Sulfur hexafluoride monitoring system for transformer substation

Abstract

The invention relates to the technical field of transformer substation sulfur hexafluoride monitoring, in particular to a sulfur hexafluoride monitoring system for a transformer substation, which comprises a detection module, a signal processing unit, a communication interface module, an alarm device and a power management module. The detection module is integrated with various sensors, so that the concentration of sulfur hexafluoride and environmental parameters can be acquired at high precision; the signal processing unit has the functions of data normalization, abnormal value elimination, leakage positioning and trend prediction; the communication interface module supports multi-mode wireless transmission and data encryption; the alarm device provides multi-stage alarm signals; and the power management module adopts a dual-power-supply framework and is integrated with a protection circuit. The system improves the complex environment adaptability through the modular design, has the characteristics of high sensitivity, strong data processing capability and rapid maintenance, and is suitable for real-time monitoring and safety management of sulfur hexafluoride in a transformer substation and other scenes.

Description

Technical Field

[0001] The present invention belongs to the technical field of power equipment monitoring and environmental protection, and in particular relates to a sulfur hexafluoride monitoring system for a transformer substation. Background Art

[0002] Sulfur hexafluoride (SF6), an important insulating gas, is widely used in high-voltage electrical equipment in substations. With the rapid development of power systems, the safe operation of substations is particularly important. However, SF6 leakage poses a potential threat to the environment and equipment operation, placing higher demands on real-time monitoring technology for its concentration. Traditional SF6 monitoring systems rely on a single sensor for detection, which suffers from problems such as insufficient sensitivity, limited data processing capabilities, and a single communication method. Furthermore, some systems have poor adaptability in complex environments, such as high or low temperatures or high humidity, which can affect monitoring performance. Furthermore, existing systems typically have a simple power supply method and lack flexible power management mechanisms, which can lead to the risk of power outages in special scenarios.

[0003] Therefore, it is necessary to design a sulfur hexafluoride monitoring system for substations to solve the problems existing in current technology.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a sulfur hexafluoride monitoring system for a substation.

[0006] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0007] A sulfur hexafluoride monitoring system for a substation comprises a detection module, a signal processing unit, a communication interface module, an alarm device and a power management module; the detection module comprises at least one gas sensor array, which is configured to collect sulfur hexafluoride concentration information in the substation environment in real time; a signal processing unit is connected to the detection module, and is configured to perform normalization operations and eliminate outliers on the collected data; a communication interface module is connected to the signal processing unit, and the communication interface module adopts an industrial-grade wireless transmission protocol for uploading processed data to a remote server; the alarm device is connected to the signal processing unit, and is configured to generate multi-level alarm signals according to preset thresholds; a power management module is respectively connected to the detection module, the signal processing unit, the communication interface module and the alarm device, and the power management module adopts a solar-lithium battery dual power supply architecture and integrates an overvoltage protection circuit.

[0008] Furthermore, the gas sensor array in the detection module includes: an infrared absorption spectrum sensor with a measurement range covering 10ppb to 1000ppm; an ultrasonic leak detection sensor with a sensitivity of up to 0.1ml / min; and an electrochemical sensor with a built-in temperature compensation unit to reduce the impact of ambient temperature on the detection results.

[0009] Furthermore, the detection module also integrates a temperature and humidity sensor and an atmospheric pressure sensor; the measurement range of the temperature and humidity sensor is -40℃ to +80℃, with an accuracy of ±0.5℃; the accuracy level of the atmospheric pressure sensor is 0.5, and the range covers 300hPa to 1100hPa.

[0010] Furthermore, the signal processing unit includes a leakage location module and a trend prediction module; the leakage location module calculates the specific coordinates of the leakage source based on the signal intensity distribution matrix; the trend prediction module uses a time series analysis algorithm to generate a sulfur hexafluoride concentration change curve.

[0011] Furthermore, the communication interface module supports 4G / 5G / NB-IoT multi-mode communication modes, has local data caching function, and has a storage capacity of not less than 128GB; the communication interface module uses the SM4 national encryption algorithm to encrypt the transmitted data.

