Maintenance isolation locking early warning management system applied to high-voltage transformer substation

Abstract

The invention belongs to the technical field of high-voltage transformer substation maintenance management, and particularly relates to a maintenance isolation locking early warning management system applied to a high-voltage transformer substation, which comprises an intelligent sensing information acquisition module, a risk dynamic evaluation decision module, an isolation locking accurate execution module, an early warning information intelligent push module and a data comprehensive management module, according to the invention, various kinds of information in the transformer substation are comprehensively collected in real time through the intelligent perception information collection module, and the risk dynamic assessment decision module carries out deep analysis based on the real-time collected data information and formulates an isolation locking strategy and an early warning scheme. The isolation locking accurate execution module accurately controls isolation equipment and a locking device according to an isolation locking strategy, the early warning information intelligent pushing module timely and accurately pushes early warning information to related personnel according to an early warning scheme, and all the modules are closely associated and cooperatively work to form an efficient and intelligent maintenance management closed loop. And the safety and the high efficiency of the maintenance operation of the high-voltage transformer substation are comprehensively ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of maintenance management of high-voltage substations, and in particular to a maintenance isolation, lockout and early warning management system applied to high-voltage substations. Background Art

[0002] A high-voltage substation is a place where power systems of different voltage levels are connected and converted. It uses transformers and other equipment to step up or down the high-voltage electric energy to meet the needs of different users and transmission lines. High-voltage substations are key facilities in the power system, assuming important functions such as voltage conversion, power distribution, and transmission control. During maintenance work at high-voltage substations, ensuring effective isolation between the maintenance area and live equipment and preventing misoperation are key to protecting the lives of workers and the normal operation of equipment. Existing substation maintenance management methods often rely on manual operations and paper records, which can easily lead to safety accidents due to untimely information transmission, inadequate implementation of isolation measures, and imperfect early warning mechanisms. Furthermore, it is impossible to effectively monitor and track the maintenance isolation and lockout execution process and gradually determine the degree of maintenance hazards and data collection risks, which is not conducive to ensuring the safety and efficiency of high-voltage substation maintenance work. In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0003] The purpose of the present invention is to provide a maintenance isolation and lockout early warning management system applied to high-voltage substations, which solves the problem that the existing technology is prone to safety accidents due to untimely information transmission, inadequate implementation of isolation measures and imperfect early warning mechanism, and is unable to effectively monitor and track the maintenance isolation and lockout execution process and gradually judge the degree of maintenance hidden dangers and data collection risks, which is not conducive to ensuring the safety and efficiency of high-voltage substation maintenance.

[0004] To achieve the above object, the present invention provides the following technical solutions: The maintenance isolation and lockout early warning management system used in high-voltage substations includes an intelligent sensing information collection module, a dynamic risk assessment and decision-making module, an isolation and lockout precise execution module, an early warning information intelligent push module, and a data integrated management module. The intelligent sensing information collection module collects various data and information related to maintenance operations in the high-voltage substation in real time and transmits the collected data and information to the data integrated management module for storage. The risk dynamic assessment and decision-making module conducts in-depth analysis of the data information collected by the intelligent perception information acquisition module. Combined with the preset risk assessment model and rules, it dynamically assesses the risk level during the maintenance operation, formulates corresponding isolation and lockout strategies and early warning plans, and transmits them to the data integrated management module for storage; The isolation and locking precise execution module sends control instructions to the corresponding isolation equipment and locking devices according to the isolation and locking strategy, accurately controls the isolation equipment and locking devices in the high-voltage substation, and effectively isolates the maintenance area from the live equipment; the early warning information intelligent push module pushes the early warning information to relevant personnel in a timely and accurate manner according to the early warning plan formulated by the risk dynamic assessment decision module, and transmits the push records and feedback information to the data comprehensive management module for storage.

