Intelligent monitoring system of transformer substation channel cover plate based on Internet of Things

Abstract

The invention discloses an intelligent monitoring system for a transformer substation channel cover plate based on the Internet of Things, and relates to the technical field of transformer substations. The acquisition monitoring module is used for acquiring environment and state data of the channel cover plate in real time; the acquisition monitoring module is also used for converting the environment and state data of the channel cover plate into a transmission format; the network connection module is used for receiving the environment and state data of the channel cover plate after the transmission format is converted by the acquisition monitoring module; interconnection, intercommunication and remote management of equipment and sensors are achieved through the Internet of Things technology, and collection and transmission of the state, temperature, humidity and other data of the trench cover plate are achieved through the sensors. Data transmission and remote management between intelligent devices are realized, and finally data acquired by a sensor is processed and analyzed, so that state prediction and maintenance plan making are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of substations, and more specifically, to an intelligent monitoring system for trench covers of substations based on the Internet of Things. Background Art

[0002] With the rapid development of the national economy and the acceleration of urbanization, urban construction requires a large amount of power supply, and the core of power supply is substation. As an important part of the power system, substation plays an important role in the power system. With the further advancement of urbanization, the number and distribution range of substations are also expanding, and the number of substation trench covers is also increasing. The safety and reliability of substation trench covers are crucial to the normal operation of the power system; Traditional covers are mostly made of cement, iron sheets, aluminum alloys and other materials, which only have basic rainproof functions, but are easy to break, rust, heavy and other problems. With the development of technology, smart trench covers have begun to integrate a variety of sensors and communication equipment, which can realize real-time monitoring and remote control of the trench cover status, such as monitoring of parameters such as temperature, humidity, water level, and automatically opening ventilation and drainage functions; However, in actual use, the data collection of trench cover monitoring is incomplete, the monitoring is not timely, the management efficiency is low, and the safety risks are high. Summary of the invention

[0003] In order to solve the above problems, the present invention provides an intelligent monitoring system for substation trench covers based on the Internet of Things.

[0004] An intelligent monitoring system for a trench cover plate of a substation based on the Internet of Things includes a collection and monitoring module, which is used to collect environmental and status data of the trench cover plate in real time: The acquisition monitoring module is also used to convert the environment and status data of the channel cover plate into a transmission format; A network connection module and an application module, wherein the network connection module is used to receive the environment and status data of the channel cover plate after the acquisition and monitoring module converts the transmission format, and the network connection module transmits the received data of the acquisition and monitoring module to the application module; The application module includes a monitoring unit and a remote control unit, wherein the monitoring unit is used to monitor the channel cover plate in real time according to the data transmitted by the network connection module, determine whether the channel cover plate has any abnormality, and if so, transmit a control signal to the remote control unit; The remote control unit is used to remotely control the channel cover plate according to the control signal of the monitoring unit.

[0005] Preferably, the acquisition and monitoring module is also used to perform multimodal fusion on the collected environment and status data of the channel cover plate, specifically: Preprocess the data collected by each sensor; A fusion cycle is preset. At the beginning of the cycle, an initial state estimation value of the cycle is set for each sensor based on the data collected by each sensor for the first time. The estimated value of the initial state of the period is,set the fusion period as one week.,Week 1, Monday: each sensor collected data for the first time, as follows; If the temperature sensor reading is within the normal range, the status estimate is 1; If the humidity sensor reading is within the normal range, the status estimate is 1; If the pressure sensor reading is within the normal range, the state estimation value is 1; If the water level sensor reading is within the normal range, the state estimation value is 1; Week 1, Sunday: After collecting a week’s worth of data, we get an estimate of the current state based on each sensor’s parameters. The state estimates for all sensors are still 1 because they are still within the normal range; The current state estimation values ​​of all sensors are superimposed to obtain the total state value of the channel cover plate; Total status value = 1+1+1+1=4; The total status value is 4, indicating that the channel cover status of the entire system is normal; At the end of the first week, the fusion cycle ends and the total state value is 4; Week 2, Monday: Start a new fusion cycle and repeat the above steps; Obtain a current state estimation value according to the parameters of each sensor in the previous time period, and the current state estimation value is assigned in the same manner as the initial state estimation value; The current state estimation values ​​of all sensors are superimposed to obtain the total state value of the channel cover, end the fusion cycle, and start the next fusion cycle.

