WO2023040575A1 - Internet-of-things-based abnormality early warning analysis system and method for special operation site - Google Patents

Internet-of-things-based abnormality early warning analysis system and method for special operation site Download PDF

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WO2023040575A1
WO2023040575A1 PCT/CN2022/113444 CN2022113444W WO2023040575A1 WO 2023040575 A1 WO2023040575 A1 WO 2023040575A1 CN 2022113444 W CN2022113444 W CN 2022113444W WO 2023040575 A1 WO2023040575 A1 WO 2023040575A1
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alarm
analysis
site
database
monitoring data
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Chinese (zh)
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王晶
张正全
李松松
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中通服和信科技有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display
    • G01N33/0063—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display using a threshold to release an alarm or displaying means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/7867—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G06Q50/265—Personal security, identity or safety

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  • the invention belongs to the technical field of early warning of abnormalities in special operation sites, and specifically relates to an analysis system and method for early warning of abnormalities in special operation sites based on the Internet of Things.
  • some special operation monitoring is mainly to analyze the environment before the operation, and some other monitoring of the entire operation process is mainly for the monitoring of the weather, rather than the continuous monitoring of the entire operation process, focusing on the video monitoring of the operation process, There is a lack of monitoring data collection and analysis of the operation process, and the applicable conditions are limited, so it is impossible to give timely alarms for sudden abnormal situations.
  • the main method at present is to control the operation process through information technology. This method relies too much on certain operation process steps, and does not effectively monitor factors such as operation status.
  • the main means of monitoring and early warning of abnormal conditions are mainly to collect and analyze meteorological data during operation through intelligent sensing equipment, and to manage personnel on-the-job through positioning technology. This method does not connect with the company's own system. The occurrence of accidents cannot achieve more convenient human-computer interaction, which reduces the efficiency of handling emergency events.
  • the present invention provides a system and method for early warning and analysis of abnormalities in special job sites based on the Internet of Things.
  • An abnormal early warning and analysis system for special operation sites based on the Internet of Things, including monitoring data acquisition module, monitoring data intelligent analysis module, abnormal situation alarm information research and judgment module, on-site abnormal situation disposal feedback module and special operation database;
  • the monitoring data collection module is used to collect abnormal situation monitoring data, and send the collected on-site monitoring data to the monitoring data intelligent analysis module; the monitoring data intelligent analysis module performs unified data processing on the collected on-site monitoring data, and send the processed data to a special job database;
  • the abnormal situation alarm information research and judgment module can intelligently analyze and judge the alarm by associating with the risk identification, job analysis, safety measures and on-site operation steps in the job ticket according to the preset different alarm types, alarm information templates and alarm level rules The highest level is to interrupt the operation or stop the operation; according to different situations, carry out research and judgment and push alarm information;
  • the on-site abnormal situation disposal feedback module fills in the on-site abnormal disposal situation according to the content of the alarm research and judgment, and correlates the filled-in content with the content of the job ticket, and automatically judges whether to resume the operation. And if the work ticket is within the validity period, the work will be resumed, and the on-site monitoring and control of special operations will be restarted;
  • the monitoring data acquisition module includes an operating environment gas analysis and monitoring unit, an equipment operation status monitoring unit, a special operation status monitoring unit, and a video intelligent analysis and monitoring unit;
  • Job analysis environment gas monitoring unit associate the job ticket with the gas detection equipment, obtain the configuration parameters of the gas detection equipment, and obtain the monitoring data of the gas detection equipment according to the configuration parameters;
  • Equipment operation status monitoring unit divide the on-site operation area according to the factory floor plan, connect with the existing automation control system, obtain the configuration parameters of the automation control system, and obtain the equipment operation data in the special operation site area according to the configuration parameters;
  • Special operation status monitoring unit according to the completion time of special operation application approval, automatically synchronize the special operation start time, dynamically calculate the duration of on-site operations, and perform real-time calibration for abnormal situations, and generate corresponding operation reports and send them to corresponding management personnel ;
  • Video intelligent analysis and monitoring unit obtain the surveillance video of the special operation site, establish a video analysis model, and analyze the surveillance video of the special operation site through the video analysis model.
  • the working methods of the monitoring data intelligent analysis module include:
  • the abnormal alarm information database includes: an operation analysis environment gas alarm database, an equipment operation status alarm database, a special operation status monitoring alarm database, and a video intelligent analysis alarm database.
  • the job analysis ambient gas alarm database according to the data collected by the job analysis ambient gas monitoring unit, compare different gas types with the job analysis gas monitoring data threshold database and the on-site job analysis effective time database, and judge the threshold based on the time stamp For the effective time, for abnormal gases exceeding the predetermined threshold range, corresponding alarm data is generated and stored in the special operation analysis environment gas alarm database.
  • the equipment operation status alarm database The equipment operation status data collected by the equipment operation status monitoring unit is matched and compared with the equipment monitoring data threshold database in real time. According to the comparison results, corresponding alarm data is generated for abnormal data and stored in the Equipment operation status alarm database.
  • the special operation state monitoring and alarm database dynamically obtain the real-time duration of on-site operations, compare the obtained duration with the valid time database of different types of on-site operation tickets, and generate corresponding alarm data storage for data with abnormal comparison results. into the special job status monitoring alarm database.
  • An abnormal early warning analysis method for a special job site based on the Internet of Things includes:
  • Step 1 Collect abnormal situation monitoring data
  • Step 2 Perform unified data processing on the collected on-site operation monitoring data and collect them into the special operation database;
  • Step 3 The level of intelligent judgment and alarm is to interrupt the operation or stop the operation, and carry out research and judgment and push the alarm information according to different situations;
  • Step 4 According to the content of the alarm research and judgment, fill in the report of the abnormal handling situation on the site, associate the filled content with the content of the job ticket, and automatically judge whether to resume the operation.
  • the beneficial effects of the present invention are: a system method based on the Internet of Things technology for abnormal situation monitoring and early warning analysis of special job sites is proposed, focusing on the monitoring of abnormal situations in the whole stage from the beginning of the operation to the end of the operation, and comprehensively considering the special operation Accurate and continuous intelligent analysis of the on-site environment; focus on monitoring the unsafe behavior of personnel during operations, the effectiveness of job analysis, and the validity of job tickets, so as to make job risk monitoring, early warning, and prevention and control more comprehensive; Combined with the analysis of environmental factors and human unsafe behavior factors, the plan is more targeted, an accurate alarm information plan is formed, and the alarm processing process is optimized; in abnormal cases, a flexible alarm disposal plan is formed and human resources are optimized through comprehensive data analysis.
  • the process of machine-computer interaction greatly improves the efficiency of handling abnormal situations, and lays the foundation for fundamentally standardizing enterprise safety operations, reducing operation safety risks, and improving the safety level of special operations in an all-round way.
  • Fig. 1 is a schematic block diagram of the present invention.
  • Special operations are defined as: operations involving fire, entering confined spaces, blind panel extraction, high-altitude operations, hoisting, temporary power consumption, ground breaking, and circuit breaks involved in chemical production units, which may cause production safety accidents.
  • the embodiment of the present invention is described by taking hot work as an example.
  • the present invention includes but is not limited to hot work, and is applicable to other types of special work.
  • the abnormal early warning and analysis system for special operations based on the Internet of Things includes a monitoring data collection module, a monitoring data intelligent analysis module, an abnormal situation alarm information research and judgment module, a field abnormal situation disposal feedback module, and a special operation database;
  • the monitoring data acquisition module is used to collect abnormal monitoring data, mainly through internal and external systems.
