if the risk problem is not effectively processed or the risk problem is upgraded, repeating the step S4, and if the risk problem is effectively processed, filling the processing condition through an early warning and alarm recording module.

Example 3

The present embodiment is another application scenario based on the visual recognition application of embodiment 1, and includes the following steps:

s1, a system administrator inquires the occurrence probability of various early warning conditions (smoke flame identification, personnel break-in, personnel fall off, personnel sleep, personnel do not wear safety helmets and personnel do not wear safety clothes) in each time period of 15 days in the future of the chemical warehouse through an early warning prediction module, wherein the interval of each time period is 3 hours;

s2, after the system administrator obtains the result output by the early warning prediction module, the personnel arrangement of the chemical warehouse in the key time period is completed through the enterprise on duty report module, so that the economic loss caused by untimely early warning treatment and unreasonable personnel allocation is reduced as much as possible;

s3, uploading the shot content to a visual recognition application in real time by a camera in the chemical warehouse, and carrying out recognition and judgment on the shot content by the visual recognition application by calling an algorithm server recognition model;

s2, after the early warning condition is identified by the identification model, the audible and visual electric alarm gives an alarm;

s3, the on-duty personnel of the chemical warehouse checks the chemical warehouse off-line, if all are normal after checking, the processing condition is filled in through the early warning and alarm recording module;

s4, if the risk problem exists, informing the enterprise to process and dispose, and informing the gridder of the branch management enterprise to track and monitor;

and S5, if the risk problem is not effectively processed or the risk problem is upgraded, repeating the step S4, and if the risk problem is effectively processed, filling the processing condition through an early warning and alarm recording module.

Example 4

The visual recognition application further comprises: and the early warning and warning map module is used for video sound, light, electricity early warning and rolling broadcast.

Example 5

The embodiment is a workflow based on the visual recognition application of embodiment 4, and includes the following steps:

s1, uploading the shot content to a visual recognition application in real time by the camera in the garden, and recognizing and judging the shot content by the visual recognition application by calling an algorithm server recognition model;

s2, after the early warning condition is identified by the identification model, the audible and visual electric alarm gives an alarm;

s3, the person on duty in the park can check the specific situation through an early warning and alarming graph module, then select to check on line or off line according to the specific situation, if all are normal after checking, fill in the processing situation through an early warning and alarming recording module;

s4, if the risk problem exists, informing the enterprise to process and dispose, and informing the gridder of the branch management enterprise to track and monitor;

and S5, if the risk problem is not effectively processed or the risk problem is upgraded, repeating the step S4, and if the risk problem is effectively processed, filling the processing condition through an early warning and alarm recording module.

Example 6

Early warning alarm statistics module that compares, makes statistics of, demonstrates all kinds of early warning through frequency of occurrence, time quantum of occurrence and degree of response respectively, and early warning alarm statistics module includes:

the early warning and comparing submodule is used for comparing the occurrence frequency, the occurrence time period and the response degree of various early warning and alarming in the jurisdiction range through two aspects of a park and an enterprise, and the early warning and alarming trend submodule is used for displaying the content of the early warning and comparing submodule in a trend mode through an image.