[0006] Preferably, the specific working method of the acquisition monitoring module also includes: The collected total status data is processed through a hash algorithm to generate a unique data fingerprint; the generated data fingerprint is stored on the blockchain; Implement end-to-end encryption to ensure that only the sender and receiver of the data can access the data content, and use the key management system based on the SM9 identification cryptographic algorithm to provide end-to-end security authentication for data transmission.

[0007] Preferably, the specific working mode of the network connection module is as follows: Obtain the historical mean of the data transmitted by the network connection module and historical standard deviation ; According to the formula , calculate and obtain the initial threshold value of the data transmitted by the acquisition monitoring module , where k is the adjustment coefficient; If the data currently transmitted by the network connection module exceeds the initial threshold , then increase the data transmission priority and transmission frequency, otherwise, transmit data at the normal frequency.

[0008] Preferably, the network connection module further comprises an adjustment unit, which is used to adjust the initial threshold of the data transmitted by the acquisition and monitoring module in real time. Make adjustments, specifically: An adjustment interval time is set in advance, and during each adjustment time, the current mean value of the data transmitted by the acquisition monitoring module is calculated. and the current standard deviation ; According to the formula , calculate and obtain the adjusted threshold ; After adjusting the gap time, if the data currently transmitted by the network connection module exceeds the initial threshold , then increase the data transmission priority and transmission frequency, otherwise, transmit data at the normal frequency.

[0009] Preferably, the specific working mode of the monitoring unit is as follows: Determining whether the channel cover plate is abnormal by using the total current state obtained by the acquisition monitoring module; The specific method for judging whether there is an abnormality in the channel cover is: If the total status value is greater than 4: it means the system is running normally; The total status value is 4, which means that 4 types of sensors are in normal status and the system can continue to operate normally temporarily; for example, the temperature sensor, humidity sensor, water level sensor, and pressure sensor are in normal status; Even if the total status value is 4, if the pressure sensor status is 0, it is judged to be abnormal; If the total status value is 2 or 3, further diagnosis and examination are required; If the total status value is 2, it means that 2 types of sensors are in normal status. It may be necessary to check the other 3 types of sensors and perform corresponding maintenance on the channel cover according to the parameters detected by the other 3 types of sensors. For sensors with a status of 0, prioritize them, check key sensors first, and perform corresponding maintenance on the channel cover according to the corresponding parameters. Sensor-specific priorities are obtained based on sensor importance, failure history, failure impact, and maintenance cost; If the total status value is 1 or 0, it is judged that there is an abnormality and immediate action is required; If the total status value is only 1, it means that only one sensor is in normal condition, which may mean that there is a serious problem with the system and requires urgent inspection and repair; If there is an abnormality, an early warning is triggered immediately and an early warning signal is generated; The monitoring unit is also used to dynamically adjust the sampling frequency of the sensor according to the real-time monitoring results.

[0010] Preferably, the specific working method of dynamically adjusting the sampling frequency of the sensor is as follows: Obtain the initial sampling frequency C1 of each sensor; Obtain the mean and standard deviation of the current parameters collected by each sensor, obtain the coefficient of variation X by dividing the mean by the standard deviation, and obtain the incremental factor Z of the sampling frequency based on the coefficient of variation; According to the formula , get the adjusted sampling frequency , and transmitted to the remote control unit to adjust each sensor.

[0011] Preferably, the specific working mode of the remote control unit is as follows: Write control logic according to the operation rules and safety requirements of the channel cover; After the monitoring unit sends the warning signal, the corresponding control logic is executed according to the abnormal state value in the acquisition monitoring module.

[0012] Preferably, the specific working mode of the remote control unit also includes: Obtain weather information from weather forecasts, and mark events above orange warning as extreme events; In extreme cases, the remote control unit can automatically close or lock the cover to prevent further damage.

[0013] Preferably, the specific working method of the network connection module also includes: Determining the transmission distance of the network connection module; Dynamically adjust bandwidth allocation based on transmission distance and network conditions.

