Internet-of-things-based intelligent safety monitoring method and system for power plant operation

Abstract

An Internet-of-Things-based intelligent safety monitoring method and system for power plant operation. The method comprises: deploying sensors and collecting monitoring data in real time; transmitting the collected data to a central server, performing data processing, integrating the monitoring data, calculating a comprehensive environmental index, and preliminarily assessing an environmental monitoring condition; and comprehensively determining a device fault condition, remotely monitoring device status, starting a device emergency response mechanism, and performing intelligent safety monitoring of power plant operation. Power plant devices and environment parameters are monitored in real time, so that device anomalies and potential safety hazards are promptly captured to achieve rapid response. The stability of the power plant is improved, and a video monitoring system is integrated in combination with image recognition technology to monitor anomalous events in the power plant area. The level of safety management is enhanced, and decisions can be quickly made in emergency situations, improving flexibility and efficiency and enhancing management effectiveness and the accuracy and stability of the monitoring system.

Description

A method and system for intelligent safety monitoring of power plant operation based on the Internet of Things Technical Field

[0001] The present invention relates to the technical field of power plant operation, and in particular to an Internet of Things-based intelligent safety monitoring method and system for power plant operation. Background Art

[0002] Currently, power plant operation monitoring systems have achieved a certain degree of real-time monitoring of key equipment. These systems collect operational data from equipment, including temperature, humidity, vibration, and other parameters, through a sensor network and transmit this data to a central server via the Internet of Things (IoT). These real-time monitoring systems utilize image recognition and intelligent algorithms to monitor power plant equipment, including belt operation status, belt tears, and temperature anomalies. Furthermore, video surveillance systems are widely used to provide visual monitoring of power plant areas.

[0003] The intelligent algorithms and image recognition technologies of existing systems still have limitations in accurately monitoring complex scenarios, especially in harsh environmental conditions such as high temperature and high humidity. Furthermore, the prediction and diagnosis of equipment failures still rely on empirical rules and lack the ability to conduct deep learning on large amounts of historical data. At the same time, the remote control capabilities of existing systems are limited, making it impossible to achieve real-time remote intervention in equipment. Furthermore, the efficiency of data processing and analysis urgently needs to be improved to more quickly respond to equipment anomalies and safety incidents. Overall, existing technologies still require further innovation and improvement in improving power plant operational safety and reducing failure risks.

[0004] Summary of the Invention

[0005] The present invention is proposed in view of the problems existing in the existing power plant operation intelligent safety monitoring method based on the Internet of Things. Therefore, the problem to be solved by the present invention is how to provide a power plant operation intelligent safety monitoring method and system based on the Internet of Things.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for intelligent safety monitoring of power plant operation based on the Internet of Things, which includes deploying sensors in the power plant environment, and collecting monitoring data in real time through the sensors connected to the Internet of Things; transmitting the collected data to a central server through the Internet of Things, performing data processing, integrating the monitoring data, calculating a comprehensive environmental index, and preliminarily judging the environmental monitoring situation; comprehensively judging the equipment failure situation based on the processed monitoring data, remotely monitoring the equipment status, starting the equipment emergency response mechanism, and performing intelligent safety monitoring of the power plant operation.

[0008] As a preferred solution of the intelligent safety monitoring method for power plant operation based on the Internet of Things described in the present invention, the sensors include temperature sensors, humidity sensors, vibration sensors, smoke sensors, gas sensors and image sensors; the monitoring data includes environmental monitoring data and equipment monitoring data, the equipment monitoring data includes equipment working status data, and the environmental monitoring data includes temperature, humidity, gas concentration and environmental identification data.