  • the internal and external systems include portable or handheld gas detection equipment background systems, video intelligent analysis systems, SIS, DCS, PLC Such as automatic control system and special operation approval system, other systems that can achieve the same function are also available, because some systems may have the same function but different names, and send the collected on-site monitoring data to the monitoring data intelligent analysis module; including the operating environment Gas analysis and monitoring unit, equipment operation status monitoring unit, special operation status monitoring unit and video intelligent analysis and monitoring unit; internal and external systems are data sources;
  • Gas detection equipment includes portable or hand-held gas detection equipment. Through WI-FI, 4G, 5G and other data transmission methods, gas The configuration parameters of the detection equipment are used to obtain the monitoring data of the gas detection equipment according to the configuration parameters.
  • the way to obtain the monitoring data is to obtain the monitoring data in a regular or real-time manner; at the same time, it supports portable or handheld gas detection through Bluetooth, LAN, etc. Point-to-point high-speed data transmission between equipment and mobile terminals for special operations, accurate acquisition of job analysis gas monitoring data, and automatic generation of job tickets for ambient gas monitoring process data;
  • Equipment operation status monitoring unit obtain the factory floor plan, divide the on-site operation area according to the factory floor plan, and connect with the existing automation control system.
  • the specific method is to connect with SIS, DCS, PLC and other automation control systems through the special operation background system.
  • Obtain the configuration parameters of the automation control system and obtain the operation data of the equipment in the special operation site area according to the configuration parameters;
  • the method of obtaining the operation data of the equipment is to obtain the operation data of the equipment in a regular or real-time manner; to achieve dynamic monitoring of the equipment on the operation site, Fully guarantee the safety of the device in the whole process of operation;
  • Special operation status monitoring unit obtain the completion time of special operation application approval, automatically synchronize the special operation start time according to the completion time of special operation application approval, use the completion time of application approval as the special operation start time, and dynamically calculate the duration of on-site operations , and perform real-time calibration for abnormal situations, including special operation interruption, stop, etc., and generate corresponding job reports to send to corresponding management personnel.
  • Job reports can be set according to the needs of different system users, mainly for Make relevant personnel understand the real-time progress of the operation process;
  • Video intelligent analysis and monitoring unit obtain the monitoring video of the special operation site, and establish a video analysis model.
  • the video analysis model is a neural network model, which uses the on-site monitoring video as input data, and the violations and unsafe factors in the on-site area as output data for training. Yes, the specific establishment process will not be described in detail, because the establishment of the neural network model is a conventional technology, and those skilled in the art can understand that the monitoring video of a special job site can be analyzed through the video analysis model; artificial intelligence can also be used to drive , capture videos and images of violations and unsafe factors in special operation site areas in real time, and upload them to the server for in-depth behavior and status analysis;
  • the monitoring data intelligent analysis module is used to perform unified data processing on the collected on-site monitoring data, and send it to the special operation database;
  • the analysis library is set up according to the safety specifications and usage requirements of special operations, and combines the received on-site monitoring data with the operation analysis gas monitoring data threshold library, equipment monitoring data threshold library, on-site job ticket valid time database and video intelligent analysis library For comparison, an abnormal alarm information database is automatically generated according to different alarm types.
  • Abnormal alarm information database includes:
  • Operation analysis environmental gas alarm database According to the data collected by the operation analysis environmental gas monitoring unit, compare different gas types with the operation analysis gas monitoring data threshold database and the on-site operation analysis effective time database, and judge the effective time of the threshold according to the time stamp. For abnormal gases that exceed the predetermined threshold range, generate corresponding alarm data and store them in the special operation analysis environment gas alarm database;
  • Equipment operation status alarm database The equipment operation status data collected by the equipment operation status monitoring unit is matched and compared with the equipment monitoring data threshold database in real time. According to the comparison results, abnormal data is generated and corresponding alarm data is stored in the equipment operation status Alarm database;
  • Special operation status monitoring and alarm database Dynamically obtain the real-time duration of on-site operations (smart correction for abnormal situations such as suspension and suspension), compare the obtained duration with the valid time database of different types of on-site operation tickets, and compare the results of the comparison Abnormal data generates corresponding alarm data and stores them in the special operation status monitoring alarm database;
  • Video intelligent analysis alarm database According to the video and image of the on-site operation area, AI analysis is carried out through scene algorithms such as personnel unsafe behavior and environmental unsafe factors in the video intelligent analysis service, real-time comparison, and the comparison result is abnormal behavior
  • the scene is stored in the video intelligent analysis alarm database;
  • the unsafe behavior of personnel includes personnel not wearing safety helmets, illegal entry of off-site operators, illegal smoking, etc.
  • the environmental unsafe factors are mainly due to the failure to implement relevant safety measures during the operation process, including Illegal discharge of gas in a certain section of the operating point, voids/inspection wells/drains, etc. are not covered; the analysis data of the video intelligent analysis monitoring unit is stored in the video intelligent analysis alarm database.
  • the abnormal situation alarm information research and judgment module can intelligently analyze and judge the alarm by associating with the risk identification, job analysis, safety measures and on-site operation steps in the job ticket according to the preset different alarm types, alarm information templates and alarm level rules The highest level is to interrupt the operation or stop the operation; conduct research and judgment and push alarm information according to different situations.
  • Case 1 The equipment monitoring data threshold database is combined with the operation analysis gas monitoring threshold database and the on-site operation ticket valid time database. If the gas environment does not meet the operation requirements or the on-site operation ticket is not within the valid time, the operation will be stopped, an alarm message will be generated, and the alarm information will be pushed; If the operation requirements are met, the operation will be interrupted, and an alarm message will be generated and pushed.
  • Case 2 The video intelligent analysis database is combined with the operation analysis gas monitoring threshold database and the on-site operation ticket valid time database. If the gas environment does not meet the operation requirements or the on-site operation ticket is not within the valid time, the operation will be stopped, an alarm message will be generated, and the alarm information will be pushed; If the job requires, the job will be interrupted, an alarm message will be generated and the alarm message will be pushed.
  • Case 3 The job analysis gas monitoring threshold database is combined with the valid time database of the on-site operation ticket. If the on-site operation ticket is not within the valid time, the operation will be stopped to generate alarm information and the alarm information will be pushed; if the on-site operation ticket is within the valid time but the gas environment is not If the job requirements are met, the job will be interrupted to generate an alarm message, and the alarm message will be pushed.
  • Situation 4 The equipment monitoring data threshold database is combined with the on-site job ticket limited time database. If the on-site job ticket is not within the valid time, the operation will be stopped to generate alarm information and the alarm information will be pushed; if the on-site job ticket is within the valid time but the equipment location, If the status does not meet the job requirements, the job will be interrupted, an alarm message will be generated, and the alarm message will be pushed.
  • Situation 5 The video intelligent analysis library is combined with the on-site job ticket limited time database. If the on-site job ticket is not within the valid time, the operation will be stopped to generate an alarm message, and the alarm message will be pushed; if the on-site job ticket is within the valid time, but the video intelligent analysis If the result does not meet the job requirements, the job will be interrupted, an alarm message will be generated, and the alarm message will be pushed.
  • This patent takes the above five situations as examples, including but not limited to the above five situations.