[0014] Beneficial effects: Through the Internet of Things technology, the interconnection and remote management of equipment and sensors are realized, and the data such as the status, temperature, and humidity of the trench cover are collected and transmitted through sensors. By realizing data transmission and remote management between smart devices, the data collected by the sensors are finally processed and analyzed to realize status prediction and maintenance plan formulation. Intelligent monitoring and management of the trench cover of the substation can be realized, and safety, stability and reliability can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the intelligent monitoring system of the present invention. DETAILED DESCRIPTION

[0016] like Figure 1 As shown: An intelligent monitoring system for trench cover plates of a substation based on the Internet of Things, including a collection monitoring module, the collection monitoring module is used to collect the environment and status data of the trench cover plates in real time: It should be noted that, in this embodiment, the environment and status data of the trench cover plates include the temperature, humidity, water level, pressure in the trench cover plates and the opening and closing status of the trench cover plates, which are specifically obtained through temperature sensors, humidity sensors, water level sensors, pressure sensors, status monitoring sensors (such as opening and closing status), etc.; In this embodiment, special sensors such as SF6 gas density monitoring and partial discharge monitoring can also be added to meet the unique monitoring needs of the substation; The acquisition monitoring module is also used to convert the environment and status data of the channel cover plate into a transmission format; convert the digital signal into data in a specific format, such as JSON, XML, etc., which are suitable for network transmission and can be parsed by the upper system; A network connection module and an application module, wherein the network connection module is used to receive the environment and status data of the channel cover plate after the acquisition and monitoring module converts the transmission format, and the network connection module transmits the received data of the acquisition and monitoring module to the application module; The application module includes a monitoring unit and a remote control unit, wherein the monitoring unit is used to monitor the channel cover plate in real time according to the data transmitted by the network connection module, determine whether the channel cover plate has any abnormality, and if so, transmit a control signal to the remote control unit; The remote control unit is used to remotely control the channel cover plate according to the control signal of the monitoring unit; Through the Internet of Things technology, the interconnection and remote management of equipment and sensors can be realized. Through sensors, the data such as the status, temperature, and humidity of the trench cover can be collected and transmitted. By realizing data transmission and remote management between smart devices, the data collected by the sensors can be processed and analyzed, and status prediction and maintenance plan formulation can be realized. This can realize intelligent monitoring and management of the trench cover of the substation and improve safety, stability and reliability.

[0017] As an optional embodiment: the acquisition monitoring module is also used to perform multimodal fusion on the collected environment and status data of the channel cover, specifically: it should be noted that the monitoring of the channel cover of the substation needs to adapt to special environments such as strong electromagnetic interference and large humidity changes. Conventional sensors will be affected by the environment. This technical solution combines different types of sensor data through multimodal data fusion to provide a more comprehensive monitoring perspective and reduce the data deviation that may be caused by a single sensor; Preprocess the data collected by each sensor; this includes filtering, normalization, and scaling to ensure that the data is on the same scale; A fusion cycle is preset. At the beginning of the cycle, an initial state estimation value of the cycle is set for each sensor based on the data collected by each sensor for the first time. It should be noted that in this embodiment, a value can be assigned to the state of each sensor, and the specific value is 0 or 1. If the sensor parameter is within the preset normal range, it is 1, otherwise, it is 0, which provides a starting point for the filter, that is, the best guess of the system state before there is actual measurement data. In this embodiment, the cycle time is set by the staff; For example, the staff set the fusion cycle to one week. On Monday of Week 1, each sensor collected data for the first time.