[0005] Furthermore, the intelligent sensing information collection module collects data information through various types of sensors deployed in the high-voltage substation, including voltage sensors, current sensors, temperature sensors, humidity sensors, infrared sensors, and personnel positioning sensors; Among them, voltage sensors and current sensors monitor the electrical parameters of the equipment in real time to determine whether the equipment is in a energized state; temperature sensors and humidity sensors monitor the ambient temperature and humidity; infrared sensors are used to detect whether the equipment has abnormal heating; and personnel positioning sensors track the location information of maintenance personnel in real time.

[0006] Furthermore, the operation process of the risk dynamic assessment decision module is as follows: The data integrated management module retrieves various data collected by the intelligent perception information collection module, pre-processes the retrieved data, removes noise and outliers, and quantitatively assesses the risks of maintenance operations based on a pre-set risk assessment indicator system; The current risk level is determined by comparing it with the preset risk threshold. Based on different risk levels, combined with the substation's topological structure and equipment characteristics, an intelligent algorithm is used to generate corresponding isolation and locking strategies. At the same time, a corresponding early warning plan is formulated to clarify the triggering conditions, warning levels, and warning methods of the warning.

[0007] Furthermore, after receiving the warning plan, the intelligent push module for early warning information selects the corresponding push method according to the warning level and warning object. For non-emergency warning information, it is released through the broadcasting system or display screen in the substation. For emergency warning information, it is directly pushed to the maintenance person in charge through SMS or mobile phone application; among them, the warning information includes warning content, warning level and response measures.

[0008] Furthermore, the early warning information intelligent push module is communicated with the isolation and lockout monitoring and tracking module. The isolation and lockout monitoring and tracking module monitors the status of the isolation equipment and the locking device in real time. If it is detected that the corresponding isolation equipment or locking device has an abnormal status execution, the abnormal information will be pushed to relevant personnel through the early warning information intelligent push module, and the abnormal information will be sent to the data comprehensive management module for storage.

[0009] Furthermore, the isolation and lockout monitoring and tracking module is communicated with the maintenance hidden danger output module. The isolation and lockout monitoring and tracking module sends the status monitoring and tracking information of all isolation equipment and locking devices involved in the high-voltage substation to the maintenance hidden danger output module. The maintenance hidden danger output module conducts a comprehensive analysis of the maintenance hidden dangers of the high-voltage substation, and generates a high maintenance hidden danger signal or a low maintenance hidden danger signal based on this, and pushes the high maintenance hidden danger signal to relevant personnel through the early warning information intelligent push module.

[0010] Furthermore, the specific analysis process of the troubleshooting output module includes: Obtain all isolation devices and locking devices involved in the high-voltage substation, mark the corresponding isolation devices or locking devices as attribute objects e, where e is a natural number greater than 1; obtain the interval between the current date and the production date of attribute object e and mark them as storage detection values, and use the current moment as the end moment and trace back to set a backtracking period of length L1, and the total number of state execution anomalies of attribute object e during the backtracking period and mark them as state abnormality values; And obtain all environmental parameters that affect the service life of the attribute object e, collect real-time data of all environmental parameters, and if there are environmental parameters whose real-time data does not meet the corresponding preset data requirements, then determine that the attribute object e is in a life-affecting state; obtain the total length of time that the attribute object e is in the life-affecting state in the historical stage and mark it as a performance degradation value; The attribute characteristic value is calculated by weighted summing the storage detection value, the state abnormality measurement value and the performance degradation measurement value. The attribute characteristic value is numerically compared with the corresponding preset attribute characteristic threshold. If the attribute characteristic value exceeds the corresponding preset attribute characteristic threshold, the attribute object e is marked as a dangerous object; if the high-voltage substation is involved in a dangerous object, a high-risk maintenance signal is generated; If the high-voltage substation does not involve any dangerous objects, the attribute characteristic value of the attribute object e is compared with the corresponding preset attribute characteristic threshold to obtain the attribute performance value, the attribute performance values ​​of all isolation equipment and locking devices involved in the high-voltage substation are averaged to obtain the isolation and lockout hidden danger value, and the isolation and lockout hidden danger value is numerically compared with the preset isolation and lockout hidden danger threshold. If the isolation and lockout hidden danger value exceeds the preset isolation and lockout hidden danger threshold, a high maintenance hidden danger signal is generated.