  • the intelligent combination of databases can improve the efficiency of handling abnormal situations in a targeted manner.
  • the system automatically generates alarm information based on the content of the alarm information research and judgment, mainly including work location, alarm type, alarm content, alarm level, alarm information push and disposal personnel, etc.;
  • the alarm information is sent to different personnel, mainly including special operation monitoring personnel, operating personnel, operation leaders, safety management personnel, and enterprise leaders, etc.
  • the on-site abnormal situation handling feedback module is based on the content of the alarm research and judgment, and relevant personnel fill in the on-site abnormal handling situation through the on-site operation mobile terminal, and support voice, picture, text and other forms of content input; according to the filled-in content and job ticket content
  • the content of the job ticket includes job analysis, implementation of risk control measures, and valid time of the job, etc., and automatically judges whether to resume the job. , re-start special operation site monitoring and control;
  • the analysis method of the abnormal early warning analysis system for special job sites based on the Internet of Things include:
  • Step 1 Collect abnormal situation monitoring data
  • Step 2 Perform unified data processing on the collected on-site operation monitoring data and collect them into the special operation database;
  • Step 3 The level of intelligent judgment and alarm is to interrupt the operation or stop the operation; conduct research and judgment and push the alarm information according to different situations;
  • Step 4 According to the content of the alarm research and judgment, fill in the report of the abnormal handling situation on the site, associate the filled content with the content of the job ticket, and automatically judge whether to resume the operation.
  • the disclosed devices, devices and methods can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the modules is only a logical function division, and there may be other division methods during actual implementation;
  • the modules described as separate components can be It may or may not be physically separated, and components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the method in this embodiment.

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Abstract

The present invention belongs to the technical field of abnormality early warning for special operation sites. Disclosed are an Internet-of-Things-based abnormality early warning analysis system and method for a special operation site. The system comprises a monitoring data collection module, an intelligent monitoring data analysis module, an abnormal situation alarm information research and determination module, a site abnormal situation handling feedback module and a special operation database, wherein the monitoring data collection module is used for collecting abnormal situation monitoring data, and sending collected site monitoring data to the intelligent monitoring data analysis module; the intelligent monitoring data analysis module performs unified data processing on the collected site monitoring data, and sends the processed data to the special operation database; and on the basis of the content of an alarm information database, the abnormal situation alarm information research and determination module associates, in an operation sheet, risk identification, operation analysis, safety measures and site operation steps according to different preset alarm types, an alarm information template and an alarm level rule.

Description

基于物联网的特殊作业现场异常预警分析***及方法An abnormal early warning analysis system and method for a special operation site based on the Internet of Things 技术领域technical field
本发明属于特殊作业现场异常预警技术领域，具体是基于物联网的特殊作业现场异常预警分析***及方法。The invention belongs to the technical field of early warning of abnormalities in special operation sites, and specifically relates to an analysis system and method for early warning of abnormalities in special operation sites based on the Internet of Things.
背景技术Background technique
目前一些特殊作业监测主要是对作业前的环境进行分析，另外一些对整个作业过程的监测主要是针对气象的监测，而不是对整个作业进行全过程持续性监测，侧重在作业过程的视频监控，缺乏对作业过程的监测数据采集和分析，适用条件受限，无法对突发异常情况进行及时报警。对作业过程的监测和管理，目前主要的方法是通过信息化技术，对作业流程进行把控，这种方法过于依赖某种作业流程步骤，没有对作业状态等因素进行有效监测。对异常情况监测预警主要的手段主要有通过智能感知设备对作业时的气象数据进行采集分析，通过定位技术对人员在岗在位进行管理，此方法没有与企业自有的***进行对接，对于突发事故的发生不能实现更为便捷的人机交互，降低了应急事件的处置效率。At present, some special operation monitoring is mainly to analyze the environment before the operation, and some other monitoring of the entire operation process is mainly for the monitoring of the weather, rather than the continuous monitoring of the entire operation process, focusing on the video monitoring of the operation process, There is a lack of monitoring data collection and analysis of the operation process, and the applicable conditions are limited, so it is impossible to give timely alarms for sudden abnormal situations. For the monitoring and management of the operation process, the main method at present is to control the operation process through information technology. This method relies too much on certain operation process steps, and does not effectively monitor factors such as operation status. The main means of monitoring and early warning of abnormal conditions are mainly to collect and analyze meteorological data during operation through intelligent sensing equipment, and to manage personnel on-the-job through positioning technology. This method does not connect with the company's own system. The occurrence of accidents cannot achieve more convenient human-computer interaction, which reduces the efficiency of handling emergency events.
发明内容Contents of the invention
为了解决上述方案存在的问题，本发明提供了基于物联网的特殊作业现场异常预警分析***及方法。In order to solve the problems in the above solutions, the present invention provides a system and method for early warning and analysis of abnormalities in special job sites based on the Internet of Things.
本发明的目的可以通过以下技术方案实现：The purpose of the present invention can be achieved through the following technical solutions:
基于物联网的特殊作业现场异常预警分析***，包括监测数据采集模块、监测数据智能分析模块、异常情况报警信息研判模块、现场异常情况处置反馈模块和特殊作业数据库；An abnormal early warning and analysis system for special operation sites based on the Internet of Things, including monitoring data acquisition module, monitoring data intelligent analysis module, abnormal situation alarm information research and judgment module, on-site abnormal situation disposal feedback module and special operation database;
所述监测数据采集模块用于对异常情况监测数据进行采集，并将采集的现场监测数据发送到监测数据智能分析模块；所述监测数据智能分析模 块对采集的现场监测数据进行统一的数据处理，并将处理后的数据发送到特殊作业数据库；The monitoring data collection module is used to collect abnormal situation monitoring data, and send the collected on-site monitoring data to the monitoring data intelligent analysis module; the monitoring data intelligent analysis module performs unified data processing on the collected on-site monitoring data, and send the processed data to a special job database;
结合报警信息数据库的内容，异常情况报警信息研判模块根据预设的不同报警类型、报警信息模板和报警等级规则，关联作业票中的风险辨识、作业分析、安全措施和现场操作步骤，智能研判报警的等级是中断作业或者停止作业；根据不同情况进行研判和报警信息推送；Combined with the content of the alarm information database, the abnormal situation alarm information research and judgment module can intelligently analyze and judge the alarm by associating with the risk identification, job analysis, safety measures and on-site operation steps in the job ticket according to the preset different alarm types, alarm information templates and alarm level rules The highest level is to interrupt the operation or stop the operation; according to different situations, carry out research and judgment and push alarm information;
现场异常情况处置反馈模块根据报警研判的内容，对现场异常处置情况进行填报，根据填报的内容与作业票内容进行关联，自动判断是否恢复作业，当作业分析气体监测不超标、作业分析在有效时间且作业票在有效期内，则恢复作业，重新开始特殊作业现场监测和管控；The on-site abnormal situation disposal feedback module fills in the on-site abnormal disposal situation according to the content of the alarm research and judgment, and correlates the filled-in content with the content of the job ticket, and automatically judges whether to resume the operation. And if the work ticket is within the validity period, the work will be resumed, and the on-site monitoring and control of special operations will be restarted;
当整改时间超过作业票有效时间或者作业分析气体仍然超标，则重新申请作业。When the rectification time exceeds the valid time of the job ticket or the job analysis gas still exceeds the standard, re-apply for the job.