[0018] Temperature sensor reading: 22°C (normal range: 20°C-25°C), state estimate value is 1; Humidity sensor reading: 45% (normal range: 40% to 50%), state estimation value is 1; Pressure sensor reading: 1.01 (normal range: 1.00-1.02), state estimate value is 1; Water level sensor reading: 12cm, (normal range: 10cm-20cm) state estimation value is 1; All sensors have a state estimate of 1 because they are within normal range; Week 1, Sunday: After collecting a week’s worth of data, we get an estimate of the current state based on each sensor’s parameters. Temperature sensor reading: 24°C, state estimate value 1; Humidity sensor reading: 48%, state estimate value is 1; Pressure sensor reading: 1.02, state estimate value is 1; Water level sensor reading: 12cm, state estimate value is 1; The state estimates for all sensors are still 1 because they are still within the normal range; The current state estimation values ​​of all sensors are superimposed to obtain the total state value of the channel cover plate; Total status value = 1+1+1+1=4; The total status value is 4, indicating that the channel cover status of the entire system is normal; At the end of the first week, the fusion cycle ends and the total state value is 4; Week 2, Monday: Start a new fusion cycle and repeat the above steps; The current state estimation value is obtained according to the parameter of each sensor in the previous time period; it should be noted that, in this embodiment, the current state estimation value is assigned in the same manner as the initial state estimation value, that is, if the sensor reading is within the normal range, the current state estimation value of the parameter is 1; The total state value of the channel cover is obtained by superimposing the current state estimation values ​​of all sensors, ending the fusion cycle and starting the next fusion cycle. In this embodiment, for example, if the current state values ​​of the temperature sensor, humidity sensor, water level sensor, pressure sensor and state monitoring sensor in this embodiment are 1, 0, 1, 1 and 1 respectively, the total state value obtained by superposition is 4, which can roughly obtain the degree of proximity between all sensor parameters and the preset standard values, and the total current state of the channel cover is obtained through this; The total current state provides a comprehensive view that integrates information from multiple sensors, allowing operators to make more accurate decisions based on more comprehensive data. Even if some sensors fail or provide inaccurate data, the system can still provide reliable state estimates by fusing data from multiple sensors. For critical infrastructure such as substations, accurate condition monitoring helps to promptly detect safety hazards, such as illegal opening of channel covers, internal water accumulation or gas leakage, so that preventive measures can be taken to avoid possible power accidents; For example: in a substation, the trench cover is equipped with a variety of sensors, including temperature sensors, humidity sensors, water level sensors, pressure sensors, and status monitoring sensors (such as opening and closing status); Temperature sensors may indicate abnormally high temperatures in the trench, which may be caused by overheating of internal equipment. Humidity sensors may indicate that humidity in the trench exceeds a safe threshold, which may cause corrosion or short circuits in electrical equipment. Water level sensors may detect water accumulation in the trench, which may affect the operation of the equipment and increase the risk of electric shock. Pressure sensors may indicate that the cover is under abnormal pressure, which may be caused by external loads or internal pressure buildup. Condition monitoring sensors may indicate that the cover is not closed properly, which may allow small animals to enter or equipment to be stolen. By fusing the data from these sensors to obtain the overall current status, operation and maintenance personnel can quickly understand the overall condition of the trench cover and take appropriate measures.

[0019] As an optional embodiment: the specific working mode of the acquisition monitoring module also includes: It should be noted that in the substation environment, data security is of vital importance, and any data leakage or tampering may lead to serious consequences. This technical solution adopts the introduction of blockchain technology to ensure the security and integrity of data during transmission and storage; The collected total status data is processed through a hash algorithm to generate a unique data fingerprint; in this embodiment, the hash algorithm (such as SHA-256) ensures the integrity and consistency of the data. Any tampering with the data will cause the hash value to change and thus be detected. The generated data fingerprint is stored on the blockchain; the distributed ledger feature of the blockchain means that the data is not stored on a single server, but distributed on multiple nodes in the network, which enhances the data's anti-attack ability and immutability; Implement end-to-end encryption to ensure that only the sender and receiver of the data can access the data content, and use the key management system based on the SM9 identification cryptographic algorithm to provide end-to-end security authentication for data transmission. This encryption method prevents any third party, including service providers, from eavesdropping on the communication content, enhancing data privacy protection.

[0020] As an optional embodiment: the specific working mode of the network connection module is as follows: It should be noted that the monitoring data of the trench cover of the substation has high requirements for real-time performance and accuracy. If there is a delay in monitoring, it will also affect the normal use of the substation and pose a safety hazard. This technical solution can optimize the data transmission strategy according to the actual network status and data importance, and reduce data packet loss and delay; Obtain the historical mean of the data transmitted by the network connection module and historical standard deviation It should be noted that in this embodiment, the historical average value of the network connection module transmitting data and historical standard deviation is the historical mean and historical standard deviation of the environment and status data of the channel cover; According to the formula , calculate and obtain the initial threshold value of the data transmitted by the acquisition monitoring module , where k is the adjustment coefficient; it should be noted that in this embodiment, the value of k is 1.023; If the data currently transmitted by the network connection module exceeds the initial threshold , the data transmission priority and transmission frequency are increased, otherwise, data is transmitted at the normal frequency. In this way, it can ensure that abnormal data can be transmitted in time, avoid monitoring delays that affect the normal use of the substation, and optimize the data transmission strategy according to the real-time network status and data characteristics, reduce data packet loss and delay, and improve the stability and efficiency of network connections.

