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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 PDF

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CN112966903A
CN112966903A CN202110156269.9A CN202110156269A CN112966903A CN 112966903 A CN112966903 A CN 112966903A CN 202110156269 A CN202110156269 A CN 202110156269A CN 112966903 A CN112966903 A CN 112966903A
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徐燕生
廖长明
敬志坚
庄永忠
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Chengdu Dinganhua Wisdom Internet Of Things Co ltd
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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

Dangerous chemical safety production risk monitoring and early warning system and method
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.
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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)；
Figure BDA0002933619050000071
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)；
Figure BDA0002933619050000072
Figure RE-GDA0003030360880000073
Figure BDA0002933619050000074
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.危险化学品安全生产风险监测预警系统，其特征在于，包括基础层、数据层、业务应用层与综合展示层；1. A risk monitoring and early warning system for safe production of hazardous chemicals, characterized in that it includes a basic layer, a data layer, a business application layer and a comprehensive display layer; 基础层与数据层相连；数据层与业务应用层相连；业务应用层与综合展示层相连；The basic layer is connected with the data layer; the data layer is connected with the business application layer; the business application layer is connected with the comprehensive display layer; 基础层包括物联网网络基础设施，用于基础数据获取；物联网网络基础设施包括数据处理单元、数据库、物联网模块、视频监控单元、互联网通信模块，The basic layer includes the Internet of Things network infrastructure for basic data acquisition; the Internet of Things network infrastructure includes data processing units, databases, Internet of Things modules, video surveillance units, and Internet communication modules. 数据层，用于存储和处理基础数据，基础数据包括监测预警数据、风险数据、视频流媒体数据；通过设置数据分析模型进行数据分析处理，数据分析模型包括数据监测分析模型、系统运行状态分析模型、风险数据分析模型与视频流媒体数据分析模型；采用JDBC后台访问数据库的方法访问基础层数据库，并为应用支撑层与业务应用层提供数据访问接口；The data layer is used to store and process basic data, including monitoring and early warning data, risk data, and video streaming media data; data analysis and processing are performed by setting data analysis models, which include data monitoring and analysis models, and system operating status analysis models. , risk data analysis model and video streaming media data analysis model; use JDBC background access database method to access the base layer database, and provide data access interfaces for the application support layer and the business application layer; 应用支撑层，采用微服务架构，集成多种协议，用于为业务应用层提供远程服务调用，包括多个业务应用：The application support layer adopts a micro-service architecture and integrates multiple protocols to provide remote service calls for the business application layer, including multiple business applications: 统一认证模块，提供统一的用户管理、权限管理和认证管理服务；Unified authentication module, providing unified user management, authority management and authentication management services; 物联网应用支撑系统，用于物联网感知互联，把感知到的信息传送到业务应用层；The IoT application support system is used for the IoT perception interconnection and transmits the perceived information to the business application layer; 地理信息服务系统，用于包含空间信息的矢量数据和栅格地图数据以及包含空间信息的遥感影像数据、地理信息数据处理；Geographic information service system for processing vector data and raster map data containing spatial information, remote sensing image data and geographic information data containing spatial information; 消息中间件，用于为业务应用之间的信息通讯提供消息通信支撑以及为业务应用程序之间同步或异步收发消息提供支持；Message middleware, which is used to provide message communication support for information communication between business applications and to provide support for synchronous or asynchronous sending and receiving of messages between business applications; 工作流引擎，用于业务流程制定与管理；Workflow engine for business process formulation and management; 移动应用系统，用于移动端应用统一集成与统一接入；Mobile application system for unified integration and unified access of mobile applications; 报表服务系统，用于报表样式、内容的快速编排和开发服务，实现数据报表的快速定制和开发；The report service system is used for the rapid arrangement and development of report style and content, and realizes the rapid