[0011] Furthermore, if the isolation and lockout hidden danger value does not exceed the preset isolation and lockout hidden danger threshold, all isolation and lockout strategies executed by the isolation and lockout precise execution module within the unit time are obtained, and the time difference between the time when the corresponding isolation and lockout strategy is completed and the time when the isolation and lockout strategy is received is calculated to obtain the isolation and lockout completion time value, and the proportion of the number of isolation and lockout completion time values ​​exceeding the preset isolation and lockout completion time threshold within the unit time is marked as the isolation and lockout completion value, and the average value and maximum value of all isolation and lockout completion time values ​​within the unit time are marked as the isolation and lockout time table value and the isolation and lockout time amplitude, respectively; The isolation and lockout completion evaluation value is obtained by weighted summing up the isolation and lockout completion value, the isolation and lockout time table value and the isolation and lockout time amplitude, and the isolation and lockout completion evaluation value is numerically compared with the preset isolation and lockout completion evaluation threshold. If the isolation and lockout completion evaluation value exceeds the preset isolation and lockout completion evaluation threshold, a high maintenance hidden danger signal is generated; if the isolation and lockout completion evaluation value does not exceed the preset isolation and lockout completion evaluation threshold, a low maintenance hidden danger signal is generated.

[0012] Furthermore, the maintenance hidden danger output module is communicatively connected to the collection risk output module, and the maintenance hidden danger output module sends the maintenance low hidden danger signal to the collection risk output module. When the collection risk output module receives the maintenance low hidden danger signal, it analyzes the data collection performance of the intelligent perception information collection module, generates a normal collection signal or a collection risk signal through analysis, and pushes the collection risk signal to relevant personnel through the early warning information intelligent push module.

[0013] Furthermore, the specific operation process of the risk collection output module is as follows: Obtain all sensors involved in the intelligent perception information collection module, calculate the number of occurrences of monitoring data collected by the corresponding sensor in a unit time that is not within the corresponding preset reasonable data range and compare it with the total number of collection times of the corresponding sensor in the unit time to obtain the unreasonable collection value; The interval between two adjacent acquisition moments of the corresponding sensor is marked as the first duration, the deviation value of the first duration compared to the corresponding preset standard first duration is marked as the time deviation characteristic value, the proportion of the number of time deviation characteristic values ​​exceeding the preset time deviation characteristic threshold is marked as the time deviation anomaly detection value, and the time deviation performance value is obtained by averaging all the time deviation characteristic values; The acquisition comprehensive coefficient is calculated by weighted summation of the acquisition unreasonable value, the time deviation anomaly detection value and the time deviation performance value, and the acquisition comprehensive coefficient is numerically compared with the corresponding preset acquisition comprehensive coefficient threshold. If the acquisition comprehensive coefficient exceeds the preset acquisition comprehensive coefficient threshold, the corresponding sensor is marked as an obstruction; if there is an obstruction in the intelligent perception information acquisition module, an acquisition risk signal is generated; if there is no obstruction in the intelligent perception information acquisition module, a normal acquisition signal is generated.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, the risk dynamic assessment and decision-making module conducts in-depth analysis based on real-time collected data information and formulates isolation and lockout strategies and early warning plans. The isolation and lockout precision execution module accurately controls the isolation equipment and locking devices according to the isolation and lockout strategies. The early warning information intelligent push module pushes early warning information to relevant personnel in a timely and accurate manner according to the early warning plan. The modules are closely linked and work together to comprehensively ensure the safety and efficiency of high-voltage substation maintenance operations. 2. In the present invention, the maintenance hidden dangers of the high-voltage substation are comprehensively analyzed through the maintenance hidden danger output module, and the operation monitoring and control of the isolation and locking execution process are strengthened when the maintenance high hidden danger signal is generated, which significantly reduces the maintenance hidden dangers of the high-voltage substation. When the maintenance low hidden danger signal is generated, the data collection performance is analyzed, and when the collection risk signal is generated, the supervision of the data collection process is strengthened to ensure the timeliness and accuracy of the transmitted data information, thereby further improving the maintenance safety of the high-voltage substation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] Example 1: Figure 1 As shown, the maintenance isolation and lockout early warning management system proposed by the present invention for high-voltage substations includes an intelligent perception information acquisition module, a risk dynamic assessment and decision-making module, an isolation and lockout precise execution module, an early warning information intelligent push module, and a data comprehensive management module; The intelligent sensing information acquisition module collects various data and information related to maintenance work in the high-voltage substation in real time, including equipment status, environmental parameters, personnel location, etc., and transmits the collected data and information to the data integrated management module for storage. By comprehensively and real-timely collecting various information in the substation, it can promptly detect equipment anomalies and environmental changes, provide accurate data support for subsequent risk assessment, and help take measures in advance to avoid accidents. Specifically, the intelligent sensing information acquisition module collects data information through various types of sensors deployed in the high-voltage substation, such as voltage sensors, current sensors, temperature sensors, humidity sensors, infrared sensors, and personnel positioning sensors; Among them, voltage sensors and current sensors monitor the electrical parameters of the equipment in real time to determine whether the equipment is in a energized state; temperature sensors and humidity sensors monitor ambient temperature and humidity to prevent environmental factors from affecting equipment performance and personnel safety; infrared sensors are used to detect whether the equipment has abnormal heating and promptly discover potential fault hazards; personnel positioning sensors track the location information of maintenance personnel in real time to ensure that personnel are active in a safe working area.

