SF6 gas density micro water synchronous monitoring method

Abstract

The present application relates to the technical field of high-voltage electrical equipment online monitoring, and discloses a SF6 gas density and micro-water synchronous monitoring method, comprising: synchronously collecting absolute pressure, temperature and micro-water sensor original readings of a gas chamber, establishing a pressure-temperature-micro-water three-parameter coupling compensation model, outputting compensated micro-water content and pairing storage with SF6 density value; when a trigger condition is met, applying a temperature pulse modulation, comparing a response curve with a factory baseline curve to evaluate sensor drift degree by deviation degree; after drift is determined to occur, locking the storage operation of the compensated micro-water content, calculating a drift correction factor, and outputting a final micro-water content value; combining the drift correction factor with pressure and micro-water trend to intelligently distinguish between equipment leakage and sensor drift failure. The present application solves the problems of micro-water data distortion under density change and online sensor self-checking failure, realizes active drift compensation, fills in the monitoring blind area, and can accurately distinguish between leakage and drift working conditions.

Description

Technical Field

[0001] This invention relates to the field of online monitoring technology for high-voltage electrical equipment, and in particular to a method for synchronous monitoring of SF6 gas density and trace moisture. Background Technology

[0002] Sulfur hexafluoride (SF6) gas is widely used in high-voltage electrical equipment such as gas-insulated switchgear, circuit breakers, and instrument transformers due to its excellent insulation and arc-quenching properties. The density and moisture content of SF6 gas are two core indicators reflecting the operating status of the equipment. In actual operation, SF6 gas, trace amounts of water vapor, and a small amount of decomposition gas produced by electric arc discharge are present simultaneously in the gas chamber of SF6 electrical equipment. Existing monitoring methods usually use independent density relays and moisture sensors to collect data separately, with the two measurement channels operating independently.

[0003] This independent measurement architecture has the following technical drawbacks: 1. When a slow leak occurs in the equipment, the total pressure in the gas chamber decreases, and the partial pressure of water molecules decreases proportionally. The volume ratio reading measured by the micro-water sensor under low-pressure conditions will deviate from the true value. Existing technology lacks a real-time pressure compensation method for micro-water measurement values ​​under density change conditions, which leads to distortion of micro-water data in the early stage of leakage and affects the operator's accurate judgment of the equipment status.

[0004] 2. Existing technology can only remove and send sensors for calibration during equipment power outage maintenance, and cannot determine whether the sensor has deteriorated in performance while the equipment is running with power; there is a monitoring blind zone between when the sensor starts to drift and the next power outage maintenance. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for simultaneous monitoring of micro-water content in SF6 gas density. This method solves the problems mentioned in the background section, such as the lack of pressure compensation in micro-water measurement under density change conditions leading to data distortion, and the inability of micro-water sensors to self-calibrate during online operation, resulting in monitoring blind spots.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for simultaneous monitoring of SF6 gas density and trace moisture includes the following steps: S1: Simultaneously collect the absolute pressure value P of the air chamber, the temperature value T of the air chamber, and the raw reading V_raw of the micro water sensor at the same sampling time, and mark the above three data as a set of synchronous sampling data with the same timestamp; S2: Based on the pressure-temperature-micro water three-phase parameter coupling compensation model, the pressure deviation of the absolute pressure value P of the gas chamber at the current sampling time relative to the reference pressure value P0, and the temperature deviation of the current temperature value T relative to the reference temperature value T0, are used to perform real-time compensation and correction on the original reading V_raw of the micro water sensor, and output the compensated micro water content V_comp. S3: When the triggering conditions are met, the online self-calibration process of the micro water sensor is started; the micro heating element installed on the outer wall of the measurement chamber of the micro water sensor is controlled to perform temperature pulse modulation on the micro volume gas in the measurement chamber, and the response curve of the micro water sensor at the rising and falling edges of the temperature pulse is recorded. The response curve is compared with the reference temperature response curve stored at the factory, and the deviation D between the two is calculated. When the deviation D exceeds the preset drift alarm threshold, it is determined that the micro water sensor has experienced performance drift and a maintenance alarm signal is output. S4: After determining that the micro-water sensor has experienced performance drift, lock the storage operation of the compensated micro-water content V_comp in step S2, determine the sensor drift correction factor Δ according to the preset rule, perform drift compensation on the subsequently compensated micro-water content V_comp, and output the final micro-water content value V_final after drift compensation.

