CN112966903A - Dangerous chemical safety production risk monitoring and early warning system and method - Google Patents
Dangerous chemical safety production risk monitoring and early warning system and method Download PDFInfo
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Abstract
The invention discloses a dangerous chemical safety production risk monitoring and early warning system and a dangerous chemical safety production risk monitoring and early warning method, wherein the system comprises a dangerous chemical safety production risk monitoring and early warning system; the method comprises the following steps: extracting and summarizing monitoring information; collecting and transmitting monitoring information; analyzing and early warning; violation/exception alarm handling. The invention realizes real-time online monitoring and early warning based on the technology of the Internet of things, realizes the transmission of monitoring data of the Internet of things to the cloud for centralized processing, can timely discover and eliminate hidden dangers, prevents major risks and restrains serious and extra-large accidents; automatically detecting the unsafe behaviors of people and the unsafe state of objects through intelligent video analysis; and simultaneously, interconnection and intercommunication with other information systems are realized.
Description
Technical Field
The invention relates to the technical field of safety monitoring, in particular to a dangerous chemical safety production risk monitoring and pre-warning system and method.
Background
With the rapid development of national economy, the number of dangerous chemical enterprises is continuously increased, the national dangerous chemical enterprises still have the problems of automation, incomplete monitoring and control facilities, low level of monitoring and early warning informatization degree and the like, and great pressure is brought to supervision work.
The dangerous chemical safety production risk monitoring is informationized, networked and low in intelligentization level, video monitoring and related alarm sensor equipment are installed aiming at major danger sources, key places and key areas, a certain effect is achieved on timely finding of hidden dangers and standardization of safety production behaviors, however, the intelligent video analysis application and the three-dimensional oblique photography application of the key areas are lacked, and intelligent identification can not be conducted on site abnormal conditions, personnel violation behaviors, operation control measures, equipment and facility safety hidden dangers and the like.
Disclosure of Invention
The invention aims to provide a dangerous chemical safety production risk monitoring and early warning system for solving the problems, which comprises a basic layer, a data layer, a business application layer and a comprehensive display layer;
the basic layer is connected with the data layer; the data layer is connected with the service application layer; the service application layer is connected with the comprehensive display layer;
the basic layer comprises an internet of things network infrastructure and is used for acquiring basic data; the Internet of things network infrastructure comprises a data processing unit, a database, an Internet of things module, a video monitoring unit and an Internet communication module,
the data layer is used for storing and processing basic data, and the basic data comprises monitoring early warning data, risk data and video streaming media data; data analysis processing is carried out by setting a data analysis model, wherein the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model; accessing a base layer database by adopting a JDBC background database access method, and providing a data access interface for an application support layer and a service application layer;
the application support layer adopts a micro-service architecture, integrates various protocols, is used for providing remote service call for the service application layer, and comprises a plurality of service applications:
the unified authentication module is used for providing unified user management, authority management and authentication management services;
the Internet of things application support system is used for sensing interconnection of the Internet of things and transmitting sensed information to the business application layer;
the geographic information service system is used for processing vector data and grid map data containing spatial information, remote sensing image data containing the spatial information and geographic information data;
the message middleware is used for providing message communication support for information communication between service applications and providing support for synchronous or asynchronous message receiving and sending between service applications;
the workflow engine is used for making and managing a business process;
the mobile application system is used for unified integration and unified access of mobile terminal application;
the report service system is used for rapidly arranging and developing the report style and the content, and realizing rapid customization and development of the data report;
the front end constructs a service system and provides the display of componentized and modularized business application and business process;
the business process comprises enterprise basic information management, administrative license management, standardized management, dangerous chemical management, safe investment management, major dangerous source management, operation place management, product material management, production process management, enterprise personnel management and safety education training;
the service application layer is built by adopting Nginx middleware, developed by adopting Java language, comprises a plurality of service application management units, calls application support layer data through an API (application programming interface) interface and is used for uniformly classifying, monitoring and managing data processing results according to a service flow according to a data analysis model;
and the comprehensive display layer adopts a B/S architecture browser and is used for visualizing the data of the service application layer.