进一步地，监测数据采集模块包括作业环境气体分析监测单元、设备运行状态监测单元、特殊作业状态监测单元和视频智能分析监测单元；Further, the monitoring data acquisition module includes an operating environment gas analysis and monitoring unit, an equipment operation status monitoring unit, a special operation status monitoring unit, and a video intelligent analysis and monitoring unit;
作业分析环境气体监测单元：将作业票与气体检测设备进行关联，获取气体检测设备的配置参数，根据配置参数获取气体检测设备的监测数据；Job analysis environment gas monitoring unit: associate the job ticket with the gas detection equipment, obtain the configuration parameters of the gas detection equipment, and obtain the monitoring data of the gas detection equipment according to the configuration parameters;
设备运行状态监测单元：根据厂区平面图划分现场作业区域，与现有的自动化控制***进行对接，获取自动化控制***的配置参数，根据配置参数获取特殊作业现场区域内设备运行数据；Equipment operation status monitoring unit: divide the on-site operation area according to the factory floor plan, connect with the existing automation control system, obtain the configuration parameters of the automation control system, and obtain the equipment operation data in the special operation site area according to the configuration parameters;
特殊作业状态监测单元：根据特殊作业申请审批的完成时间，自动同步特殊作业开始时间，动态计算现场作业的持续时间，并针对异常情况进行实时校准，并生成相应的作业报告发送至对应的管理人员；Special operation status monitoring unit: according to the completion time of special operation application approval, automatically synchronize the special operation start time, dynamically calculate the duration of on-site operations, and perform real-time calibration for abnormal situations, and generate corresponding operation reports and send them to corresponding management personnel ;
视频智能分析监测单元：获取特殊作业现场的监控视频，建立视频分析模型，通过视频分析模型对特殊作业现场的监控视频进行分析。Video intelligent analysis and monitoring unit: obtain the surveillance video of the special operation site, establish a video analysis model, and analyze the surveillance video of the special operation site through the video analysis model.
进一步地，监测数据智能分析模块的工作方法包括：Further, the working methods of the monitoring data intelligent analysis module include:
设置作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库，将接收到的现场监测数据与作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库进行比对，根据不同的报警类型自动生成异常报警信息数据库。Set up the operation analysis gas monitoring data threshold library, equipment monitoring data threshold The job ticket effective time database is compared with the video intelligent analysis database, and the abnormal alarm information database is automatically generated according to different alarm types.
进一步地，异常报警信息数据库包括：作业分析环境气体报警数据库、设备运行状态报警数据库、特殊作业状态监控报警数据库和视频智能分析报警数据库。Further, the abnormal alarm information database includes: an operation analysis environment gas alarm database, an equipment operation status alarm database, a special operation status monitoring alarm database, and a video intelligent analysis alarm database.
进一步地，作业分析环境气体报警数据库：根据作业分析环境气体监测单元采集到的数据，按不同气体类型与作业分析气体监测数据阈值库和现场作业分析有效时间数据库进行比对，依据时间戳判断阈值有效时间，针对超出既定阈值范围的异常气体，生成相应的报警数据存入特殊作业分析环境气体报警数据库。Further, the job analysis ambient gas alarm database: according to the data collected by the job analysis ambient gas monitoring unit, compare different gas types with the job analysis gas monitoring data threshold database and the on-site job analysis effective time database, and judge the threshold based on the time stamp For the effective time, for abnormal gases exceeding the predetermined threshold range, corresponding alarm data is generated and stored in the special operation analysis environment gas alarm database.
进一步地，设备运行状态报警数据库：将设备运行状态监测单元采集到的设备运行状态数据与设备监测数据阈值库进行实时匹配比对，针对比对结果，将异常的数据生成相应的报警数据存入设备运行状态报警数据库。Further, the equipment operation status alarm database: The equipment operation status data collected by the equipment operation status monitoring unit is matched and compared with the equipment monitoring data threshold database in real time. According to the comparison results, corresponding alarm data is generated for abnormal data and stored in the Equipment operation status alarm database.
进一步地，特殊作业状态监控报警数据库：动态获取现场作业实时持续时间，将获取的持续时间与不同现场作业类型作业票有效时间数据库进行比对，针对比对结果异常的数据生成相应的报警数据存入特殊作业状态监控报警数据库。Further, the special operation state monitoring and alarm database: dynamically obtain the real-time duration of on-site operations, compare the obtained duration with the valid time database of different types of on-site operation tickets, and generate corresponding alarm data storage for data with abnormal comparison results. into the special job status monitoring alarm database.
基于物联网的特殊作业现场异常预警分析方法，具体方法包括：An abnormal early warning analysis method for a special job site based on the Internet of Things. The specific methods include:
步骤一：对异常情况监测数据进行采集；Step 1: Collect abnormal situation monitoring data;
步骤二：对采集的现场作业监测数据进行统一的数据处理，汇集到特殊作业数据库；Step 2: Perform unified data processing on the collected on-site operation monitoring data and collect them into the special operation database;
步骤三：智能研判报警的等级是中断作业或者停止作业，根据不同情 况进行研判和报警信息推送；Step 3: The level of intelligent judgment and alarm is to interrupt the operation or stop the operation, and carry out research and judgment and push the alarm information according to different situations;
步骤四：根据报警研判的内容，对现场异常处置情况进行填报，根据填报的内容与作业票内容进行关联，自动判断是否恢复作业。Step 4: According to the content of the alarm research and judgment, fill in the report of the abnormal handling situation on the site, associate the filled content with the content of the job ticket, and automatically judge whether to resume the operation.
与现有技术相比，本发明的有益效果是：提出基于物联网技术的特殊作业现场异常情况监测预警分析***方法，聚焦于作业开始到作业结束整个阶段的异常情况监测，全面地考虑特殊作业的作业环境，对现场环境进行精确持续的智能分析；重点监测作业中人员的不安全行为、作业分析的有效性、作业票的有效性，使作业风险监测、预警、防控更全面；对异常情况结合环境因素和人的不安全行为因素分析，使方案更具针对性，形成精准的报警信息方案，优化报警处理过程；异常情况下通过全面的数据分析，形成灵活的报警处置方案并优化人机交互过程，大大提升异常情况处理效率，为从根本上规范企业安全作业，降低作业安全风险、全方位提升特殊作业安全水平奠定基础。Compared with the prior art, the beneficial effects of the present invention are: a system method based on the Internet of Things technology for abnormal situation monitoring and early warning analysis of special job sites is proposed, focusing on the monitoring of abnormal situations in the whole stage from the beginning of the operation to the end of the operation, and comprehensively considering the special operation Accurate and continuous intelligent analysis of the on-site environment; focus on monitoring the unsafe behavior of personnel during operations, the effectiveness of job analysis, and the validity of job tickets, so as to make job risk monitoring, early warning, and prevention and control more comprehensive; Combined with the analysis of environmental factors and human unsafe behavior factors, the plan is more targeted, an accurate alarm information plan is formed, and the alarm processing process is optimized; in abnormal cases, a flexible alarm disposal plan is formed and human resources are optimized through comprehensive data analysis. The process of machine-computer interaction greatly improves the efficiency of handling abnormal situations, and lays the foundation for fundamentally standardizing enterprise safety operations, reducing operation safety risks, and improving the safety level of special operations in an all-round way.
附图说明Description of drawings
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单的介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.
图1为本发明原理框图。Fig. 1 is a schematic block diagram of the present invention.