[0009] As a preferred solution of the method for intelligent safety monitoring of power plant operation based on the Internet of Things described in the present invention, the data processing includes the following steps: pre-processing the acquired environmental monitoring data and calculating the environmental detection score; when the real-time ambient temperature T is less than the first temperature threshold T1, the temperature score is recorded as 1 point; when the real-time ambient temperature T is greater than or equal to the first temperature threshold T1, the temperature score is recorded as 2 points; when the ambient humidity H is less than the first humidity threshold H1, the ambient humidity score is recorded as 1 point; when the ambient humidity data H is greater than or equal to the first humidity threshold H1, the ambient humidity score is recorded as 1 point. The score is recorded as 2 points; when the ambient gas concentration G is less than the first limit concentration G1, the gas concentration score is recorded as 1 point; when the first limit concentration G1≤G<the second limit concentration G2, the gas concentration score is recorded as 2 points; when the ambient gas concentration G≥the second limit concentration G2, the gas concentration score is recorded as 3 points, and smoke monitoring and fire monitoring are triggered at the same time to monitor the occurrence of smoke and the possibility of fire, adjust the monitoring equipment to identify and lock the smoke occurrence area, issue an alarm command, interrupt the continued monitoring behavior, immediately trigger the use of environmental identification data, and judge the environmental monitoring situation.

[0010] As a preferred solution of the method for intelligent safety monitoring of power plant operation based on the Internet of Things of the present invention, the calculation of the comprehensive environmental index includes evaluating the environmental monitoring situation according to the obtained environmental parameter grade score classification results. The relevant calculation formula is:

[0011] E=ω T ·T+ω H ·H+ω G ·G

[0012] Where, E is the comprehensive environmental index, ω T 、ω H 、ω G They are the weights of the corresponding environmental parameters respectively; evaluate the real-time status of the environment according to the comprehensive environmental index, continue environmental monitoring and identification, and start the personnel identification, safety helmet identification, work clothes identification and vehicle information identification systems.

[0013] As a preferred solution of the method for intelligent safety monitoring of power plant operation based on the Internet of Things of the present invention, wherein: the evaluation of the real-time status of environmental monitoring includes calculating the first environmental index f1, and the relevant calculation formula is as follows:

[0014] Where, T min is the lower limit of acceptable temperature for the power plant working environment, T max T is the upper limit of acceptable temperature for the power plant working environment. o is the optimal temperature of the power plant working environment, H min The lower limit of acceptable humidity in the working environment of a power plant, H max is the upper limit of acceptable humidity in the working environment of the power plant, G max is the maximum acceptable gas concentration in the working environment of the power plant, ω1, ω2 and ω3 are the weights of temperature, humidity and gas concentration factors respectively; when the comprehensive environmental index E is less than the first environmental index f1, the real-time status of environmental monitoring is evaluated as Level 1, the power plant is currently in a normal working environment, the equipment accident monitoring program is started, and equipment accident monitoring is prepared, the equipment operation status is checked, and the main equipment is monitored in real time; when the comprehensive environmental index E is greater than or equal to the first environmental index f1, but the degree of excess is less than 100%, the real-time status of environmental monitoring is evaluated as Level 2, the environmental parameters are adjusted, the equipment operation status is checked, the equipment parameters and indoor temperature and humidity are adjusted, ventilation is maintained, the gas concentration is reduced, and the environmental index is recalculated after stabilization for a second evaluation. If the real-time status of environmental monitoring in the second evaluation still remains at Level 2 When the environmental monitoring real-time status assessment result is raised to level 3 for processing, if the environmental monitoring real-time status is restored to level 1 in the second assessment, the normal operating status of the equipment is restored and normal operation is maintained; when the comprehensive environmental index E ≥ the first environmental index f1, but the degree of excess is higher than 100%, the environmental monitoring real-time status is assessed to be level 3, and a detailed inspection of the equipment is started, the equipment working parameters are adjusted, the indoor temperature and humidity and air purification equipment, emergency ventilation equipment are immediately adjusted, the ventilation system and fire monitoring system are immediately operated, emergency evacuation notices and alarms are sent to evacuate staff, equipment fault inspection is carried out, and a second assessment is immediately carried out. If the environmental monitoring real-time status is below level 2 in the second assessment, the equipment monitoring status is lowered, the environmental parameters are continuously monitored, and the ventilation system is continued to be started for level 2 status processing.