[0018] The risk dynamic assessment and decision-making module conducts in-depth analysis of the data information collected by the intelligent perception information collection module. Combined with the preset risk assessment model and rules, it dynamically assesses the risk level during the maintenance operation, formulates corresponding isolation and lockout strategies and early warning plans, and transmits them to the data integrated management module for storage. It can dynamically assess the risks of maintenance operations based on real-time collected data, formulate scientific and reasonable isolation and lockout strategies and early warning plans, improve the safety and pertinence of maintenance operations, and avoid safety accidents caused by blind operations. The operation process of the risk dynamic assessment and decision-making module is as follows: The data integrated management module retrieves various data collected by the intelligent sensing information acquisition module, pre-processes the retrieved data to remove noise and outliers, and quantitatively assesses the risk of maintenance operations based on a pre-set risk assessment indicator system, such as the equipment's energized state, environmental severity, and the distance personnel are close to hazardous areas. The current risk level is determined by comparing it with the pre-set risk threshold. Based on different risk levels, combined with the substation's topological structure and equipment characteristics, intelligent algorithms are used to generate corresponding isolation and locking strategies, such as determining the equipment that needs to be isolated, the switches and circuit breakers that need to be locked, etc. At the same time, corresponding early warning plans are formulated to clarify the triggering conditions, warning levels and warning methods of the warning.

[0019] The isolation and locking precision execution module sends control instructions to the corresponding isolation equipment and locking devices according to the isolation and locking strategy, accurately controlling the isolation equipment and locking devices in the high-voltage substation (for example, controlling the circuit breaker to open and the disconnector to pull out), effectively isolating the maintenance area from the live equipment. It can accurately execute the isolation and locking operation, ensure the reliable isolation of the maintenance area from the live equipment, effectively prevent misoperation, and protect the personal safety of maintenance personnel and the normal operation of equipment.

[0020] The early warning information intelligent push module pushes the early warning information to relevant personnel in a timely and accurate manner according to the early warning plan formulated by the risk dynamic assessment and decision-making module, thereby improving the emergency response speed and reducing accident losses, and transmits the push records and feedback information to the data comprehensive management module for storage.

[0021] It should be noted that after receiving the warning plan, the early warning information intelligent push module selects the corresponding push method according to the warning level and warning object. For non-emergency warning information, it is released through the broadcasting system or display screen in the substation. For emergency warning information, it is directly pushed to the maintenance person in charge through SMS or mobile phone application. Among them, the warning information includes warning content, warning level and response measures, etc., to ensure that relevant personnel can understand the situation in a timely manner and take corresponding actions.