具体实施方式Detailed ways
下面将结合实施例对本发明的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
特殊作业的定义为：化学品生产单位涉及的动火、进入受限空间、盲板抽堵、高处作业、吊装、临时用电、动土和断路等作业活动，可能引发生产安全事故的作业。本发明实施例以动火作业为例进行阐述说明，本发明包括但不局限于动火作业，并适用于其他类型的特殊作业。Special operations are defined as: operations involving fire, entering confined spaces, blind panel extraction, high-altitude operations, hoisting, temporary power consumption, ground breaking, and circuit breaks involved in chemical production units, which may cause production safety accidents. The embodiment of the present invention is described by taking hot work as an example. The present invention includes but is not limited to hot work, and is applicable to other types of special work.
如图1所示，基于物联网的特殊作业现场异常预警分析***，包括监测数据采集模块、监测数据智能分析模块、异常情况报警信息研判模块、现场异常情况处置反馈模块和特殊作业数据库；As shown in Figure 1, the abnormal early warning and analysis system for special operations based on the Internet of Things includes a monitoring data collection module, a monitoring data intelligent analysis module, an abnormal situation alarm information research and judgment module, a field abnormal situation disposal feedback module, and a special operation database;
所述监测数据采集模块用于对异常情况监测数据进行采集，主要是通过内外部***进行采集的，内外部***包括便携式或手持式气体检测设备后台***、视频智能分析***、SIS、DCS、PLC等自控***和特殊作业审批***，能够实现同功能的其他***也可以，因为有的***可能功能相同，名称并不相同，并将采集的现场监测数据发送到监测数据智能分析模块；包括作业环境气体分析监测单元、设备运行状态监测单元、特殊作业状态监测单元和视频智能分析监测单元；内外部***也就是数据源；The monitoring data acquisition module is used to collect abnormal monitoring data, mainly through internal and external systems. The internal and external systems include portable or handheld gas detection equipment background systems, video intelligent analysis systems, SIS, DCS, PLC Such as automatic control system and special operation approval system, other systems that can achieve the same function are also available, because some systems may have the same function but different names, and send the collected on-site monitoring data to the monitoring data intelligent analysis module; including the operating environment Gas analysis and monitoring unit, equipment operation status monitoring unit, special operation status monitoring unit and video intelligent analysis and monitoring unit; internal and external systems are data sources;
作业分析环境气体监测单元：特殊作业后台***将作业票与气体检测设备进行关联，气体检测设备包括便携式或者手持式气体检测设备，通过WI-FI、4G、5G等多种数据传输方式，获取气体检测设备的配置参数，根据配置参数获取气体检测设备的监测数据，获取监测数据的方式为采取定时或者实时的方式进行监测数据的获取；同时支持通过蓝牙、局域网等方式实现便携式或者手持式气体检测设备与特殊作业移动端进行点对点数据高速传输，精准获取作业分析气体监测数据，自动生成作业票环境气体监测流程数据；Job Analysis Environmental Gas Monitoring Unit: The special job background system associates job tickets with gas detection equipment. Gas detection equipment includes portable or hand-held gas detection equipment. Through WI-FI, 4G, 5G and other data transmission methods, gas The configuration parameters of the detection equipment are used to obtain the monitoring data of the gas detection equipment according to the configuration parameters. The way to obtain the monitoring data is to obtain the monitoring data in a regular or real-time manner; at the same time, it supports portable or handheld gas detection through Bluetooth, LAN, etc. Point-to-point high-speed data transmission between equipment and mobile terminals for special operations, accurate acquisition of job analysis gas monitoring data, and automatic generation of job tickets for ambient gas monitoring process data;
设备运行状态监测单元：获取厂区平面图，根据厂区平面图划分现场作业区域，与现有的自动化控制***进行对接，具体方法是通过特殊作业后台***与SIS、DCS、PLC等自动化控制***进行对接的，获取自动化 控制***的配置参数，根据配置参数获取特殊作业现场区域内设备运行数据；获取设备运行数据的方式为采取定时或者实时的方式进行设备运行数据的获取；做到作业现场装置的动态监控，全方位保障作业全过程中的装置安全；Equipment operation status monitoring unit: obtain the factory floor plan, divide the on-site operation area according to the factory floor plan, and connect with the existing automation control system. The specific method is to connect with SIS, DCS, PLC and other automation control systems through the special operation background system. Obtain the configuration parameters of the automation control system, and obtain the operation data of the equipment in the special operation site area according to the configuration parameters; the method of obtaining the operation data of the equipment is to obtain the operation data of the equipment in a regular or real-time manner; to achieve dynamic monitoring of the equipment on the operation site, Fully guarantee the safety of the device in the whole process of operation;
特殊作业状态监测单元：获取特殊作业申请审批的完成时间，根据特殊作业申请审批的完成时间，自动同步特殊作业开始时间，以申请审批的完成时间为特殊作业开始时间，动态计算现场作业的持续时间，并针对异常情况进行实时校准，异常情况包括特殊作业中断、停止等情况，并生成相应的作业报告发送至对应的管理人员，作业报告可以根据不同的***使用用户的需求进行设置，主要是为了使相关人员了解作业过程的实时进展；Special operation status monitoring unit: obtain the completion time of special operation application approval, automatically synchronize the special operation start time according to the completion time of special operation application approval, use the completion time of application approval as the special operation start time, and dynamically calculate the duration of on-site operations , and perform real-time calibration for abnormal situations, including special operation interruption, stop, etc., and generate corresponding job reports to send to corresponding management personnel. Job reports can be set according to the needs of different system users, mainly for Make relevant personnel understand the real-time progress of the operation process;
视频智能分析监测单元：获取特殊作业现场的监控视频，建立视频分析模型，视频分析模型即为神经网络模型，是以现场监控视频为输入数据，现场区域的违规、不安全因素为输出数据进行训练的，具体的建立过程不进行详细叙述了，因为神经网络模型的建立是常规技术，本领域的技术人员可以了解，通过视频分析模型对特殊作业现场的监控视频进行分析；还可以使用人工智能驱动，实时抓拍特殊作业现场区域的违规、不安全因素的视频、图像，上传至服务器进行深入的行为、状态分析；Video intelligent analysis and monitoring unit: obtain the monitoring video of the special operation site, and establish a video analysis model. The video analysis model is a neural network model, which uses the on-site monitoring video as input data, and the violations and unsafe factors in the on-site area as output data for training. Yes, the specific establishment process will not be described in detail, because the establishment of the neural network model is a conventional technology, and those skilled in the art can understand that the monitoring video of a special job site can be analyzed through the video analysis model; artificial intelligence can also be used to drive , capture videos and images of violations and unsafe factors in special operation site areas in real time, and upload them to the server for in-depth behavior and status analysis;
所述监测数据智能分析模块用于对采集的现场监测数据进行统一的数据处理，并发送到特殊作业数据库；The monitoring data intelligent analysis module is used to perform unified data processing on the collected on-site monitoring data, and send it to the special operation database;
设置作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库，作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库都是根据特殊作业的安全规范和使用要求进行设置的，将接收到的现场监测数据与作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库进行比对，根据不同的报警类型自动生成异 常报警信息数据库。Set up job analysis gas monitoring data threshold library, equipment monitoring data threshold library, on-site job ticket valid time database and video intelligent analysis library, job analysis gas monitoring data threshold library, equipment monitoring data threshold library, on-site job ticket valid time database and video intelligence The analysis library is set up according to the safety specifications and usage requirements of special operations, and combines the received on-site monitoring data with the operation analysis gas monitoring data threshold library, equipment monitoring data threshold library, on-site job ticket valid time database and video intelligent analysis library For comparison, an abnormal alarm information database is automatically generated according to different alarm types.