[0015] As a preferred solution of the method for intelligent safety monitoring of power plant operation based on the Internet of Things described in the present invention, the equipment accident monitoring includes belt deviation monitoring, tearing monitoring, coal spillage monitoring, coal bubbling monitoring, plug plate position monitoring, coal incoming monitoring, baffle flipping monitoring and folding monitoring; monitor equipment failure conditions and activate the equipment emergency response mechanism.

[0016] As a preferred solution of the method for intelligent safety monitoring of power plant operation based on the Internet of Things described in the present invention, the starting equipment emergency response mechanism includes: when the equipment fault monitoring result is a belt deviation fault, starting the automatic correction system, adjusting the belt position to return it to its original position, sending specific deviation position information, and immediately alarming and notifying the operation and maintenance personnel to handle it; when the equipment fault monitoring result is a belt tearing fault, immediately triggering the shutdown mechanism to prevent further damage and danger, sending a tearing fault alarm to the operation and maintenance personnel, and providing relevant images and data for remote diagnosis; when the equipment fault monitoring result is a coal spilling fault, starting the cleaning system, cleaning the coal, restoring the conveying system, and adjusting the conveying parameters according to the monitored coal spilling situation; when the equipment fault monitoring result is a coal bubbling fault, immediately triggering the shutdown protection mechanism, stopping the operation of related equipment, and at the same time triggering the fire fighting system preparation, sending an emergency alarm notification, Provide the specific location of coal leakage and fire risk assessment; when the equipment fault monitoring result is an abnormal plug-in board failure, the shutdown protection is triggered, and manual reset or replacement of the abnormal plug-in board is performed according to the specific situation to ensure that the system resumes normal operation, provide remote monitoring and guidance services, diagnose problems through the remote system and perform corresponding operations; when the equipment fault monitoring result is an abnormal coal incoming failure, when unauthorized material is detected entering, the shutdown protection is triggered, the operation of the conveying system is stopped, and personnel are notified for verification and processing; when the equipment fault monitoring result is a baffle flip-over failure, the shutdown mechanism is immediately triggered, relevant images and data are provided for diagnosis, and the safety system is triggered at the same time; after the fault is resolved, the system automatically resets to ensure that the equipment smoothly returns to normal operation, obtains equipment status information through remote means, records and analyzes each fault, forms a fault report, and improves the algorithm and parameters of the monitoring system based on the fault analysis results.

[0017] In the second aspect, the present invention provides an intelligent safety monitoring system for power plant operation based on the Internet of Things, which includes: an acquisition module for deploying sensors in the power plant environment, and collecting monitoring data in real time through sensors connected to the Internet of Things; a processing module for transmitting the collected data to a central server through the Internet of Things, performing data processing, integrating monitoring data, calculating a comprehensive environmental index, and preliminarily judging the environmental monitoring situation; a monitoring module for comprehensively judging equipment failure conditions based on the processed monitoring data, remotely monitoring equipment status, starting an equipment emergency response mechanism, and performing intelligent safety monitoring of power plant operation.

[0018] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements the steps of an intelligent safety monitoring method for power plant operation based on the Internet of Things.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the steps of the method for intelligent safety monitoring of power plant operation based on the Internet of Things are implemented.