[0022] Example 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the early warning information intelligent push module is communicatively connected to the isolation and locking monitoring and tracking module, and the isolation and locking monitoring and tracking module monitors the status of the isolation equipment and the locking device in real time. If it is detected that the corresponding isolation equipment or the locking device has a status execution abnormality, the early warning information intelligent push module pushes the abnormal information to the relevant personnel, and sends the abnormal information to the data integrated management module for storage, so as to realize the status monitoring and tracking of the isolation equipment and the locking device and the abnormal identification output, so as to take corresponding processing measures to reduce the operation risk of the isolation equipment and the locking device.

[0023] Furthermore, the isolation and locking monitoring and tracking module is connected to the maintenance hidden danger output module in communication. The isolation and locking monitoring and tracking module sends the status monitoring and tracking information of all isolation equipment and locking devices involved in the high-voltage substation to the maintenance hidden danger output module. The maintenance hidden danger output module conducts a comprehensive analysis of the maintenance hidden dangers of the high-voltage substation and generates a maintenance high hidden danger signal or a maintenance low hidden danger signal accordingly. The high-risk maintenance signal is pushed to relevant personnel through the early warning information intelligent push module to remind them to promptly inspect, repair or replace the corresponding isolation equipment or locking devices, and strengthen the operation monitoring and control of the isolation and locking execution process, significantly reducing the maintenance risks of high-voltage substations. The intelligent level is high and the supervision difficulty is small. The specific analysis process of the maintenance hidden danger output module is as follows: Obtain all isolation devices and locking devices involved in the high-voltage substation, mark the corresponding isolation devices or locking devices as attribute objects e, where e is a natural number greater than 1; obtain the interval between the current date and the production date of attribute object e and mark them as storage detection values, and use the current moment as the end moment and trace back to set a backtracking period of L1, preferably, L1 is thirty days; the total number of state execution anomalies of attribute object e during the backtracking period is marked as the state abnormality value; And obtain all environmental parameters that affect the service life of the attribute object e, collect real-time data of all environmental parameters, and if there are environmental parameters whose real-time data does not meet the corresponding preset data requirements, then determine that the attribute object e is in a life-affecting state; obtain the total length of time that the attribute object e is in the life-affecting state in the historical stage and mark it as a performance degradation value; The attribute characteristic value is calculated by performing a weighted summation of the storage detection value, the state abnormality measurement value, and the performance degradation measurement value; that is, the storage detection value, the state abnormality measurement value, and the performance degradation measurement value are respectively assigned corresponding preset weight coefficients, and the storage detection value, the state abnormality measurement value, and the performance degradation measurement value are respectively multiplied by the corresponding preset weight coefficients, and the sum of the three sets of product results is marked as the attribute characteristic value; it should be noted that the larger the value of the attribute characteristic value, the higher the overall usage risk of the attribute object e; Compare the attribute feature value with the corresponding preset attribute feature threshold. If the attribute feature value exceeds the corresponding preset attribute feature threshold, it indicates that the overall use risk of the attribute object e is high, and the attribute object e is marked as a dangerous object. If the high-voltage substation is involved in a dangerous object, it indicates that there is a high safety hazard in the maintenance of the high-voltage substation, and a high maintenance hazard signal is generated. If the high-voltage substation does not involve any dangerous objects, the attribute characteristic value of the attribute object e is compared with the corresponding preset attribute characteristic threshold to obtain the attribute performance value, the attribute performance values ​​of all isolation equipment and locking devices involved in the high-voltage substation are averaged to obtain the isolation and lockout hidden danger value, and the isolation and lockout hidden danger value is numerically compared with the preset isolation and lockout hidden danger threshold. If the isolation and lockout hidden danger value exceeds the preset isolation and lockout hidden danger threshold, it indicates that the safety hazard of the high-voltage substation maintenance is relatively high, and a high maintenance hidden danger signal is generated.