The risk monitoring and early warning method for the safe production of the dangerous chemicals comprises the following steps:
the method comprises the following steps: extracting and summarizing monitoring information: extracting and summarizing the Internet of things safety data deployed at the front end, including video monitoring images, violation video analysis data and Internet of things monitoring data acquired by a gateway;
step two: monitoring information acquisition and transmission: transmitting the Internet of things data acquired in the step one by using an operator special line converged on a government affair cloud platform;
step three: analyzing and early warning: the method comprises the steps that a data analysis model provided by an application supporting layer is utilized, the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model to generate a video intelligent analysis result, an equipment running state analysis result and alarm information, and the generated early warning result is pushed to a monitoring receiving end through the application supporting layer;
step four: violation/exception alarm handling: the system pushes the early warning information to the monitoring receiving end through unified message service provided by the application support, the monitoring receiving end performs on-site checking treatment after receiving the information, the treatment condition is uploaded through the system, and the system automatically feeds back the information uploaded by the monitoring receiving end to the monitoring receiving end.
The invention realizes the purpose through the following technical scheme:
the invention has the beneficial effects that: according to the invention, the system is intensively deployed at the cloud, the Internet of things safety data acquisition gateway is deployed at the enterprise site, and the gateway can ensure that the enterprise production network cannot be attacked by the external network by isolating the enterprise production network and the external network, so that the one-way transmission of the enterprise production data is ensured, the Internet of things monitoring data is transmitted to the cloud for centralized processing, and each level of supervision departments can remotely patrol;
according to the invention, through the construction and implementation of the risk monitoring and early warning system for the safe production of dangerous chemicals, the purposes of starting from a risk source before undertaking, monitoring and early warning are realized, hidden dangers can be found and eliminated in time, serious risks are prevented, and the occurrence of serious accidents is restrained; the invention adopts sensing monitoring based on the technology of the Internet of things to acquire various safety technical parameters in real time, and realizes real-time online monitoring and early warning by combining an alarm threshold value; automatically detecting the unsafe behaviors of people and the unsafe state of objects through intelligent video analysis;
the invention realizes supporting of a dangerous chemical safety production risk monitoring and early warning application system, monitoring and early warning data aggregation and display of safety production key industries and interconnection and intercommunication with other information systems by applying supporting layer construction.
Drawings
FIG. 1 is a system diagram of the present invention;
FIG. 2 is a schematic flow diagram of the process of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings in which:
as shown in the attached figure 1, the dangerous chemical safety production risk monitoring and early warning system comprises a basic layer, a data layer, a business application layer and a comprehensive display layer;
the basic layer is connected with the data layer; the data layer is connected with the service application layer; the service application layer is connected with the comprehensive display layer;
the basic layer comprises an internet of things network infrastructure and is used for acquiring basic data; the Internet of things network infrastructure comprises a data processing unit, a database, an Internet of things module, a video monitoring unit and an Internet communication module,
the data layer is used for storing and processing basic data, and the basic data comprises monitoring early warning data, risk data and video streaming media data; data analysis processing is carried out by setting a data analysis model, wherein the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model; accessing a base layer database by adopting a JDBC background database access method, and providing a data access interface for an application support layer and a service application layer; because the data acquisition quantity is huge, the data is divided in different dimensions in a mode of creating an index table for physical partitioning and a mode of logically dividing the table, the storage pressure of a single table is reduced, and the data insertion and query speed is improved;
the application support layer adopts a micro-service architecture, integrates various protocols, is used for providing remote service call for the service application layer, and comprises a plurality of service applications:
the unified authentication module is used for providing unified user management, authority management and authentication management services;
the Internet of things application support system is used for sensing interconnection of the Internet of things and transmitting sensed information to the business application layer;
the geographic information service system is used for processing vector data and grid map data containing spatial information, remote sensing image data containing the spatial information and geographic information data;
the message middleware is used for providing message communication support for information communication between service applications and providing support for synchronous or asynchronous message receiving and sending between service applications;
the workflow engine is used for making and managing a business process;
the mobile application system is used for unified integration and unified access of mobile terminal application;
the report service system is used for rapidly arranging and developing the report style and the content, and realizing rapid customization and development of the data report;
the front end constructs a service system and provides the display of componentized and modularized business application and business process;
the business process comprises enterprise basic information management, administrative license management, standardized management, dangerous chemical management, safe investment management, major dangerous source management, operation place management, product material management, production process management, enterprise personnel management and safety education training;
the service application layer is built by adopting Nginx middleware, developed by adopting Java language, comprises a plurality of service application management units, calls application support layer data through an API (application programming interface) interface and is used for uniformly classifying, monitoring and managing data processing results according to a service flow according to a data analysis model;
and the comprehensive display layer adopts a B/S architecture browser and is used for visualizing the data of the service application layer.