[0012] Furthermore, the alarm device includes an audible and visual alarm, an SMS alarm unit and a mobile APP push service; the sound intensity of the audible and visual alarm is not less than 85dB; the SMS alarm unit supports group sending function; the mobile APP push service can send real-time alarm information to designated users.

[0013] Furthermore, the power management module has a dual power automatic switching circuit, a remote power monitoring interface and an explosion-proof battery compartment; the switching time of the dual power automatic switching circuit does not exceed 10ms; the remote power monitoring interface communicates with external devices through the RS485 protocol; and the explosion-proof battery compartment adopts an IP67 protection grade design.

[0014] Furthermore, the present invention also includes a self-test module and a fault diagnosis module; the self-test module performs a sensor zero-point calibration operation on a daily basis; the fault diagnosis module can identify 12 types of faults such as sensor failure and communication interruption, and generate corresponding fault codes.

[0015] Furthermore, the trend prediction module adopts a prediction model based on LSTM neural network and support vector machine (SVM) regression algorithm; the prediction time window can be configured from 1 to 24 hours, and the specific duration is set by the user according to actual needs.

[0016] Furthermore, the present invention adopts a modular design, and each component is connected through at least one of a quick-release mechanical interface, a magnetic mounting base and a standard DIN rail mounting slot; the design of the quick-release mechanical interface facilitates the rapid replacement of faulty components; the magnetic mounting base achieves stable adsorption through permanent magnets and is suitable for metal surface installation; the standard DIN rail mounting slot complies with the IEC 60715 standard to ensure installation compatibility.

[0017] Furthermore, when the signal processing unit performs normalization operations and outlier removal on the collected data, the following steps are included: first, the original data is linearly transformed so that all data values ​​are mapped to the interval [0,1]; second, outliers are removed through the 3σ criterion, that is, data points that exceed the range of ±3 times the standard deviation of the mean are removed; finally, the data after outlier removal is smoothed and filtered to reduce noise interference.

[0018] Furthermore, when the leak location module calculates the coordinates of the leak source based on the signal intensity distribution matrix, it includes the following steps: first, obtaining the signal intensity value of each sensor in the gas sensor array and constructing a signal intensity distribution matrix; second, refining the signal intensity distribution matrix through an interpolation algorithm to improve the spatial resolution; finally, using the least squares method to fit the leak source position and output specific coordinate information.

[0019] Furthermore, when the trend prediction module uses the time series analysis algorithm to generate the sulfur hexafluoride concentration change curve, the following steps are included: first, the historical data is segmented and the trend characteristics of each segment of data are extracted; second, the LSTM neural network model and support vector machine (SVM) regression algorithm are trained based on the extracted trend characteristics; finally, the current data is input into the trained model to generate the concentration change curve for a period of time in the future.

[0020] Furthermore, when the communication interface module uses the SM4 national encryption algorithm to encrypt the transmitted data, the following steps are included: first, the data to be transmitted is divided into data blocks of fixed length; second, the SM4 encryption operation is performed on each data block to generate a ciphertext data block; finally, the ciphertext data blocks are combined in sequence into a complete ciphertext data stream, and sent to the remote server via the wireless network.

[0021] Furthermore, when the alarm device generates a multi-level alarm signal according to a preset threshold, the following steps are included: first, three alarm thresholds are set, namely a low alarm threshold, a medium alarm threshold and a high alarm threshold; second, when the detected sulfur hexafluoride concentration exceeds the low alarm threshold but does not reach the medium alarm threshold, a first-level alarm signal is triggered; when the concentration exceeds the medium alarm threshold but does not reach the high alarm threshold, a second-level alarm signal is triggered; when the concentration exceeds the high alarm threshold, a third-level alarm signal is triggered.

[0022] Furthermore, the dual power automatic switching circuit in the power management module includes the following steps during the switching process: first, the output voltage of the solar panel and the lithium battery is monitored in real time; second, when the main power voltage is lower than the preset threshold, the switching logic is started to switch the load to the backup power supply; finally, after the switching is completed, the main power voltage is re-monitored. If it returns to normal, the load is switched back to the main power supply.