[0020] The beneficial effects of the present invention include establishing a sensor network to monitor power plant equipment and environmental parameters in real time, promptly capturing equipment anomalies and safety hazards, and enabling rapid responses. This reduces the probability of equipment failure and improves the stability of the power plant. The integrated video surveillance system, combined with image recognition technology, enables monitoring of abnormal events in the power plant area. It can automatically identify different types of safety issues and issue alarms, improving safety management. Operations and maintenance personnel can remotely monitor equipment status and perform remote operations. In emergency situations, decisions can be made quickly, improving the flexibility and efficiency of operations and maintenance. This improves equipment utilization and energy efficiency, and enhances management effectiveness and the accuracy and stability of the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] FIG1 is a flow chart of an intelligent safety monitoring method for power plant operation based on the Internet of Things. DETAILED DESCRIPTION

[0023] To make the above-mentioned objects, features, and advantages of the present invention more easily understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0026] Example 1

[0027] 1 , which is a first embodiment of the present invention, provides a method for intelligent safety monitoring of power plant operation based on the Internet of Things, including:

[0028] S1: Deploy sensors in the power plant environment and collect monitoring data in real time through sensors connected by the Internet of Things.

[0029] Specifically, temperature sensors: installed on key equipment (generators, transformers, etc.) and various areas of the power plant to monitor temperature changes and issue warnings of overheating or overcooling. Humidity sensors: installed on key equipment and areas where humidity is prone to accumulate to monitor humidity levels and prevent humid environments from affecting equipment performance. Vibration sensors: installed on important rotating mechanical equipment to monitor vibration frequency, detect abnormal vibrations, and prevent mechanical failures. Smoke sensors: distributed in various areas of the power plant, especially areas with potential fire risks, to monitor the smoke concentration in the air in real time. Gas sensors: used to monitor the concentration of key gases, such as carbon monoxide and carbon dioxide, to ensure a safe working environment. The real-time operating status of the equipment is monitored through equipment sensors, such as the speed, voltage, current, etc. of the generator. The vibration frequency monitors the vibration frequency of the equipment to detect whether there is abnormal vibration in the mechanical equipment. The image sensor is a monitoring device.

[0030] Monitoring data includes environmental monitoring data and equipment monitoring data. Equipment monitoring data includes equipment working status data, and environmental parameters include temperature, humidity, gas concentration and other environmental parameters to ensure that the equipment operates in a suitable environment.

[0031] S2: The collected data is transmitted to the central server through the Internet of Things for data processing, integration of monitoring data, calculation of comprehensive environmental index, and preliminary judgment of environmental monitoring status;

[0032] Specifically, the acquired environmental monitoring data is pre-processed and the environmental detection score is calculated;

[0033] When the real-time ambient temperature T is less than the first temperature threshold T1, the temperature score is recorded as 1 point; when the real-time ambient temperature T is greater than or equal to the first temperature threshold T1, the temperature score is recorded as 2 points;

[0034] When the ambient humidity H is less than the first humidity threshold H1, the ambient humidity score is recorded as 1 point; when the ambient humidity data H is greater than or equal to the first humidity threshold H1, the ambient humidity score is recorded as 2 points;

[0035] When the ambient gas concentration G is less than the first limit concentration G1, the gas concentration score is recorded as 1 point; when the first limit concentration G1≤G<the second limit concentration G2, the gas concentration score is recorded as 2 points; when the ambient gas concentration G≥the second limit concentration G2, the gas concentration score is recorded as 3 points, and smoke monitoring and fire monitoring are triggered at the same time to monitor the occurrence of smoke and the possibility of fire, adjust the monitoring equipment to identify and lock the smoke occurrence area, issue an alarm command, interrupt the continued monitoring behavior, immediately trigger the use of environmental identification data, and judge the environmental monitoring situation.

[0036] The environmental monitoring situation is evaluated based on the environmental parameter grade score classification results. The relevant calculation formula is:

[0037] E=ω T ·T+ω H ·H+ω G ·G

[0038] Where, E is the comprehensive environmental index, ω T 、ω H 、ω G are the weights of the corresponding environmental parameters;

[0039] Assess the real-time status of the environment based on the comprehensive environmental index, continue environmental monitoring and identification, and activate personnel identification, safety helmet identification, work clothes identification, and vehicle information identification systems.