customization and development of data reports; 前端构建服务系统，提供组件化、模块化业务应用与业务流程的展示；Front-end construction service system, providing componentized and modularized business applications and business process display; 所述业务流程包括企业基本信息管理、行政许可管理、标准化管理、危险化学品管理、安全投入管理、重大危险源管理、作业场所管理、产品物料管理、生产工艺管理、企业人员管理与安全教育培训；The business process includes enterprise basic information management, administrative licensing management, standardized management, hazardous chemicals management, safety input management, major hazardous source management, workplace management, product material management, production process management, enterprise personnel management and safety education and training ; 业务应用层，采用Nginx中间件搭建，采用Java语言开发，包括多个业务应用管理单元，通过API接口调用应用支撑层数据，用于根据数据分析模型对数据处理结果按照业务流程统一分类监控管理；The business application layer is built with Nginx middleware and developed in Java language, including multiple business application management units, and the application support layer data is called through the API interface, which is used to monitor and manage the data processing results according to the unified classification and business process according to the data analysis model; 综合展示层，采用B/S架构浏览器，用于业务应用层数据的可视化。The comprehensive display layer adopts the B/S architecture browser for visualization of data in the business application layer. 2.根据权利要求1所述危险化学品安全生产风险监测预警系统，其特征在于，所述业务应用管理单元包括档案信息管理单元、风险态势动态研判单元、事故应急支撑单元、风险综合分析单元、风险分布单元、监测预警单元、风险动态预警单元、监督反馈单元、在线巡查单元、安全风险研判与承诺单元、企业级应用单元；2. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 1, wherein the business application management unit comprises an archive information management unit, a risk situation dynamic research and judgment unit, an accident emergency support unit, a comprehensive risk analysis unit, Risk distribution unit, monitoring and early warning unit, dynamic risk early warning unit, supervisory feedback unit, online inspection unit, security risk judgment and commitment unit, and enterprise-level application unit; 档案信息管理单元，用于企业基本信息管理、行政许可管理、标准化管理、危险化学品管理、安全投入管理、重大危险源管理、作业场所管理、产品物料管理、生产工艺管理、企业人员管理、安全教育培训管理；File information management unit, used for enterprise basic information management, administrative license management, standardized management, hazardous chemicals management, safety investment management, major hazardous source management, workplace management, product material management, production process management, enterprise personnel management, safety Education and training management; 风险态势动态研判单元，用于环境敏感点风险态势动态研判、人口密集区风险态势动态研判、重点监管行业风险态势动态研判、重点监管化工园区风险态势动态研判、恶劣气候风险态势动态研判；The dynamic research and judgment unit of risk situation is used for dynamic research and judgment of risk situation of environmentally sensitive points, dynamic research and judgment of risk situation of densely populated areas, dynamic research and judgment of risk situation of key supervision industries, dynamic research and judgment of risk situation of key supervision chemical parks, dynamic research and judgment of risk situation of severe weather; 事故应急支撑单元，用于应急资源统计、化学品知识图谱、视频监控调用；Accident emergency support unit, used for emergency resource statistics, chemical knowledge map, and video surveillance calls; 风险综合分析单元，用于企业风险预警趋势分析、高风险预警因素分析、风险预警未反馈率、重点监管危险化学品综合分析、重点监管化工工艺综合分析；The comprehensive risk analysis unit is used for enterprise risk early warning trend analysis, high risk early warning factor analysis, risk early warning non-feedback rate, comprehensive analysis of key regulated hazardous chemicals, and comprehensive analysis of key supervised chemical processes; 风险分布单元，用于危险化学品企业信息、重大危险源信息、重点监管危险化学品信息、重点监管工艺信息、重点监管区域信息的管理；Risk distribution unit, which is used for the management of hazardous chemical enterprise information, major hazard source information, key supervised hazardous chemicals information, key supervised process information, and key supervised area information; 监测预警单元，用于预警信息监控、安全隐患智能识别、视频监控、预警记录查询；Monitoring and early warning unit, used for early warning information monitoring, intelligent identification of safety hazards, video monitoring, and early warning record query; 风险动态预警单元，用于企业风险预警、重点监管危险化学品风险预警、重点监管化工工艺风险预警、人口密集区风险预警；Risk dynamic early warning unit, used for enterprise risk early warning, risk early warning of key supervision hazardous chemicals, key