[0023] Furthermore, when the self-test module performs the sensor zero-point calibration on a daily basis, the following steps are included: first, reading the output value of the sensor in an environment without sulfur hexafluoride; second, comparing the output value with the standard zero-point value and calculating the deviation; finally, adjusting the calibration parameters of the sensor according to the deviation so that its output value is consistent with the standard zero-point value.

[0024] Furthermore, when the fault diagnosis module identifies 12 fault types such as sensor failure and communication interruption, it includes the following steps: first, defining the characteristic parameters of each fault type; second, monitoring the operating status of the system in real time and extracting relevant parameters; finally, matching the extracted parameters with the characteristic parameters to determine whether a fault exists and generate a corresponding fault code.

[0025] Furthermore, when the trend prediction module adopts a prediction model based on an LSTM neural network, the following steps are included: first, the historical data is divided into a training set and a test set; second, the LSTM neural network is trained using the training set, and the network weights are adjusted until the prediction error meets the requirements; finally, the prediction performance of the model is verified using the test set, and the model parameters are optimized based on the verification results.

[0026] Furthermore, the design of the quick-release mechanical interface includes the following structure: the interface body is made of high-strength aluminum alloy material, and the surface is anodized to improve corrosion resistance; a spring snap mechanism is provided inside the interface, which can be quickly disassembled by pressing a button; the end face of the interface is equipped with a sealing ring to ensure the air tightness of the connection.

[0027] Furthermore, the design of the magnetic mounting base includes the following structure: the base body is made of engineering plastic material, and a high-energy permanent magnet is embedded in the bottom; the surface of the permanent magnet is covered with a layer of non-slip rubber pad to prevent damage to the mounting surface during the adsorption process; there are bolt holes around the base, which can be fixed to a non-metallic surface by bolts.

[0028] Furthermore, the design of the standard DIN rail mounting slot includes the following structure: the mounting slot is stamped from cold-rolled steel plate and the surface is nickel-plated to improve corrosion resistance; elastic clips are provided in the slot to fix the module; and limit baffles are provided at both ends of the slot to prevent the module from slipping out. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings described below are only some embodiments. A person skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0030] Figure 1 This is a structural block diagram of a sulfur hexafluoride monitoring system for a substation according to the present invention;

[0031] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0032] The present invention will now be described in further detail with reference to the accompanying drawings.

[0033] See also Figure 1 As shown, in this embodiment, a sulfur hexafluoride monitoring system for a substation is provided, including a detection module, a signal processing unit, a communication interface module, an alarm device and a power management module.

[0034] Detection module 1 is the core acquisition unit of the entire system, consisting of a gas sensor array, a temperature and humidity sensor, and an atmospheric pressure sensor. The gas sensor array consists of an infrared absorption spectrum sensor, an ultrasonic leak detection sensor, and an electrochemical sensor, all mounted in parallel on the detection module's internal circuit board and connected to the signal processing unit via signal lines. The infrared absorption spectrum sensor is located at the center of the gas sensor array, with a measurement range of 10 ppb to 1000 ppm, capable of real-time detection of sulfur hexafluoride concentrations. Ultrasonic leak detection sensors, with a sensitivity of 0.1 ml / min, are positioned on either side of the infrared absorption spectrum sensor and are used to capture gas signals released from tiny leaks. The electrochemical sensor has a built-in temperature compensation unit, which is linked to the ambient temperature sensor via a thermistor to minimize the impact of external temperature changes on detection results. The temperature and humidity sensor and atmospheric pressure sensor are mounted on the top area of ​​the detection module and exchange data with the gas sensor array via the I2C bus, ensuring the synchronous collection of environmental parameters and gas concentration data.

[0035] The signal processing unit is connected to the detection module via a multi-core shielded cable and integrates a leak location module and a trend prediction module. The leak location module calculates the specific coordinates of the leak source based on the signal intensity distribution matrix. It works by first acquiring the signal intensity values ​​of each sensor in the gas sensor array and storing these values ​​in the signal processing unit's cache. It then refines the signal intensity distribution matrix using an interpolation algorithm to improve spatial resolution. Finally, it uses the least squares method to fit the leak source location and output specific coordinate information. The trend prediction module uses an LSTM neural network and support vector machine regression algorithm to generate a sulfur hexafluoride concentration curve. The calculation process involves segmenting historical data to extract trend features for each segment. The LSTM neural network model and support vector machine regression algorithm are then trained based on the extracted trend features. Finally, the current data is input into the trained model to generate a concentration curve for the future.