[0024] Furthermore, if the isolation and lockout hidden danger value does not exceed the preset isolation and lockout hidden danger threshold, all isolation and lockout strategies executed by the isolation and lockout precise execution module within the unit time are obtained, and the time difference between the time when the corresponding isolation and lockout strategy is completed and the time when the isolation and lockout strategy is received is calculated to obtain the isolation and lockout completion time value, and the proportion of the number of isolation and lockout completion time values ​​exceeding the preset isolation and lockout completion time threshold within the unit time is marked as the isolation and lockout completion value, and the average value and maximum value of all isolation and lockout completion time values ​​within the unit time are marked as the isolation and lockout time table value and the isolation and lockout time amplitude, respectively; The isolation and lockout completion evaluation value is calculated by weighted summing the isolation and lockout completion difference value, the isolation and lockout time table value, and the isolation and lockout time amplitude; that is, the isolation and lockout completion difference value, the isolation and lockout time table value, and the isolation and lockout time amplitude are respectively assigned corresponding preset weight coefficients, and the isolation and lockout completion difference value, the isolation and lockout time table value, and the isolation and lockout time amplitude are respectively multiplied by the corresponding preset weight coefficients, and the sum of the three sets of product results is marked as the isolation and lockout completion evaluation value; it should be noted that the larger the value of the isolation and lockout completion evaluation value, the worse the overall execution efficiency performance of the isolation and lockout operation per unit time; The isolation and lockout completion evaluation value is numerically compared with the preset isolation and lockout completion evaluation threshold. If the isolation and lockout completion evaluation value exceeds the preset isolation and lockout completion evaluation threshold, it indicates that the execution efficiency of the isolation and lockout operation per unit time is generally poor, and there is a high safety hazard in the high-voltage substation maintenance site, and a high maintenance hazard signal is generated; if the isolation and lockout completion evaluation value does not exceed the preset isolation and lockout completion evaluation threshold, it indicates that the safety hazard in the high-voltage substation maintenance site is generally low, and a low maintenance hazard signal is generated.

[0025] Example 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the maintenance hidden danger output module is communicatively connected to the acquisition risk output module. The maintenance hidden danger output module sends a maintenance low hidden danger signal to the acquisition risk output module. When the acquisition risk output module receives the maintenance low hidden danger signal, it analyzes the data acquisition performance of the intelligent perception information acquisition module and generates a normal acquisition signal or an acquisition risk signal through the analysis. The collected risk signals are pushed to relevant personnel through the early warning information intelligent push module to remind them to inspect, repair or replace the corresponding sensors, strengthen the supervision of the data collection process, ensure the timeliness and accuracy of the transmitted data information, and help avoid adverse effects on the subsequent risk assessment process and isolation and lockout execution process, and further improve the safety of high-voltage substation maintenance. The specific operation process of the collection risk output module is as follows: Obtain all sensors involved in the intelligent perception information collection module, calculate the number of times the monitoring data collected by the corresponding sensor per unit time is not within the corresponding preset reasonable data range (i.e., the corresponding monitoring data is obviously wrong), and compare it with the total number of collection times of the corresponding sensor per unit time to obtain the unreasonable collection value; The interval between two adjacent acquisition moments of the corresponding sensor is marked as the first duration, and the deviation value of the first duration compared to the corresponding preset standard first duration is marked as the time deviation characteristic value. When the value of the time deviation characteristic value is too large, it indicates that the acquisition interval is too long or too short, and the acquisition time is inaccurate; the proportion of the number of time deviation characteristic values ​​that exceed the preset time deviation characteristic threshold is marked as the time deviation anomaly detection value, and the time deviation performance value is obtained by calculating the average of all time deviation characteristic values; The acquisition comprehensive coefficient is calculated by taking a weighted sum of the acquisition unreasonable value, the time deviation anomaly detection value, and the time deviation performance value. That is, the acquisition unreasonable value, the time deviation anomaly detection value, and the time deviation performance value are each assigned a corresponding preset weight coefficient, and the acquisition unreasonable value, the time deviation anomaly detection value, and the time deviation performance value are multiplied by the corresponding preset weight coefficient, and the sum of the three sets of product results is marked as the acquisition comprehensive coefficient. It should be noted that the larger the value of the acquisition comprehensive coefficient, the worse the acquisition operation performance of the corresponding sensor per unit time. The acquisition comprehensive coefficient is numerically compared with the corresponding preset acquisition comprehensive coefficient threshold. If the acquisition comprehensive coefficient exceeds the preset acquisition comprehensive coefficient threshold, it indicates that the acquisition operation performance of the corresponding sensor per unit time is generally poor, and the corresponding sensor is marked as an obstructor; if there is an obstructor in the intelligent perception information acquisition module, it indicates that the acquisition risk of the intelligent perception information acquisition module is high, and it is difficult to ensure the timeliness and accuracy of the transmitted data information, and an acquisition risk signal is generated; if there is no obstructor in the intelligent perception information acquisition module, it indicates that the acquisition risk of the intelligent perception information acquisition module is low, which is conducive to ensuring the timeliness and accuracy of the transmitted data information, and an acquisition normal signal is generated.