supervision chemical process risk early warning, and risk early warning of densely populated areas; 监督反馈单元，用于预警通报和历史信息查询；Supervision and feedback unit for early warning notification and historical information query; 在线巡查单元，用于在线监测接入数据情况巡查、可视化监管、监测预警分析与报告；Online inspection unit, used for online monitoring of access data status inspection, visual supervision, monitoring and early warning analysis and reporting; 安全风险研判与承诺单元，用于企业承诺信息填报和监管部门查看企业已承诺信息；Security risk judgment and commitment unit, which is used to fill in the company's commitment information and check the company's committed information by the regulatory department; 企业级应用单元，用于基础信息管理、企业日报表、数据监测、可视化管理、信息提醒、监管反馈、安全风险研判与承诺填报。Enterprise-level application unit, used for basic information management, enterprise daily report, data monitoring, visual management, information reminder, regulatory feedback, security risk research and judgment and commitment filling. 3.根据权利要求1所述危险化学品安全生产风险监测预警系统，其特征在于，所述数据监测分析模型为：设Tx为实时监测数据得分，Rx为所有接入的点位的风险值算术平均数，Ri为单个接入点位风险值，n为接入点位数量，则：3. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 1, wherein the data monitoring and analysis model is: let T x be the real-time monitoring data score, and R x be the risk of all access points value arithmetic mean, R i is the risk value of a single access point, n is the number of access points, then: Tx＝20×(5-Rx)；T x =20×(5-R x );
Figure RE-FDA0003030360870000031
Figure RE-FDA0003030360870000031
 4.根据权利要求1所述危险化学品安全生产风险监测预警系统，其特征在于，所述系统运行状态分析模型为：设Ty为安全监控系统运行状态值，Ry为故障率与离线率算术平均数，Rf为24小时内所有探测器故障率，Ro为24小时内所有探测器离线率，Rf，i为一个探测器24小时内故障率，Ro，i为一个探测器24 小时内离线率，24小时内有5次以上报警摄像头数/配置有视频分析摄像头数，则：4. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 1, wherein the system operating state analysis model is: let T y be the safety monitoring system operating state value, and R y be the failure rate and the offline rate Arithmetic mean, R f is the failure rate of all detectors within 24 hours, R o is the offline rate of all detectors within 24 hours, R f, i is the failure rate of one detector within 24 hours, R o, i is one detector The offline rate within 24 hours, the number of cameras with more than 5 alarms in 24 hours/the number of cameras equipped with video analysis, then: Ty＝100×(1-Ry)；T y =100×(1-R y );
Figure RE-FDA0003030360870000041
Figure RE-FDA0003030360870000041
Figure RE-FDA0003030360870000042
Figure RE-FDA0003030360870000042
Figure RE-FDA0003030360870000043
Figure RE-FDA0003030360870000043
 5.根据权利要求1所述危险化学品安全生产风险监测预警系统，其特征在于，所述视频智能分析数据模型为：设Tz为视频智能分析得分值，Rz为24小时内有5次以上报警摄像头数/配置有视频分析摄像头数，则：5. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 1, wherein the video intelligent analysis data model is: let T z be the video intelligent analysis score value, and R z be that there are 5 in 24 hours. The number of alarm cameras above the second/number of cameras configured with video analysis, then: Tz＝65+35×(1-Rz)。T z =65+35×(1−R z ). 6.根据权利要求1所述危险化学品安全生产风险监测预警系统，其特征在于，所述风险数据分析模型为：6. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 1, wherein the risk data analysis model is: 设R为企业安全生产风险指数值；Ti为企业基础信息得分值；Tx为重大危险源实时监测数据得分值；Ty为安全监控系统运行状态得分值；Tz为视频智能分析得分值；Ta为加分值；γi为企业基础信息得分值修正系数，γx为重大危险源实时监测数据得分值修正系数，γy为安全监控系统运行状态得分值修正系数，γz为视频智能分析得分值修正系数，γa为加分值修正系数；则：Let R be the enterprise safety production risk index value; T i is the enterprise basic information score value; Tx is the real-time monitoring data score value of major hazard sources; Ty is the operating status score value of the safety monitoring system; T z is the video intelligence Analysis score value; T a is the extra score value; γ i is the correction coefficient of the enterprise basic information score value, γ x is the score value correction coefficient of the real-time monitoring data of major hazard sources, and γ y is the score value of the operating status of the safety monitoring system Correction coefficient, γ z is the correction coefficient of the video intelligent analysis score value, and γ a is the correction coefficient of the bonus point value; then: R＝γi×Ti+γx×Tx+γy×Ty+γz×Tz+γa×Ta R=γ i ×T i +γ x ×T x +γ y ×T y +γ z ×T z +γ a ×T a 7.根据权利要求6所述危险化学品安全生产风险监测预警系统，其特征在于，所述企业基础信息得分值修正系数、重大危险源实时监测得分值修正系数、安全监控系统运行状态得分值修正系数、视频智能分析得分值修正系数、企业基础信息得分值修正系数、重大危险源实时监测数据得分值修正系数、安全监控系统运行状态得分值修正系数、视频智能分析得分值修正系数均为设定值。