[0021] As an optional embodiment: the network connection module further includes an adjustment unit, which is used to adjust the initial threshold of the data transmitted by the acquisition and monitoring module in real time. Make adjustments, specifically: It should be noted that the monitoring data of the trench cover of the substation is periodic and bursty. This technical solution can adaptively adjust the threshold to ensure the timely transmission of key data; An adjustment interval time is set in advance, and during each adjustment time, the current mean value of the data transmitted by the acquisition monitoring module is calculated. and the current standard deviation ; According to the formula , calculate and obtain the adjusted threshold ; After adjusting the gap time, if the data currently transmitted by the network connection module exceeds the initial threshold , then increase the data transmission priority and transmission frequency, otherwise, transmit data at the normal frequency.

[0022] The dynamic threshold adjustment algorithm can automatically adjust the threshold and transmission strategy, reduce manual intervention, and improve the intelligence level of the system.

[0023] As an optional embodiment: the specific working mode of the monitoring unit is as follows: It should be noted that the traditional monitoring method may focus on post-analysis, lack of real-time analysis capabilities, and cannot respond to sudden changes in the state of the channel cover plate in a timely manner. This technical solution can solve the above problems; The overall current state obtained by the acquisition monitoring module is used to determine whether the channel cover plate is abnormal; in this embodiment, the specific method for determining whether the channel cover plate is abnormal may be: If the total status value is high (for example, the total status value is close to the number of sensors): it means that most sensor parameters are within the preset normal range and the system is operating normally; For example, if the total status value is 4, it means that 4 types of sensors are in normal status and the system can continue to operate normally temporarily; for example, the temperature sensor, humidity sensor, water level sensor, and pressure sensor are in normal status; Pressure sensors may be critical to system operation, and their abnormalities may indicate potential risks; Even if the total status value is 4, if the pressure sensor status is 0, the system should trigger the early warning mechanism and conduct real-time temperature monitoring and analysis; If the total status value is moderate (for example, the total status value is less than the number of sensors but more than half): Indicates that some sensor parameters may deviate from the normal range and require further diagnosis and inspection; If the total status value is 2, it means that 2 types of sensors are in normal state. It may be necessary to check the other 3 types of sensors and perform corresponding maintenance on the channel cover according to the parameters detected by the other 3 types of sensors. For sensors with a status of 0, prioritize them, check key sensors first, and perform corresponding maintenance on the channel cover according to the corresponding parameters. For example, if the temperature sensor status is 0, it should be processed first even if the total status value is not the lowest. It should be noted that, in this embodiment, for sensors with a status of 0, priority sorting is required, which means that among all abnormal sensors, they are sorted according to their importance to the operation of the system, and the most critical sensors are inspected and maintained first.

[0024] For example, if both the temperature sensor and the pressure sensor are abnormal (status 0), and the pressure sensor is critical to system operation, then the pressure sensor should be given a higher priority and be inspected and maintained first. The specific priorities are based on the following factors: Importance of sensors: Which sensors are most critical to the safe and stable operation of the system? Failure history: which sensors have frequently failed in the past; Fault impact: the degree to which sensor failure affects system performance and safety; Maintenance cost and difficulty: Which sensors are easier to maintain and repair? By prioritizing critical sensors, potential system failures can be prevented more effectively, improving system safety and reliability; If the total status value is low (for example, the total status value is much lower than the number of sensors): Indicates that most sensor parameters are not within the preset normal range, the system may have major problems, and immediate measures need to be taken; For example, a total status value of only 1 indicates that only one sensor is in normal condition, which may mean that there is a serious problem with the system and requires urgent inspection and repair.

[0025] Emergency response: Immediately start the system self-check program, quickly diagnose all sensors, determine the cause of the fault, and initiate appropriate emergency measures based on the type of fault.

[0026] If there is an abnormality, an early warning is triggered immediately and a warning signal is generated; relevant personnel are notified via SMS, email or application push; The monitoring unit is also used to dynamically adjust the sampling frequency of the sensor according to the real-time monitoring results.