异常报警信息数据库包括：Abnormal alarm information database includes:
作业分析环境气体报警数据库：根据作业分析环境气体监测单元采集到的数据，按不同气体类型与作业分析气体监测数据阈值库和现场作业分析有效时间数据库进行比对，依据时间戳判断阈值有效时间，针对超出既定阈值范围的异常气体，生成相应的报警数据存入特殊作业分析环境气体报警数据库；Operation analysis environmental gas alarm database: According to the data collected by the operation analysis environmental gas monitoring unit, compare different gas types with the operation analysis gas monitoring data threshold database and the on-site operation analysis effective time database, and judge the effective time of the threshold according to the time stamp. For abnormal gases that exceed the predetermined threshold range, generate corresponding alarm data and store them in the special operation analysis environment gas alarm database;
设备运行状态报警数据库：将设备运行状态监测单元采集到的设备运行状态数据与设备监测数据阈值库进行实时匹配比对，针对比对结果，将异常的数据生成相应的报警数据存入设备运行状态报警数据库；Equipment operation status alarm database: The equipment operation status data collected by the equipment operation status monitoring unit is matched and compared with the equipment monitoring data threshold database in real time. According to the comparison results, abnormal data is generated and corresponding alarm data is stored in the equipment operation status Alarm database;
特殊作业状态监控报警数据库：动态获取现场作业实时持续时间(发生中止、暂停等异常情况进行智能校正)，将获取的持续时间与不同现场作业类型作业票有效时间数据库进行比对，针对比对结果异常的数据生成相应的报警数据存入特殊作业状态监控报警数据库；Special operation status monitoring and alarm database: Dynamically obtain the real-time duration of on-site operations (smart correction for abnormal situations such as suspension and suspension), compare the obtained duration with the valid time database of different types of on-site operation tickets, and compare the results of the comparison Abnormal data generates corresponding alarm data and stores them in the special operation status monitoring alarm database;
视频智能分析报警数据库：根据获取现场作业区域的视频、图像，通过视频智能分析服务中的人员不安全行为和环境不安全因素等场景算法进行AI分析，实时比对，比对结果为异常的行为、场景存入视频智能分析报警数据库；其中的人员不安全行为包括人员未戴安全帽、非现场作业人员非法进入、违规抽烟等；环境不安全因素主要是作业过程中未落实相关安全措施，包括作业点某一区间内气体违规排放、空洞/窨井/地沟等未有覆盖物等；将视频智能分析监测单元的分析数据存入视频智能分析报警数据库。Video intelligent analysis alarm database: According to the video and image of the on-site operation area, AI analysis is carried out through scene algorithms such as personnel unsafe behavior and environmental unsafe factors in the video intelligent analysis service, real-time comparison, and the comparison result is abnormal behavior The scene is stored in the video intelligent analysis alarm database; the unsafe behavior of personnel includes personnel not wearing safety helmets, illegal entry of off-site operators, illegal smoking, etc. The environmental unsafe factors are mainly due to the failure to implement relevant safety measures during the operation process, including Illegal discharge of gas in a certain section of the operating point, voids/inspection wells/drains, etc. are not covered; the analysis data of the video intelligent analysis monitoring unit is stored in the video intelligent analysis alarm database.
结合报警信息数据库的内容，异常情况报警信息研判模块根据预设的不同报警类型、报警信息模板和报警等级规则，关联作业票中的风险辨识、作业分析、安全措施和现场操作步骤，智能研判报警的等级是中断作业或 者停止作业；根据不同情况进行研判和报警信息推送。Combined with the content of the alarm information database, the abnormal situation alarm information research and judgment module can intelligently analyze and judge the alarm by associating with the risk identification, job analysis, safety measures and on-site operation steps in the job ticket according to the preset different alarm types, alarm information templates and alarm level rules The highest level is to interrupt the operation or stop the operation; conduct research and judgment and push alarm information according to different situations.
具体的应用场景如下：The specific application scenarios are as follows:
情况一：设备监测数据阈值库与作业分析气体监测阈值库、现场作业票有效时间数据库组合。若气体环境不满足作业要求或现场作业票不在有效时间内则停止作业，生成报警信息，进行报警信息推送；若作业气体环境满足作业要求且作业票在有效时间内，但是设备位置和状态等不满足作业要求，则中断作业，生成报警信息并进行报警信息推送。Case 1: The equipment monitoring data threshold database is combined with the operation analysis gas monitoring threshold database and the on-site operation ticket valid time database. If the gas environment does not meet the operation requirements or the on-site operation ticket is not within the valid time, the operation will be stopped, an alarm message will be generated, and the alarm information will be pushed; If the operation requirements are met, the operation will be interrupted, and an alarm message will be generated and pushed.
情况二：视频智能分析库与作业分析气体监测阈值库、现场作业票有效时间数据库组合。若气体环境不满足作业要求或现场作业票不在有效时间内则停止作业，生成报警信息，进行报警信息推送；若作业气体环境满足作业要求且作业票在有效时间内，但是视频监测分析结果不满足作业要求，则中断作业，生成报警信息并进行报警信息推送。Case 2: The video intelligent analysis database is combined with the operation analysis gas monitoring threshold database and the on-site operation ticket valid time database. If the gas environment does not meet the operation requirements or the on-site operation ticket is not within the valid time, the operation will be stopped, an alarm message will be generated, and the alarm information will be pushed; If the job requires, the job will be interrupted, an alarm message will be generated and the alarm message will be pushed.
情况三：作业分析气体监测阈值库与现场作业票有效时间数据库组合，若现场作业票不在有效时间内则停止作业生成报警信息，进行报警信息推送；若现场作业票在有效时间内但气体环境不满足作业要求则中断作业生成报警信息，进行报警信息推送。Case 3: The job analysis gas monitoring threshold database is combined with the valid time database of the on-site operation ticket. If the on-site operation ticket is not within the valid time, the operation will be stopped to generate alarm information and the alarm information will be pushed; if the on-site operation ticket is within the valid time but the gas environment is not If the job requirements are met, the job will be interrupted to generate an alarm message, and the alarm message will be pushed.
情况四：设备监测数据阈值库与现场那作业票有限时间数据库组合，若现场作业票不在有效时间内则停止作业生成报警信息，进行报警信息推送；若现场作业票在有效时间内但设备位置、状态等不符合作业要求则中断作业，生成报警信息，进行报警信息推送。Situation 4: The equipment monitoring data threshold database is combined with the on-site job ticket limited time database. If the on-site job ticket is not within the valid time, the operation will be stopped to generate alarm information and the alarm information will be pushed; if the on-site job ticket is within the valid time but the equipment location, If the status does not meet the job requirements, the job will be interrupted, an alarm message will be generated, and the alarm message will be pushed.