[0007] Furthermore, the calculated method for the compensated micro-moisture content V_comp in step S2 is as follows: V_comp = V_raw × (P0 / P) × f(T0 / T) Where f is a temperature correction function, determined by the temperature characteristic curve provided by the micro-water sensor manufacturer; the reference pressure value P0 is the absolute pressure value of the air chamber sampled for the first time under the rated inflation pressure when the equipment is put into operation; and the reference temperature value T0 is the temperature value of the air chamber sampled for the first time when the equipment is put into operation.

[0008] Furthermore, step S2 also includes: substituting the absolute pressure value P and temperature value T of the gas chamber at the same sampling time into the Beattie-Bridgman SF6 gas state equation to calculate the SF6 gas density value ρ, storing the density value ρ in pairs with the compensated micro-moisture content V_comp to form a density-micro-moisture synchronous record; and simultaneously recording the status information of each self-verification execution, including the self-verification timestamp, deviation D, whether a drift alarm is triggered, and whether the S4 locking operation is triggered.

[0009] Furthermore, the triggering condition for step S3 includes at least one of the following: The time interval since the last online self-calibration process of the sensor was completed has reached the preset self-calibration cycle; The compensated micro-moisture content V_comp experienced a sudden change exceeding the statistical fluctuation range in multiple consecutive samplings; It is triggered instantly by external control commands.

[0010] Furthermore, the sensor drift correction factor in step S4 is calculated as follows: Let the execution time of the last self-verification process before the locking time be t0, and the self-verification process determines that the micro-water sensor is normal (D≤drift alarm threshold). Let the current time point be t1, and the micro-water sensor has experienced performance drift (D exceeds the drift alarm threshold). From all the historical data of the compensated micro-water content V_comp during the period from t0 to t1, abnormal data exceeding the preset time window are removed, and the average value is taken as the baseline average value M_baseline. The original micro-water reading V_raw, which was sampled for the first time after the self-calibration determination of drift, is compensated to obtain V_comp_current. The difference between M_baseline and V_comp_current is used as the sensor drift correction factor Δ, Δ=M_baseline-V_comp_current. Δ is stored in non-volatile memory and used to compensate for the drift of all subsequent compensated micro-water contents.

[0011] Furthermore, the drift compensation method for the subsequently compensated micro-water content V_comp is as follows: V_final = V_comp + Δ, where Δ is the sensor drift correction factor. The drift compensation continues until the micro-water sensor is replaced or Δ is reset after offline calibration.

[0012] Furthermore, the reference temperature response curve is obtained in the following way: Before the micro water sensor leaves the factory, the reference mean M_baseline is calculated by sorting all V_comp values ​​within 30 days before the locking time according to the sampling time and taking the median value, or by using a moving average algorithm.

[0013] Furthermore, when the compensated micro-water content V_comp shows a monotonically increasing trend and the absolute pressure value P of the air chamber shows a monotonically decreasing trend in consecutive sampling, the sensor drift correction factor Δ mentioned in step S4 is also considered. When |Δ| does not exceed the preset threshold, the device is determined to have a leakage defect and a leakage alarm signal is output. When |Δ| exceeds the preset threshold, an alarm is output for sensor abnormality, prompting the user to first check the status of the micro-water sensor. During the drift compensation process in step S4, when the absolute value of the sensor drift correction factor Δ continues to increase beyond a preset threshold, an abnormal self-check process is initiated as one of the triggering conditions for step S3.

[0014] Furthermore, the micro-water sensor is a dew point type micro-water sensor, whose measurement chamber is connected to the sampling valve port of the device body through a sampling pipeline. The measurement chamber is equipped with a dew point mirror, a photoelectric detection unit, and a semiconductor cooling chip; the micro heating element is a ceramic heating chip attached to the outer wall of the measurement chamber.