Specifically, the business application comprises a file information management unit, a risk situation dynamic studying and judging unit, an accident emergency support unit, a risk comprehensive analysis unit, a risk distribution unit, a monitoring and early warning unit, a risk dynamic early warning unit, a supervision feedback unit, an online patrol unit, a safety risk studying and judging and committing unit and an enterprise-level application unit;
the file information management unit is used for enterprise basic information management, administrative license management, standardized management, dangerous chemical management, safe investment management, major dangerous source management, operation place management, product material management, production process management, enterprise personnel management and safety education training management;
the risk situation dynamic studying and judging unit is used for studying and judging the risk situation dynamic of the environment sensitive point, the risk situation dynamic of the population dense area, the risk situation dynamic of the key supervision industry, the risk situation dynamic of the key supervision chemical industry park and the risk situation dynamic of the severe climate;
the emergency supporting unit is used for emergency resource statistics, chemical knowledge map and video monitoring and calling;
the risk comprehensive analysis unit is used for enterprise risk early warning trend analysis, high risk early warning factor analysis, risk early warning non-feedback rate, key supervision dangerous chemical comprehensive analysis and key supervision chemical process comprehensive analysis;
the risk distribution unit is used for managing dangerous chemical enterprise information, major hazard source information, key supervision dangerous chemical information, key supervision process information and key supervision area information;
the monitoring and early warning unit is used for early warning information monitoring, potential safety hazard intelligent identification, video monitoring and early warning record inquiry;
the risk dynamic early warning unit is used for enterprise risk early warning, important supervision dangerous chemical risk early warning, important supervision chemical process risk early warning and population dense area risk early warning;
the supervision feedback unit is used for early warning notification and historical information inquiry;
the online patrol unit is used for online monitoring access data condition patrol, visual supervision, monitoring early warning analysis and reporting;
the safety risk research and judgment and commitment unit is used for filling and submitting the commitment information of the enterprise and checking the commitment information of the enterprise by a supervision department;
and the enterprise-level application unit is used for basic information management, enterprise daily reports, data monitoring, visual management, information reminding, supervision feedback, safety risk research and judgment and commitment filling.
Specifically, the data monitoring analysis model is as follows: let TxScoring of real-time monitoring data, RxIs the arithmetic mean of the risk values of all accessed points, RiFor a single access point location risk value, n is the number of access point locations, then:
Tx＝20×(5-Rx)；
specifically, the system operation state analysis model is as follows: let TyFor safety monitoring of the system operating state values, RyIs the arithmetic mean of the failure rate and the off-line rate, RfFailure rate of all detectors in 24 hours, RoFor off-line rate of all detectors in 24 hours, Rf，iIs the failure rate, R, of one detector in 24 hourso，iIf the off-line rate of a detector in 24 hours has more than 5 times of alarm cameras/number of configured video analysis cameras in 24 hours, then:
Ty＝100×(1-Ry)；
specifically, the video intelligent analysis data model is as follows: let TzScore value, R, for video intelligence analysiszIf the number of alarm cameras/the number of configured video analysis cameras is more than 5 times in 24 hours, then:
Tz＝65+35×(1-Rz)。
specifically, the risk data analysis model is as follows:
setting R as an enterprise safety production risk index value; t isiScoring the enterprise base information; t isxData score values are monitored in real time for major hazard sources; t isyScoring the operating state of the safety monitoring system; t iszIntelligently analyzing the score value for the video; t isaAdding value; gamma rayiCorrection factor, gamma, for the enterprise base information scorexCorrection coefficient, gamma, for real-time monitoring data score of major hazardyCorrection factor, gamma, for the value of the operating state score of the safety monitoring systemzScore correction factor, gamma, for video intelligence analysisaA correction factor is added to the score; then:
R＝γi×Ti+γx×Tx+γy×Ty+γz×Tz+γa×Ta。
specifically, the enterprise basic information score correction coefficient, the major hazard source real-time monitoring score correction coefficient, the safety monitoring system operating state score correction coefficient, the video intelligent analysis score correction coefficient, the enterprise basic information score correction coefficient, the major hazard source real-time monitoring data score correction coefficient, the safety monitoring system operating state score correction coefficient, and the video intelligent analysis score correction coefficient are all set values.