情况五：视频智能分析库与现场那作业票有限时间数据库组合，若现场作业票不在有效时间内则停止作业生成报警信息，进行报警信息推送；若现场作业票在有效时间内，但视频智能分析结果不满足作业要求则中断作业，生成报警信息，进行报警信息推送。Situation 5: The video intelligent analysis library is combined with the on-site job ticket limited time database. If the on-site job ticket is not within the valid time, the operation will be stopped to generate an alarm message, and the alarm message will be pushed; if the on-site job ticket is within the valid time, but the video intelligent analysis If the result does not meet the job requirements, the job will be interrupted, an alarm message will be generated, and the alarm message will be pushed.
本专利以上述五种情况为例，包含但不限于以上五种情况。针对不同 作业环境和特殊作业类型，进行数据库的智能组合，能够有针对性地进行提高异常情况处置效率。This patent takes the above five situations as examples, including but not limited to the above five situations. According to different operating environments and special types of operations, the intelligent combination of databases can improve the efficiency of handling abnormal situations in a targeted manner.
***根据报警信息研判的内容，自动生成报警信息，主要包括作业地点、报警类型、报警内容、报警级别、报警信息推送和处置人员等内容；并以声光报警、短信、电话、APP等方式将报警信息推送不同的人员，主要包括特殊作业监护人员、作业人员、作业负责人、安全管理人员、企业负责人等。The system automatically generates alarm information based on the content of the alarm information research and judgment, mainly including work location, alarm type, alarm content, alarm level, alarm information push and disposal personnel, etc.; The alarm information is sent to different personnel, mainly including special operation monitoring personnel, operating personnel, operation leaders, safety management personnel, and enterprise leaders, etc.
所述现场异常情况处置反馈模块根据报警研判的内容，相关人员通过现场作业移动端对现场异常处置情况进行填报，支持语音、图片、文字等多种形式内容录入；根据填报的内容与作业票内容进行关联，作业票内容包括作业分析、风险管控措施落实、作业有效时间等内容，自动判断是否恢复作业，当作业分析气体监测不超标、作业分析在有效时间且作业票在有效期内，则恢复作业，重新开始特殊作业现场监测和管控；The on-site abnormal situation handling feedback module is based on the content of the alarm research and judgment, and relevant personnel fill in the on-site abnormal handling situation through the on-site operation mobile terminal, and support voice, picture, text and other forms of content input; according to the filled-in content and job ticket content For association, the content of the job ticket includes job analysis, implementation of risk control measures, and valid time of the job, etc., and automatically judges whether to resume the job. , re-start special operation site monitoring and control;
当整改时间超过作业票有效时间或者作业分析气体仍然超标，则重新申请作业。When the rectification time exceeds the valid time of the job ticket or the job analysis gas still exceeds the standard, re-apply for the job.
基于物联网的特殊作业现场异常预警分析***的分析方法，具体方法包括：The analysis method of the abnormal early warning analysis system for special job sites based on the Internet of Things, the specific methods include:
步骤一：对异常情况监测数据进行采集；Step 1: Collect abnormal situation monitoring data;
步骤二：对采集的现场作业监测数据进行统一的数据处理，汇集到特殊作业数据库；Step 2: Perform unified data processing on the collected on-site operation monitoring data and collect them into the special operation database;
步骤三：智能研判报警的等级是中断作业或者停止作业；根据不同情况进行研判和报警信息推送；Step 3: The level of intelligent judgment and alarm is to interrupt the operation or stop the operation; conduct research and judgment and push the alarm information according to different situations;
步骤四：根据报警研判的内容，对现场异常处置情况进行填报，根据填报的内容与作业票内容进行关联，自动判断是否恢复作业。Step 4: According to the content of the alarm research and judgment, fill in the report of the abnormal handling situation on the site, associate the filled content with the content of the job ticket, and automatically judge whether to resume the operation.
在本发明所提供的实施例中，应该理解到，所揭露的设备，装置和方 法，可以通过其他的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式；所述作为分离部件说明的模块可以是或者也可以不是物理上分开的，作为模块显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方法的目的。In the embodiments provided in the present invention, it should be understood that the disclosed devices, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods during actual implementation; the modules described as separate components can be It may or may not be physically separated, and components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the method in this embodiment.
另对于本领域技术人员而言，显然本发明不限于上述示范性实施例的细节，而且在不背离本发明的精神或基本特征的情况下，能够以其他的具体形式实现本发明。In addition, it is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.
因此，无论从哪一点来看，均应将实施例看作是示范性的，而且是非限制性的，本发明的范围由所附权利要求而不是上述说明限定，因此旨在将落在权利要求的等同要件的含义和范围内的所有变化涵括在本发明内。不应将权利要求中的任何附关联图标记视为限制所涉及的权利要求。Accordingly, the embodiments should be regarded in all points of view as exemplary and not restrictive, the scope of the invention being defined by the appended claims rather than the foregoing description, and it is therefore intended that the scope of the invention be defined by the appended claims rather than by the foregoing description. All changes within the meaning and range of equivalents of the elements are embraced in the present invention. Any reference sign in a claim should not be construed as limiting the claim concerned.
此外，显然“包括”一词不排除其他单元或步骤，单数不排除复数。***权利要求中陈述的多个单元或装置也可以由一个单元或装置通过软件或者硬件来实现。第二等词语用来表示名称，而并不表示任何特定的顺序。In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or devices stated in the system claims may also be realized by one unit or device through software or hardware. Secondary terms are used to denote names without implying any particular order.
最后应说明的是，以上实施例仅用以说明本发明的技术方法而非限制，尽管参照较佳实施例对本发明进行了详细说明，本领域的普通技术人员应当理解，可以对本发明的技术方法进行修改或等同替换，而不脱离本发明技术方法的精神和范围。Finally, it should be noted that the above embodiments are only used to illustrate the technical method of the present invention without limitation, although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be Modifications or equivalent replacements can be made without departing from the spirit and scope of the technical method of the present invention.

Claims (8)

  1. 基于物联网的特殊作业现场异常预警分析***，其特征在于，包括监测数据采集模块、监测数据智能分析模块、异常情况报警信息研判模块、现场异常情况处置反馈模块和特殊作业数据库；The Internet of Things-based abnormal early warning and analysis system for special operation sites is characterized in that it includes a monitoring data collection module, a monitoring data intelligent analysis module, an abnormal situation alarm information research and judgment module, a field abnormal situation handling feedback module and a special operation database;
    所述监测数据采集模块用于对异常情况监测数据进行采集，并将采集的现场监测数据发送到监测数据智能分析模块；所述监测数据智能分析模块对采集的现场监测数据进行统一的数据处理，并将处理后的数据发送到特殊作业数据库；The monitoring data collection module is used to collect abnormal situation monitoring data, and send the collected on-site monitoring data to the monitoring data intelligent analysis module; the monitoring data intelligent analysis module performs unified data processing on the collected on-site monitoring data, and send the processed data to a special job database;
    异常情况报警信息研判模块根据预设的不同报警类型、报警信息模板和报警等级规则，关联作业票中的风险辨识、作业分析、安全措施和现场操作步骤，智能研判报警的等级是中断作业或者停止作业；根据不同情况进行研判和报警信息推送；According to the preset different alarm types, alarm information templates and alarm level rules, the abnormal situation alarm information research and judgment module is associated with the risk identification, job analysis, safety measures and on-site operation steps in the job ticket, and intelligently judges whether the level of the alarm is to interrupt the operation or stop homework; conduct research and judgment and push alarm information according to different situations;
    现场异常情况处置反馈模块根据报警研判的内容，对现场异常处置情况进行填报，根据填报的内容与作业票内容进行关联，自动判断是否恢复作业，当作业分析气体监测不超标、作业分析在有效时间且作业票在有效期内，则恢复作业，重新开始特殊作业现场监测和管控；The on-site abnormal situation disposal feedback module fills in the on-site abnormal disposal situation according to the content of the alarm research and judgment, and correlates the filled-in content with the content of the job ticket, and automatically judges whether to resume the operation. And if the work ticket is within the validity period, the work will be resumed, and the on-site monitoring and control of special operations will be restarted;
    当整改时间超过作业票有效时间或者作业分析气体仍然超标，则重新申请作业。When the rectification time exceeds the valid time of the job ticket or the job analysis gas still exceeds the standard, re-apply for the job.