[0015] Furthermore, the deviation D in step S3 is calculated as follows: the response curve is discretized into N sampling points on the rising and falling edges of the pulse, the relative deviation between the response curve and the reference temperature response curve at each sampling point is calculated, and the root mean square value of the relative deviation of all sampling points is taken as the deviation D.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention establishes a three-phase parameter coupling compensation model of pressure-temperature-micro water, performs real-time pressure compensation on the original readings of the micro water sensor, converts the volume ratio reading under low pressure back to the reference pressure state, and performs temperature correction in combination with the temperature characteristic curve, thus solving the problem of data distortion caused by the systematically low micro water reading when the equipment leaks slowly.

[0017] 2. This invention applies temperature pulses to the gas inside the measurement chamber using a miniature heating element, records the sensor response curve, compares it with the factory reference curve, calculates the deviation, and quantitatively assesses the degree of drift. It can autonomously determine the sensor performance degradation while in operation without power outages or disassembly, filling the monitoring blind spot in the prior art between sensor drift and power outage maintenance.

[0018] 3. After determining that the sensor has experienced performance drift, this invention locks the compensated trace moisture content storage operation, establishes a benchmark mean using the last normal historical data before the drift occurred, calculates the sensor drift correction factor Δ, and actively compensates for the drift of all subsequent measurements; the self-calibration result is fed back to the measurement link in real time, so that the system can still output a relatively accurate trace moisture content value in the monitoring blind zone between the occurrence of drift and manual maintenance, thereby improving the availability of monitoring data. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the overall process of a method for simultaneous monitoring of SF6 gas density and micro-water content proposed in this invention. Figure 2 This invention provides an S2 three-phase parameter coupling compensation model for a synchronous monitoring method of SF6 gas density micro-water content. Figure 3 This is a flowchart of the online self-calibration process of the S3 sensor for a method of synchronous monitoring of SF6 gas density and micro-water content proposed in this invention. Figure 4This is a system architecture diagram of a method for simultaneous monitoring of SF6 gas density and micro-water content proposed in this invention. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] Example 1, please refer to Figures 1 to 4 This is the first embodiment of the present invention, which provides a specific implementation method for the synchronous acquisition and pressure-temperature compensation steps in the synchronous monitoring method for SF6 gas density micro-water content.

[0022] The synchronous acquisition unit consists of three parts: an absolute pressure transmitter, a platinum resistance temperature sensor, and a dew point micro-moisture sensor. The absolute pressure transmitter is installed at the gas filling valve port of the equipment and is sealed to the valve port through a threaded interface. Its pressure-sensing diaphragm directly contacts the SF6 gas in the gas chamber and outputs a 4-20mA current signal corresponding to an absolute pressure of 0-1.0MPa.

[0023] The platinum resistance temperature sensor is attached to the outer wall of the equipment housing and covered with heat insulation cotton to reduce the interference of ambient temperature on the measurement. The output resistance signal is converted into a 4-20mA signal by a temperature transmitter. The dew point micro-water sensor is installed at the sampling valve port of the equipment. Its measurement chamber is connected to the valve port through a stainless steel sampling pipeline. The semiconductor cooling chip, gold-plated dew point mirror and photoelectric detection unit are arranged sequentially from bottom to top in the measurement chamber.

[0024] Three signals are connected to the same data acquisition unit, which has a built-in high-precision analog-to-digital converter chip and a GPS / BeiDou timing module; the default acquisition cycle is 15 minutes. At the beginning of each acquisition cycle, the acquisition unit simultaneously latches the instantaneous values ​​of three channels: absolute pressure P (unit MPa), temperature T (unit °C), and raw reading V_raw (unit μL / L or ppmv) of the micro-moisture sensor, and stores this set of data with the same timestamp before storing it in the local storage chip.