[0036] The communication interface module is connected to the signal processing unit via an RS485 interface and supports 4G / 5G / NB-IoT multi-mode communication. It is equipped with a local data cache unit and an SM4 national secret algorithm encryption module. The local data cache unit uses a solid-state storage chip with a storage capacity of not less than 128GB, which is used to temporarily store processed data. The workflow of the SM4 national secret algorithm encryption module includes dividing the data to be transmitted into data blocks of fixed length, performing SM4 encryption operations on each data block to generate ciphertext data blocks, and finally combining the ciphertext data blocks in sequence into a complete ciphertext data stream and sending it to the remote server via the wireless network. The communication interface module also has a breakpoint resume function, which automatically records unsent data blocks when the network is interrupted and re-uploads them after the network is restored.

[0037] The alarm device is connected to a signal processing unit via a relay and integrates an audible and visual alarm, an SMS alarm unit, and a mobile app push service. The audible and visual alarm, mounted on the top of the alarm housing and with a sound intensity of at least 85dB, activates the buzzer and LED light via a control circuit. The SMS alarm unit connects to the mobile communication network via a SIM card module and supports group messaging, sending alarm text messages to designated users when an anomaly is detected. The mobile app push service communicates with the user's smartphone via Wi-Fi or a mobile network. When the sulfur hexafluoride concentration exceeds a preset threshold, it triggers a corresponding alarm signal and pushes real-time alert information to the user. The alarm device has three alarm thresholds: low, medium, and high. A level 1 alarm is triggered when the detected sulfur hexafluoride concentration exceeds the low alarm threshold but does not reach the medium alarm threshold. A level 2 alarm is triggered when the concentration exceeds the medium alarm threshold but does not reach the high alarm threshold. A level 3 alarm is triggered when the concentration exceeds the high alarm threshold.

[0038] The power management module is connected to the detection module, signal processing unit, communication interface module, and alarm device via power cables. It integrates a dual-power automatic switching circuit, a remote power monitoring interface, and an explosion-proof battery compartment. The dual-power automatic switching circuit uses a voltage monitoring chip to monitor the output voltage of the solar panel and lithium battery in real time. When the main power supply voltage falls below a preset threshold, the switching logic is activated to switch the load to the backup power supply in less than 10ms. The remote power monitoring interface communicates with external devices via the RS485 protocol, providing real-time battery charge information. The explosion-proof battery compartment features an IP67 protection rating and an internal overvoltage protection circuit to prevent overcharging or short-circuiting of the battery.

[0039] The self-test module and fault diagnosis module are integrated into the signal processing unit. The self-test module performs a daily sensor zero-point calibration. Its workflow involves reading the sensor's output value in a sulfur hexafluoride-free environment, comparing this output value with the standard zero-point value to calculate the deviation, and finally adjusting the sensor's calibration parameters based on the deviation to align its output value with the standard zero-point value. The fault diagnosis module can identify 12 fault types, including sensor failure and communication interruption. Its workflow involves defining characteristic parameters for each fault type, monitoring the system's operating status in real time, extracting relevant parameters, matching the extracted parameters with the characteristic parameters, determining whether a fault exists, and generating the corresponding fault code.