[0027] As an optional embodiment: the specific working method of dynamically adjusting the sampling frequency of the sensor is as follows: Obtain the initial sampling frequency C1 of each sensor; The mean and standard deviation of the current parameters collected by each sensor are obtained, and the coefficient of variation X is obtained by dividing the mean by the standard deviation. The incremental factor Z of the sampling frequency is obtained according to the coefficient of variation. It should be noted that in this embodiment, different incremental factors Z can be set according to the size of the coefficient of variation X, and two thresholds s1 and s2 of the coefficient of variation X are preset in advance, and s1 is less than s2. If the coefficient of variation X is less than s1, the incremental factor Z is small, and the value can be 0.1022. If the coefficient of variation X is between s1 and s2, the incremental factor Z is medium, and the value can be 0.2025. If the coefficient of variation X is greater than s2, the incremental factor Z is large, and the value can be 0.3049. It should be noted that, in this embodiment, the thresholds s1 and s2 of the two coefficients of variation X are determined by analyzing historical data to be the maximum and minimum values ​​of the normal range of the historical data of the coefficient of variation; If there is no historical data, for each sensor parameter, draw its histogram; s1 can be set to a percentile lower than the first peak of the histogram. This percentile can be set by expert experience. For example, if the first peak of the histogram corresponds to the 80% percentile, s1 can be set to the 70% percentile. s2 can be set to a percentile higher than the first peak, also set by expert experience. For example, if the second peak of the histogram corresponds to the 90% percentile, s2 can be set to the 85% percentile. The value of the incremental factor Z is based on system presets and can be modified accordingly in actual use; If the coefficient of variation X is less than s1, the incremental factor Z is small, which means that the operation is stable and does not need to be frequently adopted. The value can be 0.1022. If the coefficient of variation X is between s1 and s2, the incremental factor Z is medium, which means that the adoption frequency needs to be moderately increased. The value can be 0.2025. If the coefficient of variation X is greater than s2, the incremental factor Z is large, which can be 0.3049, which means that frequent sampling is required. According to the formula , get the adjusted sampling frequency , and transmit it to the remote control unit to adjust each sensor. Continuously monitor the changes in sensor data, update the coefficient of variation and increment factor Z according to the new data, and then adjust the sampling frequency again. This process should be dynamic to adapt to the real-time changes in the state of the channel cover.

[0028] As an optional embodiment: the specific working mode of the remote control unit is as follows: Write control logic according to the operation rules and safety requirements of the channel cover; for example: if the temperature exceeds the set threshold, the cover will automatically open to dissipate heat; if illegal intrusion (such as small animals entering) is detected, the cover will automatically close and an alarm will be sounded; After the monitoring unit sends the warning signal, the corresponding control logic is executed according to the abnormal state value in the acquisition monitoring module; for example: the sensor sends the data to the monitoring unit, the monitoring unit analyzes the sensor data, and determines that the water level is indeed too high. The back-end software sends an opening command to the actuator (such as a drain valve or a cover motor) according to the preset control logic. After receiving the command, the actuator automatically opens the drain valve or adjusts the position of the cover to drain the water. The actuator feeds back the operation result to the data processing center. The center confirms that the operation is successful, and the system informs the operator through the user interface or notification system that the operation has been completed and the cover is adjusted.

[0029] As an optional embodiment: the specific working mode of the remote control unit also includes: It should be noted that the control strategy may be too dependent on preset rules and lack the ability to make dynamic adjustments based on real-time data analysis, and the sensor may not work properly under extreme conditions, resulting in missing or inaccurate data, affecting control decisions, and in extreme weather or other disasters, the communication link may be interrupted, resulting in the inability to convey control commands in a timely manner; Obtain weather information from weather forecasts and mark events above orange warning as extreme events; integrate third-party weather service APIs, such as the National Meteorological Information Center or other reliable weather service providers, to obtain real-time weather forecast data; In the event of an extreme event, the remote control unit can automatically close or lock the cover to prevent further damage. In this embodiment, an automatic closing or locking mechanism of the channel cover is designed to ensure rapid response when an extreme weather warning is received, for example, using an electric push rod or a hydraulic system to control the opening and closing of the cover.

[0030] Through the above steps, the automation system of the trench cover will be able to continue to operate in extreme weather conditions, ensuring that the safety and functionality of the trench cover are not affected.