Scoring the enterprise basic information, and judging the scoring according to the record of whether education training, regulation and regulation, emergency plan, emergency drill and safety investment exist; the real-time monitoring score of the major hazard source is obtained by deducting the grade of the emerging major hazard source, whether dangerous chemicals exist, the qualification of safety responsible persons and the monitoring of the dangerous process, and if no major hazard source exists, the score is not obtained.
The risk monitoring and early warning method for the safe production of the dangerous chemicals comprises the following steps:
the method comprises the following steps: extracting and summarizing monitoring information: extracting and summarizing the Internet of things safety data deployed at the front end, including video monitoring images, violation video analysis data and Internet of things monitoring data acquired by a gateway;
step two: monitoring information acquisition and transmission: transmitting the Internet of things data acquired in the step one by using an operator special line converged on a government affair cloud platform;
step three: analyzing and early warning: the method comprises the steps that a data analysis model provided by an application supporting layer is utilized, the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model to generate a video intelligent analysis result, an equipment running state analysis result and alarm information, and the generated early warning result is pushed to a monitoring receiving end through the application supporting layer;
step four: violation/exception alarm handling: the system pushes the early warning information to the monitoring receiving end through unified message service provided by the application support, the monitoring receiving end performs on-site checking treatment after receiving the information, the treatment condition is uploaded through the system, and the system automatically feeds back the information uploaded by the monitoring receiving end to the monitoring receiving end.
Specifically, the data layer adopts JDBC background database access technology to realize access to the database in the base layer, and provides data access interfaces for the service application layer and the application support layer; because the data acquisition quantity is huge, the data are split in different dimensions in the ways of creating indexes, physically partitioning the table and logically partitioning the table, the storage pressure of a single table is reduced, and the data insertion and query speed is increased
According to the invention, the system is intensively deployed at the cloud, the Internet of things safety data acquisition gateway is deployed at the enterprise site, and the gateway ensures that the enterprise production network cannot be attacked by the external network by isolating the enterprise production network and the external network, so that the one-way transmission of the enterprise production data is ensured, the monitoring data of the Internet of things is transmitted to the cloud for centralized processing, and each level of supervision departments can remotely patrol;
according to the invention, through the construction and implementation of the risk monitoring and early warning system for the safe production of dangerous chemicals, the purposes of starting from a risk source before undertaking, monitoring and early warning are realized, hidden dangers can be found and eliminated in time, serious risks are prevented, and the occurrence of serious accidents is restrained; the invention adopts sensing monitoring based on the technology of the Internet of things to acquire various safety technical parameters in real time, and realizes real-time online monitoring and early warning by combining an alarm threshold value; automatically detecting the unsafe behaviors of people and the unsafe state of objects through intelligent video analysis;
the invention realizes supporting of a dangerous chemical safety production risk monitoring and early warning application system, monitoring and early warning data aggregation and display of safety production key industries and interconnection and intercommunication with other information systems by applying supporting layer construction.
The technical solution of the present invention is not limited to the limitations of the above specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the protection scope of the present invention.