[0040] The modular design of the system allows each component to be connected through at least one of a quick-release mechanical interface, a magnetic mounting base, and a standard DIN rail mounting slot. The design of the quick-release mechanical interface includes an interface body made of high-strength aluminum alloy, with an anodized surface for improved corrosion resistance. A spring clip mechanism is installed inside the interface, which can be quickly disassembled by pressing a button. The end face of the interface is equipped with a sealing ring to ensure the airtightness of the connection. The design of the magnetic mounting base includes a base body made of engineering plastic, with a high-energy permanent magnet embedded in the bottom. The surface of the permanent magnet is covered with a layer of non-slip rubber pad to prevent damage to the mounting surface during adsorption. Bolt holes are provided around the base so that it can be fixed to a non-metallic surface by bolts. The design of the standard DIN rail mounting slot includes a slot body stamped from cold-rolled steel plate, with a nickel-plated surface for improved corrosion resistance. An elastic clip is installed in the slot to fix the module, and limit baffles are installed at both ends of the slot to prevent the module from sliding out.

[0041] The signal processing unit normalizes and removes outliers from the collected data by first performing a linear transformation on the raw data to map all values ​​to the [0, 1] range. It then uses the 3σ criterion to remove outliers, i.e., data points outside the range of ±3 standard deviations from the mean. Finally, the data after outlier removal undergoes smoothing filtering to reduce noise. The communication interface module uses the SM4 national encryption algorithm to encrypt transmitted data. It first segments the data to be transmitted into fixed-length blocks. It then performs the SM4 encryption operation on each block to generate a ciphertext block. Finally, the ciphertext blocks are sequentially combined into a complete ciphertext data stream and transmitted via the wireless network to a remote server. The dual-power automatic switching circuit in the power management module monitors the output voltages of the solar panel and lithium battery in real time. When the main power supply voltage falls below a preset threshold, it activates the switching logic to switch the load to the backup power supply. Finally, after the switchover is complete, it re-monitors the main power supply voltage. If the voltage returns to normal, the load is switched back to the main power supply.

[0042] In order to better enable relevant personnel in this technical field to fully understand and implement the present invention, the specific implementation principle of the present invention is further supplemented below with reference to a specific application scenario.

[0043] In actual substation operation, a SF6 monitoring system is deployed near high-voltage electrical equipment to detect changes in SF6 gas concentration in real time. The system's operation is described in detail in the following steps.

[0044] First, the detection module collects environmental data through its internal gas sensor array, temperature and humidity sensors, and atmospheric pressure sensors. The infrared absorption spectrum sensor in the gas sensor array is located at the center, with a detection range of 10ppb to 1000ppm, capable of highly sensitive detection of sulfur hexafluoride gas concentrations. Ultrasonic leak detection sensors are placed on both sides of the infrared absorption spectrum sensor to capture gas signals released from tiny leaks, with a sensitivity of 0.1ml / min. The electrochemical sensor is linked to the thermistor via a built-in temperature compensation unit to reduce the impact of external temperature fluctuations on the detection results. The temperature and humidity sensors and atmospheric pressure sensor are installed in the top area of ​​the detection module and exchange data synchronously with the gas sensor array via the I2C bus to ensure consistency between the collected environmental parameters and gas concentration data. The data from these sensors is transmitted to the signal processing unit via signal lines, completing the initial data collection task.

[0045] The signal processing unit then normalizes the received data and removes outliers. First, the raw data is linearly mapped to the [0, 1] interval to eliminate the impact of different dimensions on subsequent processing. Next, the 3σ criterion is used to remove outlier data points that fall outside the range of ±3 standard deviations from the mean, thereby reducing noise interference. Finally, the data after outlier removal is smoothed and filtered to improve data quality. Based on this, the leak location module calculates the specific coordinates of the leak source based on the signal intensity distribution matrix. The signal processing unit first obtains the signal intensity values ​​of each sensor in the gas sensor array and stores these values ​​in a cache. The signal intensity distribution matrix is ​​then refined using an interpolation algorithm to improve spatial resolution. Finally, the least squares method is used to fit the leak source location and output the specific coordinate information. Meanwhile, the trend prediction module uses an LSTM neural network and support vector machine regression algorithm to generate a sulfur hexafluoride concentration curve. This module segments historical data, extracts trend features of each segment, and trains the LSTM neural network model and support vector machine regression algorithm based on the extracted features. Finally, the current data is input into the trained model to generate a concentration change curve for a period of time in the future.