[0031] As an optional embodiment: the specific working method of the network connection module also includes: Determine the transmission distance of the network connection module; it should be noted that for a wired network, the transmission distance can be determined by measuring the length of the physical medium (such as a network cable), and for a wireless network, the transmission distance can be determined by a signal attenuation test. Signal attenuation to a certain extent will affect the effective and stable transmission of the signal; Dynamically adjust bandwidth allocation according to transmission distance and network conditions. For short-distance transmission (such as wired transmission within 100 meters), high-speed Ethernet technology can be used, such as Category 6 twisted pair with a transmission rate of 1000M. For medium and long-distance transmission, optical fiber communication technology can be used. Through the above steps, appropriate network transmission strategies can be set according to different transmission distances to ensure the real-time, accuracy and security of data transmission.

[0032] How it works The acquisition monitoring module is used to collect the environment and status data of the channel cover in real time: it should be noted that, in this embodiment, the environment and status data of the channel cover include the temperature, humidity, water level, pressure and the opening and closing state of the channel cover, which are obtained by temperature sensors, humidity sensors, water level sensors, pressure sensors, status monitoring sensors (such as opening and closing state), etc. In this embodiment, special sensors such as SF6 gas density monitoring and partial discharge monitoring can also be added to meet the unique monitoring needs of the substation; The acquisition monitoring module is also used to convert the environment and status data of the channel cover plate into a transmission format; convert the digital signal into data in a specific format, such as JSON, XML, etc., which are suitable for network transmission and can be parsed by the upper system; The network connection module is used to receive the environment and status data of the channel cover plate after the acquisition and monitoring module converts the transmission format, and the network connection module transmits the received data of the acquisition and monitoring module to the application module; The monitoring unit is used to monitor the channel cover plate in real time according to the data transmitted by the network connection module, determine whether the channel cover plate has any abnormality, and if so, transmit a control signal to the remote control unit; The remote control unit is used to remotely control the channel cover plate according to the control signal of the monitoring unit.

[0033] The above are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical staff in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of this template.

Claims

1. An intelligent monitoring system for trench cover plates of substations based on the Internet of Things, characterized in that: It includes a collection and monitoring module, which is used to collect the environment and status data of the channel cover in real time: The acquisition monitoring module is also used to convert the environment and status data of the channel cover plate into a transmission format; A network connection module and an application module, wherein the network connection module is used to receive the environment and status data of the channel cover plate after the acquisition and monitoring module converts the transmission format, and the network connection module transmits the received data of the acquisition and monitoring module to the application module; The application module includes a monitoring unit and a remote control unit, wherein the monitoring unit is used to monitor the channel cover plate in real time according to the data transmitted by the network connection module, determine whether the channel cover plate has any abnormality, and if so, transmit a control signal to the remote control unit; The remote control unit is used to remotely control the channel cover plate according to the control signal of the monitoring unit.

2. According to the intelligent monitoring system of the trench cover of the substation based on the Internet of Things in claim 1, it is characterized in that: The acquisition and monitoring module is also used to perform multi-modal fusion on the collected environment and status data of the channel cover plate, specifically: Preprocess the data collected by each sensor; A fusion cycle is preset. At the beginning of the cycle, an initial state estimation value of the cycle is set for each sensor based on the data collected by each sensor for the first time. The estimated value of the initial state of the period is,set the fusion period as one week.,Week 1, Monday: each sensor collected data for the first time, as follows; If the temperature sensor reading is within the normal range, the status estimate is 1; If the humidity sensor reading is within the normal range, the status estimate is 1; If the pressure sensor reading is within the normal range, the state estimation value is 1; If the water level sensor reading is within the normal range, the state estimation value is 1; Week 1, Sunday: After collecting a week’s worth of data, get an estimate of the current state based on each sensor’s parameters; The state estimates of all sensors remain 1; The current state estimation values ​​of all sensors are superimposed to obtain the total state value of the channel cover plate; Total status value = 1+1+1+1=4; The total status value is 4, indicating that the channel cover status of the entire system is normal; At the end of the first week, the fusion cycle ends and the total state value is 4; Week 2, Monday: Start a new fusion cycle and repeat the above steps; Obtain a current state estimation value according to the parameters of each sensor in the previous time period, and the current state estimation value is assigned in the same manner as the initial state estimation value; The current state estimation values ​​of all sensors are superimposed to obtain the total state value of the channel cover, ending the fusion cycle and starting the next fusion cycle.