[0026] The working principle of the present invention: When in use, various types of information in the substation are collected comprehensively and in real time through the intelligent perception information collection module. The risk dynamic assessment decision module conducts in-depth analysis based on the real-time collected data information, and formulates isolation and locking strategies and early warning plans, so that the safety protection of maintenance operations is more targeted and scientific, and effectively prevents safety accidents caused by blind operation. The isolation and locking precision execution module accurately controls the isolation equipment and locking devices according to the isolation and locking strategy to ensure that the maintenance area is reliably isolated from the live equipment to prevent misoperation and ensure the safety of maintenance personnel and equipment. The early warning information intelligent push module pushes the early warning information to relevant personnel in a timely and accurate manner according to the early warning plan, which improves the emergency response speed and enables relevant personnel to quickly take countermeasures to reduce accident losses. The modules are closely linked and work together to form an efficient and intelligent maintenance management closed loop, from data collection to risk assessment, isolation and locking execution to early warning push, to comprehensively guarantee the safety and efficiency of high-voltage substation maintenance operations.

[0027] The thresholds, preset values, preset ranges, etc. in the technical solution of the present invention are set for result comparison and analysis in order to determine whether they are good or bad. As for their size, they are set for entry and storage based on a combination of large-scale model analysis of sample data and manual experience, and can also be appropriately adjusted based on seasonal or common-sense influencing conditions. As for the settings of preset weight coefficients, influencing factors, etc., specific numerical values ​​are assigned based on the influence of each parameter on the result, ultimately reflecting the influence on the result. They are also set for entry and storage based on a combination of large-scale model analysis of sample data and manual experience, and can also be appropriately adjusted based on seasonal or common-sense influencing conditions.

[0028] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. The preferred embodiments do not describe all details in detail, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention and enable those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The maintenance isolation and lockout early warning management system used in high-voltage substations is characterized by: It includes an intelligent perception information collection module, a risk dynamic assessment and decision-making module, an isolation and locking precise execution module, an early warning information intelligent push module, and a data comprehensive management module. The intelligent perception information collection module collects various data and information related to maintenance operations in the high-voltage substation in real time, and transmits the collected data and information to the data comprehensive management module for storage in real time. The risk dynamic assessment and decision-making module conducts in-depth analysis of the data information collected by the intelligent perception information acquisition module. Combined with the preset risk assessment model and rules, it dynamically assesses the risk level during the maintenance operation, formulates corresponding isolation and lockout strategies and early warning plans, and transmits them to the data integrated management module for storage; The isolation and locking precise execution module sends control instructions to the corresponding isolation equipment and locking devices according to the isolation and locking strategy, and accurately controls the isolation equipment and locking devices in the high-voltage substation; the early warning information intelligent push module pushes the early warning information to relevant personnel according to the early warning plan formulated by the risk dynamic assessment decision module, and transmits the push records and feedback information to the data comprehensive management module for storage.

2. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 1 is characterized in that: The intelligent sensing information acquisition module collects data information through various types of sensors deployed in the high-voltage substation, including voltage sensors, current sensors, temperature sensors, humidity sensors, infrared sensors, and personnel positioning sensors.

3. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 1 is characterized in that: The operation process of the risk dynamic assessment decision module is as follows: The data integrated management module retrieves various data collected by the intelligent perception information collection module, pre-processes the retrieved data, removes noise and outliers, and quantitatively assesses the risks of maintenance operations based on a pre-set risk assessment indicator system; Determine the current risk level by comparing it with the preset risk threshold; According to different risk levels, combined with the substation's topological structure and equipment characteristics, intelligent algorithms are used to generate corresponding isolation and locking strategies. At the same time, corresponding early warning plans are formulated to clarify the triggering conditions, warning levels and warning methods of the warning.

4. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 1 is characterized in that: After receiving the warning plan, the warning information intelligent push module selects the corresponding push method according to the warning level and warning object; among them, the warning information includes warning content, warning level and response measures.

5. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 1 is characterized in that: The early warning information intelligent push module is communicated with the isolation and lockout monitoring and tracking module. The isolation and lockout monitoring and tracking module monitors the status of the isolation equipment and the locking device in real time. If an abnormal status is detected in the corresponding isolation equipment or the locking device, the abnormal information will be pushed to the relevant personnel through the early warning information intelligent push module.

6. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 5 is characterized in that: The isolation lockout monitoring and tracking module is communicated with the maintenance hidden danger output module. The maintenance hidden danger output module conducts a comprehensive analysis of the maintenance hidden dangers of the high-voltage substation, and generates a high maintenance hidden danger signal or a low maintenance hidden danger signal accordingly, and pushes the high maintenance hidden danger signal to relevant personnel through the early warning information intelligent push module.

7. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 6 is characterized in that: The specific analysis process of the maintenance hidden danger output module is as follows: obtain all the isolation equipment and locking devices involved in the high-voltage substation, mark the corresponding isolation equipment or locking device as the attribute object e, and e is a natural number greater than 1; calculate the attribute characteristic value by weighted summing the storage detection value, the state abnormality value and the performance degradation value. If the attribute characteristic value exceeds the corresponding preset attribute characteristic threshold, the attribute object e is marked as a dangerous object; if the high-voltage substation involves a dangerous object, a maintenance high hidden danger signal is generated; if the high-voltage substation does not involve a dangerous object, the isolation and lockout hidden danger value is compared with the preset isolation and lockout hidden danger threshold, otherwise a maintenance high hidden danger signal is generated.

8. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 7 is characterized in that: If the isolation and lockout hazard value does not exceed the preset isolation and lockout hazard threshold, the isolation and lockout completion evaluation value is calculated by weighted summing the isolation and lockout completion value, the isolation and lockout time table value and the isolation and lockout time amplitude. If the isolation and lockout completion evaluation value exceeds the preset isolation and lockout completion evaluation threshold, a high maintenance hazard signal is generated; otherwise, a low maintenance hazard signal is generated.

9. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 6 is characterized in that: The maintenance hidden danger output module is communicated with the collection risk output module. When the collection risk output module receives the maintenance low hidden danger signal, it analyzes the data collection performance of the intelligent perception information collection module, generates a normal collection signal or a collection risk signal through the analysis, and pushes the collection risk signal to relevant personnel through the early warning information intelligent push module.

10. The maintenance isolation and lockout early warning management system for high-voltage substations according to claim 9 is characterized in that: The specific operation process of the collection risk output module is as follows: All sensors involved in the intelligent perception information acquisition module are obtained, and the acquisition comprehensive coefficient is calculated by weighted summation of the acquisition unreasonable value, time deviation anomaly detection value and time deviation performance value. If the acquisition comprehensive coefficient exceeds the preset acquisition comprehensive coefficient threshold, the corresponding sensor is marked as an obstruction; if there is an obstruction in the intelligent perception information acquisition module, an acquisition risk signal is generated; otherwise, a acquisition normal signal is generated.

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