Claims (8)
1. The dangerous chemical safety production risk monitoring and early warning system is characterized by comprising a basic layer, a data layer, a business application layer and a comprehensive display layer;
the basic layer is connected with the data layer; the data layer is connected with the service application layer; the service application layer is connected with the comprehensive display layer;
the basic layer comprises an internet of things network infrastructure and is used for acquiring basic data; the Internet of things network infrastructure comprises a data processing unit, a database, an Internet of things module, a video monitoring unit and an Internet communication module,
the data layer is used for storing and processing basic data, and the basic data comprises monitoring early warning data, risk data and video streaming media data; data analysis processing is carried out by setting a data analysis model, wherein the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model; accessing a base layer database by adopting a JDBC background database access method, and providing a data access interface for an application support layer and a service application layer;
the application support layer adopts a micro-service architecture, integrates various protocols, is used for providing remote service call for the service application layer, and comprises a plurality of service applications:
the unified authentication module is used for providing unified user management, authority management and authentication management services;
the Internet of things application support system is used for sensing interconnection of the Internet of things and transmitting sensed information to the business application layer;
the geographic information service system is used for processing vector data and grid map data containing spatial information, remote sensing image data containing the spatial information and geographic information data;
the message middleware is used for providing message communication support for information communication between service applications and providing support for synchronous or asynchronous message receiving and sending between service application programs;
the workflow engine is used for making and managing a business process;
the mobile application system is used for unified integration and unified access of mobile terminal application;
the report service system is used for rapidly arranging and developing services of report styles and contents, and realizing rapid customization and development of data reports;
the front end constructs a service system and provides the display of componentized and modularized business application and business process;
the business process comprises enterprise basic information management, administrative license management, standardized management, dangerous chemical management, safe investment management, major dangerous source management, operation place management, product material management, production process management, enterprise personnel management and safety education training;
the service application layer is built by adopting Nginx middleware, developed by adopting Java language, comprises a plurality of service application management units, calls application support layer data through an API (application programming interface) interface and is used for uniformly classifying, monitoring and managing data processing results according to a service flow according to a data analysis model;
and the comprehensive display layer adopts a B/S architecture browser and is used for visualizing the data of the service application layer.
2. The dangerous chemical safety production risk monitoring and early warning system according to claim 1, wherein the business application management unit comprises a file information management unit, a risk situation dynamic study and judgment unit, an accident emergency support unit, a risk comprehensive analysis unit, a risk distribution unit, a monitoring and early warning unit, a risk dynamic early warning unit, a supervision feedback unit, an online patrol unit, a safety risk study and judgment and commitment unit, and an enterprise-level application unit;
the file information management unit is used for enterprise basic information management, administrative license management, standardized management, dangerous chemical management, safe investment management, major dangerous source management, operation place management, product material management, production process management, enterprise personnel management and safety education training management;
the risk situation dynamic studying and judging unit is used for studying and judging the risk situation dynamic of the environment sensitive point, the risk situation dynamic of the population dense area, the risk situation dynamic of the key supervision industry, the risk situation dynamic of the key supervision chemical industry park and the risk situation dynamic of the severe climate;
the emergency supporting unit is used for emergency resource statistics, chemical knowledge map and video monitoring and calling;
the risk comprehensive analysis unit is used for enterprise risk early warning trend analysis, high risk early warning factor analysis, risk early warning non-feedback rate, key supervision hazardous chemical comprehensive analysis and key supervision chemical process comprehensive analysis;
the risk distribution unit is used for managing dangerous chemical enterprise information, major hazard source information, key supervision dangerous chemical information, key supervision process information and key supervision area information;
the monitoring and early warning unit is used for early warning information monitoring, potential safety hazard intelligent identification, video monitoring and early warning record inquiry;
the risk dynamic early warning unit is used for enterprise risk early warning, important supervision dangerous chemical risk early warning, important supervision chemical process risk early warning and population dense area risk early warning;
the supervision feedback unit is used for early warning notification and historical information inquiry;
the online patrol unit is used for online monitoring access data condition patrol, visual supervision, monitoring early warning analysis and reporting;
the safety risk studying, judging and committing unit is used for filling and reporting the commitment information of the enterprise and checking the committed information of the enterprise by a supervision department;
and the enterprise-level application unit is used for basic information management, enterprise daily reports, data monitoring, visual management, information reminding, supervision feedback, safety risk research and judgment and commitment filling.