[0040] Calculate the first environmental index f1, the relevant calculation formula is as follows:

[0041] Where, T min is the lower limit of acceptable temperature for the power plant working environment, T max T is the upper limit of acceptable temperature for the power plant working environment. o is the optimal temperature of the power plant working environment, H min The lower limit of acceptable humidity in the working environment of a power plant, H max is the upper limit of acceptable humidity in the working environment of the power plant, G max is the maximum acceptable gas concentration in the power plant working environment, ω1, ω2 and ω3 are the weights of temperature, humidity and gas concentration factors respectively;

[0042] When the comprehensive environmental index E is less than the first environmental index f1, the real-time status of environmental monitoring is assessed as level 1. The power plant is currently in a normal working environment. The equipment accident monitoring program is started to prepare for equipment accident monitoring, check the equipment operating status, and conduct real-time monitoring of major equipment.

[0043] When the comprehensive environmental index E ≥ the first environmental index f1, but the degree of excess is less than 100%, the real-time status of environmental monitoring is assessed as Level 2, and the environmental parameters are adjusted. At the same time, the equipment operation is checked, the equipment parameters and indoor temperature and humidity are adjusted, ventilation is maintained, and the gas concentration is reduced. After stabilization, the environmental index is recalculated and a second assessment is conducted. If the real-time status of environmental monitoring remains at Level 2 after the second assessment, the real-time status assessment result of environmental monitoring is raised to Level 3 for processing. If the real-time status of environmental monitoring returns to Level 1 after the second assessment, the normal operation of the equipment is restored and normal operation is maintained;

[0044] When the comprehensive environmental index E ≥ the first environmental index f1, but the degree of excess is higher than 100%, the real-time status of environmental monitoring is assessed to be level 3, and detailed inspection equipment is started, equipment operating parameters are adjusted, indoor temperature and humidity, air purification equipment, and emergency ventilation equipment are immediately adjusted, the ventilation system and fire monitoring system are immediately operated, emergency evacuation notices and alarms are sent to evacuate staff, equipment faults are checked, and a secondary assessment is immediately conducted. If the real-time status of environmental monitoring in the secondary assessment is below level 2, the equipment monitoring status is reduced, environmental parameters are continuously monitored, and the ventilation system is continued to be started for level 2 status processing.

[0045] Equipment accident monitoring includes belt deviation monitoring, tearing monitoring, coal spillage monitoring, coal bubbling monitoring, plug plate position monitoring, coal incoming monitoring, belt flap overturning monitoring and folding monitoring; monitor equipment failure conditions and activate equipment emergency response mechanism.

[0046] S3: Comprehensively judge the equipment failure situation based on the processed monitoring data, remotely monitor the equipment status, activate the equipment emergency response mechanism, and conduct intelligent safety monitoring of power plant operation.

[0047] Specifically, when the equipment fault monitoring result is a belt deviation fault, the automatic correction system is started, the belt position is adjusted to return it to its original position, the specific deviation position information is sent, and an immediate alarm is issued to notify the operation and maintenance personnel for processing; when the equipment fault monitoring result is a belt tearing fault, the shutdown mechanism is immediately triggered to prevent further damage and danger, and a tearing fault alarm is sent to the operation and maintenance personnel, and relevant images and data are provided for remote diagnosis; when the equipment fault monitoring result is a coal spilling fault, the cleaning system is started, the coal is cleaned, the conveying system is restored, and the conveying parameters are adjusted according to the monitored coal spilling situation; when the equipment fault monitoring result is a coal bubbling fault, the shutdown protection mechanism is immediately triggered, the operation of related equipment is stopped, and the fire fighting system is triggered to prepare, an emergency alarm notification is sent, and the specific location of the coal bubbling and a fire risk assessment are provided; when the equipment fault monitoring result is a coal bubbling fault, the shutdown protection mechanism is immediately triggered, the operation of related equipment is stopped, and the fire fighting system is triggered to prepare, an emergency alarm notification is sent, and the specific location of the coal bubbling and a fire risk assessment are provided; When the result is an abnormal plug-in board failure, the shutdown protection is triggered, and manual reset or replacement of the abnormal plug-in board is performed according to the specific situation to ensure that the system resumes normal operation, provide remote monitoring and guidance services, diagnose problems through the remote system and perform corresponding operations; when the equipment fault monitoring result is an abnormal coal failure, when unauthorized material is detected entering, the shutdown protection is triggered, the operation of the conveying system is stopped, and personnel are notified for verification and processing; when the equipment fault monitoring result is a baffle flip-over failure, the shutdown mechanism is immediately triggered, relevant images and data are provided for diagnosis, and the safety system is triggered at the same time; after the fault is resolved, the system automatically resets to ensure that the equipment smoothly returns to normal operation, obtains equipment status information through remote means, records and analyzes each fault, forms a fault report, and improves the algorithm and parameters of the monitoring system based on the fault analysis results.