[0046] The communication interface module is connected to the signal processing unit via the RS485 interface and is responsible for uploading the processed data to the remote server. The communication interface module first divides the data to be transmitted into data blocks of fixed length and performs SM4 encryption operation on each data block to generate a ciphertext data block. Subsequently, the ciphertext data blocks are sequentially combined into a complete ciphertext data stream and sent to the remote server via 4G / 5G / NB-IoT multi-mode communication. In the event of a network interruption, the communication interface module will automatically record the unsent data blocks and re-upload them after the network is restored to ensure the integrity of the data transmission. In addition, the local data cache unit uses a solid-state storage chip with a storage capacity of not less than 128GB for temporarily storing processed data.

[0047] The alarm device is connected to the signal processing unit via a relay and triggers an alarm signal when it detects that the sulfur hexafluoride concentration exceeds a preset threshold. The alarm device is set to three alarm thresholds: low, medium, and high. A level 1 alarm is triggered when the detected sulfur hexafluoride concentration exceeds the low alarm threshold but does not reach the medium alarm threshold; a level 2 alarm is triggered when the concentration exceeds the medium alarm threshold but does not reach the high alarm threshold; and a level 3 alarm is triggered when the concentration exceeds the high alarm threshold. An audible and visual alarm is mounted on the top of the alarm device's housing. Its sound intensity is no less than 85dB, and the control circuit drives a buzzer and LED light to produce audible and visual alarms. The SMS alarm unit connects to the mobile communication network via a SIM card module and supports group messaging, sending alarm text messages to designated users when an anomaly is detected. The mobile app push service communicates with the user's smart terminal via Wi-Fi or mobile network to deliver real-time alarm information.

[0048] The power management module is connected to the detection module, signal processing unit, communication interface module, and alarm device via power cables, providing them with a stable power supply. The dual-power automatic switching circuit monitors the output voltage of the solar panel and lithium battery in real time through a voltage monitoring chip. When the main power voltage falls below the preset threshold, the switching logic is activated to switch the load to the backup power supply, and the switching time does not exceed 10ms. After the switch is completed, the main power voltage is re-monitored. If it returns to normal, the load is switched back to the main power supply. The remote power monitoring interface communicates with external devices via the RS485 protocol and provides real-time feedback on battery power information. The explosion-proof battery compartment adopts an IP67 protection level design and is equipped with an internal overvoltage protection circuit to prevent battery overcharging or short circuiting.

[0049] The self-test module performs sensor zero-point calibration daily. It first reads the sensor's output in a sulfur hexafluoride-free environment, compares it with the reference zero-point value, and calculates the deviation. Finally, it adjusts the sensor's calibration parameters based on the deviation to align its output with the reference zero-point value. The fault diagnosis module monitors the system's operating status in real time, identifying 12 fault types, including sensor failure and communication interruption. This module first defines characteristic parameters for each fault type and extracts the relevant parameters in real time. It then matches the extracted parameters with the characteristic parameters to determine whether a fault exists and generates a corresponding fault code.

[0050] The modular design of the system allows the components to be connected through at least one of the following methods: a quick-release mechanical interface, a magnetic mounting base, and a standard DIN rail mounting slot. The design of the quick-release mechanical interface includes an interface body made of high-strength aluminum alloy, with an anodized surface for improved corrosion resistance. A spring clip mechanism is provided inside the interface, allowing for quick disassembly by pressing a button, and a sealing ring is provided on the end face of the interface to ensure the airtightness of the connection. The design of the magnetic mounting base includes a base body made of engineering plastic, with a high-energy permanent magnet embedded in the bottom. The surface of the permanent magnet is covered with a layer of non-slip rubber pad to prevent damage to the mounting surface during adsorption. Bolt holes are provided around the base so that it can be fixed to a non-metallic surface by bolts. The design of the standard DIN rail mounting slot includes a slot body stamped from cold-rolled steel plate, with a nickel-plated surface for improved corrosion resistance. An elastic clip is provided inside the slot to fix the module, and limit baffles are provided at both ends of the slot to prevent the module from slipping out.