3. According to the intelligent monitoring system of the trench cover of the substation based on the Internet of Things in claim 2, it is characterized in that: The specific working method of the acquisition monitoring module also includes: The collected total status data is processed through a hash algorithm to generate a unique data fingerprint; the generated data fingerprint is stored on the blockchain; Implement end-to-end encryption to ensure that only the sender and receiver of the data can access the data content, and use the key management system based on the SM9 identification cryptographic algorithm to provide end-to-end security authentication for data transmission.

4. According to the intelligent monitoring system of the trench cover of the substation based on the Internet of Things in claim 1, it is characterized in that: The specific working mode of the network connection module is as follows: Obtain the historical mean of the data transmitted by the network connection module and historical standard deviation ; According to the formula , calculate and obtain the initial threshold value of the data transmitted by the acquisition monitoring module , where k is the adjustment coefficient; If the data currently transmitted by the network connection module exceeds the initial threshold , then increase the data transmission priority and transmission frequency, otherwise, transmit data at the normal frequency.

5. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 4 is characterized in that: The network connection module also includes an adjustment unit, which is used to adjust the initial threshold of the data transmitted by the acquisition monitoring module in real time. Make adjustments, specifically: An adjustment interval time is set in advance, and during each adjustment time, the current mean value of the data transmitted by the acquisition monitoring module is calculated. and the current standard deviation ; According to the formula , calculate and obtain the adjusted threshold ; After adjusting the gap time, if the data currently transmitted by the network connection module exceeds the initial threshold , then increase the data transmission priority and transmission frequency, otherwise, transmit data at the normal frequency.

6. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 2 is characterized in that: The specific working mode of the monitoring unit is as follows: Determining whether the channel cover plate is abnormal by using the total current state obtained by the acquisition monitoring module; The specific method for judging whether there is an abnormality in the channel cover is: If the total status value is greater than 4: it means the system is running normally; The total status value is 4, which means that 4 types of sensors are in normal status and the system continues to operate normally for the time being; Even if the total status value is 4, if the pressure sensor status is 0, it is judged to be abnormal; If the total status value is 2 or 3, further diagnosis and examination are required; If the total status value is 2, it means that two types of sensors are in normal condition, and the other three types of sensors need to be checked, and the channel cover plate needs to be maintained accordingly according to the parameters detected by the other three types of sensors; If the total status value is 3, it means that 3 types of sensors are in normal status, and the other 2 types of sensors need to be checked, and the channel cover plate needs to be maintained accordingly according to the parameters detected by the other 3 types of sensors; If the total status value is 1 or 0, it is judged that there is an abnormality and measures need to be taken; If the total status value is only 1 or 0, it means that only one sensor is in normal condition, which means that there is a problem with the system and needs to be checked and repaired; If there is an abnormality, an early warning is triggered immediately and an early warning signal is generated; The monitoring unit is also used to dynamically adjust the sampling frequency of the sensor according to the real-time monitoring results.

7. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 6 is characterized in that: The specific working method of dynamically adjusting the sampling frequency of the sensor is as follows: Obtain the initial sampling frequency C1 of each sensor; Obtain the mean and standard deviation of the current parameters collected by each sensor, obtain the coefficient of variation X by dividing the mean by the standard deviation, and obtain the incremental factor Z of the sampling frequency based on the coefficient of variation; According to the formula , get the adjusted sampling frequency , and transmitted to the remote control unit to adjust each sensor.

8. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 7 is characterized in that: The specific working mode of the remote control unit is as follows: Write control logic according to the operation rules and safety requirements of the channel cover; After the monitoring unit sends the warning signal, the corresponding control logic is executed according to the abnormal state value in the acquisition monitoring module.

9. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 8 is characterized in that: The specific working method of the remote control unit also includes: Obtain weather information from weather forecasts, and mark events above orange warning as extreme events; In extreme cases, the remote control unit can automatically close or lock the cover to prevent further damage.

10. The intelligent monitoring system for trench cover plates of substations based on the Internet of Things according to claim 4 is characterized in that: The specific working method of the network connection module also includes: Determining the transmission distance of the network connection module; Dynamically adjust bandwidth allocation based on transmission distance and network conditions.

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