7. The risk monitoring and early warning system for safe production of hazardous chemicals according to claim 6, characterized in that, the correction coefficient of the score value of the basic information of the enterprise, the correction coefficient of the score value of the real-time monitoring of major hazard sources, and the operating state of the safety monitoring system are obtained. Score correction coefficient, video intelligent analysis score value correction coefficient, enterprise basic information score value correction coefficient, major hazard real-time monitoring data score value correction coefficient, safety monitoring system operating status score value correction coefficient, video intelligent analysis The score correction coefficients are all set values. 8.危险化学品安全生产风险监测预警方法，其特征在于，包括如下步骤：8. A method for monitoring and early-warning the risk of hazardous chemical production safety, characterized in that it comprises the following steps: 步骤一：监控信息抽取汇总：对部署在前端的物联网安全数据包括通过采集网关采集的视频监控图像、违规行为视频分析数据、物联网监测数据进行抽取汇总；Step 1: Extraction and summary of monitoring information: extract and summarize the security data of the Internet of Things deployed at the front end, including video surveillance images collected through the collection gateway, video analysis data of violations, and Internet of Things monitoring data; 步骤二：监控信息采集传输：利用汇聚在政务云平台的运营商专线，传输步骤一中采集到的物联网数据；Step 2: Monitoring information collection and transmission: use the operator's dedicated line converged on the government affairs cloud platform to transmit the IoT data collected in step 1; 步骤三：分析预警：利用应用支撑层提供的数据分析模型，包括数据监测分析模型、系统运行状态分析模型、风险数据分析模型与视频流媒体数据分析模型生成视频智能分析结果、设备运行状态分析结果、报警信息，并通过应用支撑层将生成的预警结果推送至监管接收端；Step 3: Analysis and early warning: Use the data analysis models provided by the application support layer, including data monitoring analysis models, system operating status analysis models, risk data analysis models and video streaming media data analysis models to generate video intelligent analysis results and equipment operating status analysis results , alarm information, and push the generated early warning results to the supervision receiving end through the application support layer; 步骤四：违规/异常报警处理：系统通过应用支撑提供的统一消息服务将预警信息推送至监管接收端，监管接收端接收到信息后，进行现场核查处置，并通过系统将处置情况进行上传，系统根据监管接收端上传的信息自动反馈至监管接收端。Step 4: Violation/abnormal alarm processing: The system pushes the warning information to the supervision receiving end through the unified message service provided by the application support. After the supervision receiving end receives the information, it conducts on-site verification and disposal, and uploads the disposal situation through the system. According to the information uploaded by the supervision receiver, it is automatically fed back to the supervision receiver.
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CN114819291A (en) * 2022-04-06 2022-07-29 江苏易政达信息科技有限公司 Urban hazardous waste monitoring and management system and emission prediction method
CN114778768A (en) * 2022-04-08 2022-07-22 深圳市欣横纵技术股份有限公司 Visual remote real-time monitoring and intelligent analysis system and method
CN114678117B (en) * 2022-05-26 2022-08-02 成都与睿创新科技有限公司 Management method and device for standardizing operating behaviors of operating room personnel
CN114678117A (en) * 2022-05-26 2022-06-28 成都与睿创新科技有限公司 Management method and device for standardizing operating behaviors of operating room personnel
CN115239179A (en) * 2022-08-05 2022-10-25 卡奥斯化智物联科技(青岛)有限公司 Chemical production operation flow system
WO2024027200A1 (en) * 2022-08-05 2024-02-08 卡奥斯化智物联科技(青岛)有限公司 Chemical production operation process system
CN115348296A (en) * 2022-09-05 2022-11-15 绍兴安瑞思网络科技有限公司 Chemical production operation management system and management method based on Internet of things
CN115424212A (en) * 2022-10-11 2022-12-02 国网河北省电力有限公司 Electric power operation field violation identification system and application thereof
CN115604013A (en) * 2022-10-21 2023-01-13 北京珞安科技有限责任公司（Cn） Industrial data interaction platform and interaction method
CN117061711A (en) * 2023-10-11 2023-11-14 深圳市爱为物联科技有限公司 Video monitoring safety management method and system based on Internet of things
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Application publication date: 20210615