[0051] Through the above steps, the present invention achieves highly sensitive detection of sulfur hexafluoride gas concentration in substation environments, precise leak location, concentration trend prediction, and multi-level alarm functions, while also providing adaptability to complex environments and a flexible power management mechanism. These features not only improve the reliability of the sulfur hexafluoride monitoring system but also significantly enhance the safe operation of substations.

[0052] The present invention is not limited to the above-described embodiments. Any structural changes made under the guidance of the present invention, which have the same or similar technical solutions as the present invention, should be understood to fall within the scope of protection of the present invention. The technologies, shapes, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A sulfur hexafluoride monitoring system for a substation, characterized in that: include: Detection module, signal processing unit, communication interface module, alarm device and power management module; The detection module includes at least one gas sensor array, and the gas sensor array is configured to collect sulfur hexafluoride concentration information in the substation environment in real time; The signal processing unit is connected to the detection module, and the signal processing unit is configured to perform normalization operations and outlier removal on the collected data; The communication interface module is connected to the signal processing unit, and the communication interface module adopts an industrial-grade wireless transmission protocol for uploading processed data to a remote server; the alarm device is connected to the signal processing unit, and the alarm device is configured to generate a multi-level alarm signal according to a preset threshold; The power management module is connected to the detection module, signal processing unit, communication interface module and alarm device respectively. The power management module adopts a solar-lithium battery dual power supply architecture and integrates an overvoltage protection circuit.

2. A sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The gas sensor array in the detection module includes: an infrared absorption spectrum sensor, an ultrasonic leak detection sensor and an electrochemical sensor; The infrared absorption spectrum sensor has a measurement range of 10 ppb to 1000 ppm; The sensitivity of the ultrasonic leak detection sensor reaches 0.1 ml / min; The electrochemical sensor has a built-in temperature compensation unit to reduce the influence of ambient temperature on the detection result.

3. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The detection module is also integrated with a temperature and humidity sensor and an atmospheric pressure sensor; The temperature and humidity sensor has a measurement range of -40 degrees Celsius to +80 degrees Celsius, with an accuracy of + / - 0.5 degrees Celsius. The atmospheric pressure sensor has an accuracy level of 0.5 and a measuring range of 300 hPa to 1100 hPa.

4. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The signal processing unit includes a leakage positioning module and a trend prediction module; The leakage locating module calculates the specific coordinates of the leakage source based on the signal strength distribution matrix; The trend prediction module generates a sulfur hexafluoride concentration change curve using a time series analysis algorithm.

5. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The communication interface module supports 4G / 5G / NB-IoT multi-mode communication, has a local data cache function, and a storage capacity of not less than 128GB; The communication interface module uses the SM4 national encryption algorithm to encrypt the transmitted data.

6. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The alarm device includes an audible and visual alarm, a text message alarm unit and a mobile APP push service; The sound intensity of the sound and light alarm is not less than 85dB; The SMS alarm unit supports group messaging function; The mobile APP push service can send real-time alarm information to designated users.

7. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The power management module has a dual power automatic switching circuit, a remote power monitoring interface and an explosion-proof battery compartment; The switching time of the dual power automatic switching circuit does not exceed 10ms; The remote power monitoring interface communicates with external devices via the RS485 protocol; The explosion-proof battery compartment is designed with IP67 protection grade.

8. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: It also includes a self-test module and a fault diagnosis module; The self-test module performs a sensor zero point calibration operation at regular intervals every day; The fault diagnosis module can identify 12 fault types such as sensor failure and communication interruption, and generate corresponding fault codes.

9. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: The trend prediction module adopts a prediction model based on LSTM neural network and support vector machine regression algorithm; The prediction time window can be configured to be 1 hour to 24 hours, and the specific duration is set by the user according to actual needs.

10. The sulfur hexafluoride monitoring system for a substation according to claim 1, characterized in that: Each component is connected by at least one of a quick-release mechanical interface, a magnetic mounting base, and a standard DIN rail mounting slot; The design of the quick-release mechanical interface facilitates the rapid replacement of faulty components; The magnetic mounting base achieves stable adsorption through permanent magnets and is suitable for installation on metal surfaces; The standard DIN rail mounting slots comply with IEC 60715 standards, ensuring installation compatibility.

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