[0048] Furthermore, this embodiment also provides an intelligent safety monitoring system for power plant operation based on the Internet of Things, including: an acquisition module, used to deploy sensors in the power plant environment, and collect monitoring data in real time through sensors connected to the Internet of Things; a processing module, used to transmit the collected data to a central server through the Internet of Things, perform data processing, integrate monitoring data, calculate a comprehensive environmental index, and preliminarily judge the environmental monitoring situation; a monitoring module, used to comprehensively judge equipment failure conditions based on the processed monitoring data, remotely monitor equipment status, activate equipment emergency response mechanisms, and perform intelligent safety monitoring of power plant operation.

[0049] This embodiment also provides a computer device, which is suitable for the case of an intelligent safety monitoring method for power plant operation based on the Internet of Things, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement all or part of the steps of the method described in the embodiment of the present invention proposed in the above embodiment.

[0050] This embodiment further provides a storage medium having a computer program stored thereon, which, when executed by a processor, performs the method of any optional implementation of the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0051] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. Technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0052] As can be seen from the above, this method realizes real-time monitoring of power plant equipment and environmental parameters by establishing a sensor network, which can timely capture equipment anomalies and safety hazards and achieve rapid response. Improve the stability of the power plant. Combined with image recognition technology, it can realize the monitoring of abnormal events in the power plant area. The system can automatically identify different types of safety issues and issue timely alarms to improve the level of safety management. It can make decisions quickly in emergency situations and improve the flexibility and efficiency of operation and maintenance. The collected data is transmitted to the central server through the cloud platform or local area network for processing and analysis. Provide optimization suggestions for power plant operation and improve equipment utilization and energy efficiency. Comprehensively process the various monitoring results to form a comprehensive equipment monitoring report. Reduce the possibility of human error and improve management efficiency and the accuracy and stability of the monitoring system.

[0053] Example 2

[0054] Referring to Table 1, which is a second embodiment of the present invention, this embodiment provides an intelligent safety monitoring method for power plant operation based on the Internet of Things. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0055] Table 1 Technical characteristics comparison table

[0056] As can be seen from the above, this method realizes real-time monitoring of power plant equipment and environmental parameters by establishing a sensor network, which can timely capture equipment anomalies and safety hazards and achieve rapid response. Improve the stability of the power plant. Combined with image recognition technology, it can realize the monitoring of abnormal events in the power plant area. The system can automatically identify different types of safety issues and issue timely alarms to improve the level of safety management. It can make decisions quickly in emergency situations and improve the flexibility and efficiency of operation and maintenance. The collected data is transmitted to the central server through the cloud platform or local area network for processing and analysis. Provide optimization suggestions for power plant operation and improve equipment utilization and energy efficiency. Comprehensively process the various monitoring results to form a comprehensive equipment monitoring report. Reduce the possibility of human error and improve management efficiency and the accuracy and stability of the monitoring system.