3. The dangerous chemical safety production risk monitoring and early warning system according to claim 1, wherein the data monitoring and analyzing model is: let TxScoring of real-time monitoring data, RxIs the arithmetic mean of the risk values of all accessed points, RiFor a single access point location risk value, n is the number of access point locations, then:
Tx＝20×(5-Rx)；
4. the dangerous chemical safety production risk monitoring and early warning system according to claim 1, wherein the system operation state analysis model is: let TyFor safety monitoring of the system operating state values, RyIs the arithmetic mean of the failure rate and the off-line rate, RfFailure rate of all detectors in 24 hours, RoFor off-line rate of all detectors in 24 hours, Rf，iIs the failure rate of one detector within 24 hours,Ro，ithe off-line rate of a detector within 24 hours is that the number of alarm cameras/the number of configured video analysis cameras is more than 5 times within 24 hours, then:
Ty＝100×(1-Ry)；
5. the dangerous chemical safety production risk monitoring and early warning system according to claim 1, wherein the video intelligent analysis data model is: let TzScore value, R, for video intelligence analysiszIf the number of alarm cameras/the number of configured video analysis cameras is more than 5 times in 24 hours, then:
Tz＝65+35×(1-Rz)。
6. the risk monitoring and early warning system for the safe production of dangerous chemicals according to claim 1, wherein the risk data analysis model is:
setting R as an enterprise safety production risk index value; t isiScoring the enterprise base information; t isxData score values are monitored in real time for major hazard sources; t isyScoring the operating state of the safety monitoring system; t iszIntelligently analyzing the score value for the video; t isaAdding value; gamma rayiCorrection factor, gamma, for the enterprise base information scorexCorrection coefficient, gamma, for real-time monitoring data score of major hazardyCorrection factor, gamma, for the value of the operating state score of the safety monitoring systemzScore correction factor, gamma, for video intelligence analysisaA correction factor is added to the score; then:
R＝γi×Ti+γx×Tx+γy×Ty+γz×Tz+γa×Ta
7. the dangerous chemical safety production risk monitoring and early warning system according to claim 6, wherein the enterprise basic information score correction coefficient, the major hazard source real-time monitoring score correction coefficient, the safety monitoring system operating state score correction coefficient, the video intelligent analysis score correction coefficient, the enterprise basic information score correction coefficient, the major hazard source real-time monitoring data score correction coefficient, the safety monitoring system operating state score correction coefficient, and the video intelligent analysis score correction coefficient are all set values.
8. The risk monitoring and early warning method for the safe production of the dangerous chemicals is characterized by comprising the following steps of:
the method comprises the following steps: extracting and summarizing monitoring information: extracting and summarizing the Internet of things safety data deployed at the front end, including video monitoring images, violation video analysis data and Internet of things monitoring data acquired by an acquisition gateway;
step two: monitoring information acquisition and transmission: transmitting the Internet of things data acquired in the step one by using an operator special line converged on a government affair cloud platform;
step three: analyzing and early warning: the method comprises the steps that a data analysis model provided by an application supporting layer is utilized, the data analysis model comprises a data monitoring analysis model, a system running state analysis model, a risk data analysis model and a video streaming media data analysis model to generate a video intelligent analysis result, an equipment running state analysis result and alarm information, and the generated early warning result is pushed to a monitoring receiving end through the application supporting layer;
step four: violation/exception alarm handling: the system pushes the early warning information to the supervision receiving end through unified message service provided by the application support, the supervision receiving end performs on-site check treatment after receiving the information, the treatment condition is uploaded through the system, and the system automatically feeds back the information uploaded by the supervision receiving end to the supervision receiving end.
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