  2. 根据权利要求1所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，监测数据采集模块包括作业环境气体分析监测单元、设备运行状态监测单元、特殊作业状态监测单元和视频智能分析监测单元；According to claim 1, the internet-of-things-based abnormal early warning and analysis system for special operation sites is characterized in that the monitoring data acquisition module includes an operation environment gas analysis and monitoring unit, an equipment operation status monitoring unit, a special operation status monitoring unit and video intelligent analysis monitoring unit;
    作业分析环境气体监测单元：将作业票与气体检测设备进行关联，获取气体检测设备的配置参数，根据配置参数获取对应气体检测设备的监测数据；Job analysis environment gas monitoring unit: associate the job ticket with the gas detection equipment, obtain the configuration parameters of the gas detection equipment, and obtain the monitoring data of the corresponding gas detection equipment according to the configuration parameters;
    设备运行状态监测单元：根据厂区平面图划分现场作业区域，与现有的自动化控制***进行对接，获取自动化控制***的配置参数，根据配置 参数获取特殊作业现场区域内设备运行数据；Equipment operation status monitoring unit: divide the on-site operation area according to the factory floor plan, connect with the existing automation control system, obtain the configuration parameters of the automation control system, and obtain the equipment operation data in the special operation site area according to the configuration parameters;
    特殊作业状态监测单元：根据特殊作业申请审批的完成时间，自动同步特殊作业开始时间，动态计算现场作业的持续时间，并针对异常情况进行实时校准，并生成相应的作业报告发送至对应的管理人员；Special operation status monitoring unit: according to the completion time of special operation application approval, automatically synchronize the special operation start time, dynamically calculate the duration of on-site operations, and perform real-time calibration for abnormal situations, and generate corresponding operation reports and send them to corresponding management personnel ;
    视频智能分析监测单元：获取特殊作业现场的监控视频，建立视频分析模型，通过视频分析模型对特殊作业现场的监控视频进行分析。Video intelligent analysis and monitoring unit: obtain the surveillance video of the special operation site, establish a video analysis model, and analyze the surveillance video of the special operation site through the video analysis model.
  3. 根据权利要求2所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，监测数据智能分析模块的工作方法包括：According to claim 2, the Internet of Things-based abnormal early warning and analysis system for special job sites is characterized in that the working method of the monitoring data intelligent analysis module includes:
    设置作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库，将接收到的现场监测数据与作业分析气体监测数据阈值库、设备监测数据阈值库、现场作业票有效时间数据库和视频智能分析库进行比对，根据不同的报警类型自动生成异常报警信息数据库。Set up the operation analysis gas monitoring data threshold library, equipment monitoring data threshold The job ticket effective time database is compared with the video intelligent analysis database, and the abnormal alarm information database is automatically generated according to different alarm types.
  4. 根据权利要求3所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，异常报警信息数据库包括：作业分析环境气体报警数据库、设备运行状态报警数据库、特殊作业状态监控报警数据库和视频智能分析报警数据库。According to claim 3, the Internet of Things-based abnormal early warning and analysis system for special operation sites is characterized in that the abnormal alarm information database includes: operation analysis environment gas alarm database, equipment operation status alarm database, special operation status monitoring alarm database and video Intelligent analysis alarm database.
  5. 根据权利要求4所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，作业分析环境气体报警数据库：根据作业分析环境气体监测单元采集到的数据，按不同气体类型与作业分析气体监测数据阈值库和现场作业分析有效时间数据库进行比对，依据时间戳判断阈值有效时间，针对超出既定阈值范围的异常气体，生成相应的报警数据存入特殊作业分析环境气体报警数据库。According to claim 4, the internet-of-things-based abnormal early warning and analysis system for special operation sites is characterized in that the operation analysis environment gas alarm database: according to the data collected by the operation analysis environment gas monitoring unit, the gas is analyzed according to different gas types and operations The monitoring data threshold database is compared with the on-site operation analysis effective time database, and the threshold effective time is judged according to the time stamp. For abnormal gases exceeding the predetermined threshold range, corresponding alarm data is generated and stored in the special operation analysis environmental gas alarm database.
  6. 根据权利要求4所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，设备运行状态报警数据库：将设备运行状态监测单元采 集到的设备运行状态数据与设备监测数据阈值库进行实时匹配比对，针对比对结果，将异常的数据生成相应的报警数据存入设备运行状态报警数据库。According to claim 4, the abnormal early warning and analysis system for special job sites based on the Internet of Things is characterized in that the equipment operation state alarm database: the equipment operation state data collected by the equipment operation state monitoring unit and the equipment monitoring data threshold database are real-time Matching and comparison, according to the comparison results, generate corresponding alarm data for abnormal data and store them in the equipment operation status alarm database.
  7. 根据权利要求4所述的基于物联网的特殊作业现场异常预警分析***，其特征在于，特殊作业状态监控报警数据库：动态获取现场作业实时持续时间，将获取的持续时间与不同现场作业类型作业票有效时间数据库进行比对，针对比对结果异常的数据生成相应的报警数据存入特殊作业状态监控报警数据库。According to claim 4, the Internet of Things-based special operation site abnormal early warning analysis system is characterized in that the special operation status monitoring and alarm database: dynamically obtains the real-time duration of on-site operations, and compares the acquired duration with different types of on-site operation job tickets The effective time database is compared, and the corresponding alarm data is generated for the abnormal data of the comparison result and stored in the special operation status monitoring alarm database.
  8. 根据权利要求1-7任一项所述的基于物联网的特殊作业现场异常预警分析***的分析方法，其特征在于，具体方法包括：According to any one of claims 1-7, the analysis method based on the Internet of Things abnormal early warning analysis system for special job sites is characterized in that the specific methods include:
    步骤一：对异常情况监测数据进行采集；Step 1: Collect abnormal situation monitoring data;
    步骤二：对采集的现场作业监测数据进行统一的数据处理，汇集到特殊作业数据库；Step 2: Perform unified data processing on the collected on-site operation monitoring data and collect them into the special operation database;
    步骤三：智能研判报警的等级是中断作业或者停止作业，根据不同情况进行研判和报警信息推送；Step 3: The level of intelligent judgment and alarm is to interrupt the operation or stop the operation, and carry out research and judgment and push the alarm information according to different situations;
    步骤四：根据报警研判的内容，对现场异常处置情况进行填报，根据填报的内容与作业票内容进行关联，自动判断是否恢复作业。Step 4: According to the content of the alarm research and judgment, fill in the report of the abnormal handling situation on the site, associate the filled content with the content of the job ticket, and automatically judge whether to resume the operation.
PCT/CN2022/113444 2021-09-17 2022-08-19 Internet-of-things-based abnormality early warning analysis system and method for special operation site WO2023040575A1 (en)

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