[0057] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent safety monitoring method for power plant operation based on the Internet of Things, characterized in that: Including, Deploy sensors in the power plant environment, and collect monitoring data in real time through Internet of Things-connected sensors; Transmit the collected data to the central server through the Internet of Things, perform data processing, integrate the monitoring data, calculate the comprehensive environment index, and preliminarily judge the environmental monitoring situation; Comprehensively judge the equipment failure situation based on the processed monitoring data, remotely monitor the equipment status, start the equipment emergency response mechanism, and conduct intelligent safety monitoring of the power plant operation.

2. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 1, characterized in that: The sensors include temperature sensors, humidity sensors, vibration sensors, smoke sensors, gas sensors, and image sensors; the monitoring data includes environmental monitoring data and equipment monitoring data, the equipment monitoring data includes equipment working status data, and the environmental monitoring data includes temperature, humidity, gas concentration, and environmental identification data.

3. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 2, characterized in that: The data processing includes the following steps: Pre-process the obtained environmental monitoring data and calculate the environmental detection score; When the real-time environmental temperature T < the first temperature threshold T1, the temperature score is recorded as 1 point; when the real-time environmental temperature T ≥ the first temperature threshold T1, the temperature score is recorded as 2 points; When the environmental humidity H < the first humidity threshold H1, the environmental humidity score is recorded as 1 point; when the environmental humidity data H ≥ the first humidity threshold H1, the environmental humidity score is recorded as 2 points; When the environmental gas concentration G < the first limit concentration G1, the gas concentration score is recorded as 1 point; When the first limit concentration G1 ≤ G < the second limit concentration G2, the gas concentration score is recorded as 2 points; When the environmental gas concentration G ≥ the second limit concentration G2, the gas concentration score is recorded as 3 points, and at the same time, trigger smoke monitoring and fire monitoring, monitor the occurrence of smoke and the possibility of fire, adjust the monitoring equipment to identify and lock the smoke occurrence area, issue an alarm instruction, interrupt the continuous monitoring behavior, immediately trigger the use of environmental identification data, and judge the environmental monitoring situation.

4. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 3, wherein: The calculated comprehensive environment index includes evaluating and judging the environmental monitoring situation based on the obtained environmental parameter score results. The relevant calculation formula is: E = ω T ·T + ω H ·H + ω G ·G where E is the comprehensive environment index, and ω T , ω H , ω G are the weights of the corresponding environment parameters respectively; Evaluate the real-time status of environmental monitoring based on the comprehensive environment index, and start the personnel identification, safety helmet identification, Work uniform identification, and vehicle information identification systems.

5. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 4, characterized in that: The evaluation of the real-time status of environmental monitoring includes: Calculate the first environmental index f1, and the relevant calculation formula is as follows: Wherein, T min is the lower limit of the acceptable temperature of the power plant working environment, T max is the upper limit of the acceptable temperature of the power plant working environment, T o is the optimal temperature of the power plant working environment, H min is the lower limit of the acceptable humidity of the power plant working environment, H max is the upper limit of the acceptable humidity of the power plant working environment, G max is the maximum acceptable gas concentration of the power plant working environment, and ω1, ω2 and ω3 are the weight factors of temperature, humidity and gas concentration respectively; When the comprehensive environment index E < the first environment index f1, the real-time status of environmental monitoring is evaluated as level 1 status, the power plant is currently in a normal working environment, start the equipment accident monitoring program, prepare for equipment accident monitoring, check the equipment operation status, and conduct real-time monitoring of the main equipment; When the comprehensive environment index E ≥ the first environment index f1, but the exceeding degree is less than 100%, the real-time status of environmental monitoring is evaluated as level 2 status, adjust the environmental parameters, and at the same time check the equipment operation situation, adjust the equipment parameters and indoor temperature and humidity, keep ventilation, reduce the gas concentration, recalculate the environment index after stabilization, conduct a secondary evaluation, if the real-time status of environmental monitoring in the secondary evaluation still remains at level 2 status, raise the evaluation result of the real-time status of environmental monitoring to level 3 status for processing, if the real-time status of environmental monitoring in the secondary evaluation returns to level 1 status, restore the normal operation status of the equipment and maintain normal operation; When the comprehensive environment index E ≥ the first environment index f1, but the exceeding degree is higher than 100%, the real-time status of environmental monitoring is evaluated as level 3. Start detailed inspection of equipment, adjust equipment working parameters, immediately adjust indoor temperature and humidity, air purification equipment, and emergency ventilation equipment, immediately operate the ventilation system and fire monitoring system, send out emergency evacuation notices and alarm alerts to evacuate staff, conduct equipment failure inspections, and immediately conduct a secondary evaluation. If the real-time status of environmental monitoring in the secondary evaluation is below level 2, reduce the equipment monitoring status, continuously monitor environmental parameters, and continue to start the ventilation system for level 2 status processing.

6. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 5, characterized in that: The equipment accident monitoring includes belt deviation monitoring, tearing monitoring, coal spillage monitoring, coal outburst monitoring, position monitoring of the plug board, coal arrival monitoring, outer turning monitoring of the belt skirt, and folding monitoring; monitor the equipment failure situation and start the equipment emergency response mechanism.

7. The intelligent safety monitoring method for power plant operation based on the Internet of Things according to claim 6, characterized in that: The start of the equipment emergency response mechanism includes When the equipment failure monitoring result is a belt deviation fault, start the automatic correction system, adjust the belt position to re-align it, send the specific deviation position information, and immediately alarm and notify the operation and maintenance personnel for handling; When the equipment failure monitoring result is a belt tearing fault, immediately trigger the shutdown mechanism to prevent further damage and danger, send a tearing fault alarm to the operation and maintenance personnel, and at the same time provide relevant images and data for remote diagnosis; When the equipment failure monitoring result is a coal spillage fault, start the cleaning system to clean the coal material, restore the conveying system, and adjust the conveying parameters according to the monitored coal spillage situation; When the equipment failure monitoring result is a coal outburst fault, immediately trigger the shutdown protection mechanism, stop the operation of relevant equipment, and at the same time trigger the fire fighting system preparation, send an emergency alarm notice, and provide the specific position of the coal outburst and the fire risk assessment; When the equipment failure monitoring result is an abnormal plug board fault, trigger the shutdown protection, perform manual reset or replace the abnormal plug board according to the specific situation to ensure the normal operation of the system, provide remote monitoring and guidance services, diagnose problems through the remote system and perform corresponding operations; When the equipment failure monitoring result is an abnormal coal arrival fault, when unauthorized materials are detected entering, trigger the shutdown protection and stop the operation of the conveying system, and notify the personnel for verification and handling; When the equipment failure monitoring result is an outer turning fault of the belt skirt, immediately trigger the shutdown mechanism, provide relevant images and data for diagnosis, and at the same time trigger the safety system; After the fault is resolved, the system automatically resets to ensure that the equipment smoothly returns to the normal operation state. Obtain the equipment status information through remote means, record and analyze each fault, form a fault report, and improve the algorithm and parameters of the monitoring system based on the fault analysis results.

8. An intelligent safety monitoring system for power plant operation based on the Internet of Things, based on the intelligent safety monitoring method for power plant operation based on the Internet of Things according to any one of claims 1 to 7, characterized in that: Including The acquisition module is used to deploy sensors in the power plant environment and collect monitoring data in real time through the sensors connected by the Internet of Things; The processing module is used to transmit the collected data to the central server through the Internet of Things for data processing, integrate the monitoring data, calculate the comprehensive environment index, and initially judge the environmental monitoring situation; The monitoring module is used to comprehensively judge the equipment failure situation based on the processed monitoring data, remotely monitor the equipment status, start the equipment emergency response mechanism, and conduct intelligent safety monitoring of the power plant operation.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the method for intelligent safety monitoring of power plant operation based on the Internet of Things according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the method for intelligent safety monitoring of power plant operation based on the Internet of Things according to any one of claims 1 to 7 are implemented.

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