[0025] Within the same acquisition cycle, the data logger also calculates the SF6 density value ρ in the current gas chamber according to the Beattie-Bridgman equation of state. The parameters required for the calculation include the currently acquired P and T, as well as the gas chamber volume constant corresponding to the equipment model. The density value ρ is bound to the timestamp and paired with the compensated micro-moisture content V_comp to form a density-micro-moisture synchronous record.

[0026] Step S2 is executed immediately after the data acquisition unit completes the raw data acquisition in S1. The compensation calculation is performed by the ARM processor built into the acquisition unit, without needing to upload to the host computer, thus ensuring the real-time nature of the compensation.

[0027] The reference pressure value P0 and reference temperature value T0 are determined when the equipment is put into operation. On the day of commissioning, after the equipment is charged to the rated pressure and left to stand for 24 hours to allow the gas temperature and shell temperature to reach thermal equilibrium, the first sampling is performed. The P and T values ​​collected this time are recorded as P0 and T0 respectively and stored in the non-volatile memory of the data logger.

[0028] The physical basis of the three-phase parameter coupling compensation model is Dalton's law of partial pressure. In the equipment's gas chamber, the dew point temperature measured by the micro-water sensor depends on the partial pressure of water vapor, not the total pressure of the gas chamber. When the total pressure of the gas chamber drops from P0 to P due to leakage, the partial pressure of water vapor drops proportionally. The volume ratio reading V_raw measured by the sensor under low pressure will be lower than the true micro-water content when the gas is not leaking. Therefore, it is necessary to convert the reading under the current pressure state back to the reference pressure state and multiply it by the pressure ratio P0 / P.

[0029] The temperature correction function f is provided by the sensor manufacturer in the factory report, given in the form of a piecewise line table or cubic polynomial coefficients. After the data acquisition unit imports this function into the host computer configuration software, for any temperature ratio T0 / T, the value of f is obtained by looking up the table and linear interpolation. As an example, if the linear approximation formula f(x)=1+k·(x-1) is used, where x=T0 / T, the value of k is obtained by fitting the temperature characteristic curve of the sensor, and is usually between -0.05 and 0.05.

[0030] The compensated micro-moisture content V_comp is paired with the density value ρ and stored, and then uploaded to the station monitoring backend via RS-485 bus or LoRa wireless module.

[0031] Example 2, as Figure 3 As shown, this is the second embodiment of the present invention. Unlike the previous embodiment, this embodiment provides a specific implementation method for the online self-calibration step of the sensor.

[0032] The sensor online self-calibration process in step S3 can be triggered autonomously within the data acquisition unit without relying on instructions from the host computer. The triggering logic is implemented by the data acquisition unit's firmware program, with the priority from high to low being immediate triggering by external control instructions, triggering by V_comp mutation, and triggering during the self-calibration cycle.

[0033] The self-verification period is set to 30 days by default. When the timer count inside the collector reaches 30 days, the firmware automatically starts the S3 process. The condition for triggering the V_comp mutation is that the V_comp values ​​of the most recent 5 consecutive samples all exceed 3 times the standard deviation of the historical data of the previous 30 days.

[0034] After S3 is started, the data acquisition unit first checks whether the current device is in a stable operating state. The specific judgment condition is that the fluctuation range of the P value and T value of the most recent 3 samples does not exceed ±0.5% and ±1℃, respectively. If the condition is not met, the self-calibration is postponed to the next acquisition cycle for re-judgment. If the condition is met, the temperature pulse modulation stage is entered.

[0035] The miniature heating element is a platinum resistance heating element on an alumina ceramic substrate, which is installed close to the lower half of the outer wall of the measurement chamber; the power supply of the heating element is controlled by a solid-state relay through one digital output port of the data acquisition unit.

[0036] Temperature pulse modulation consists of three stages: preheating, heating, and natural cooling. During the preheating stage, the data logger continuously records the readings of the micro-moisture sensor at a frequency of 10Hz for 10 seconds, taking the average value as the baseline reading before pulse modulation. During the heating stage, the data logger controls the solid-state relay to close, energizes the heating element, and the gas temperature inside the measurement chamber rises at a set rate. The data logger continuously records the readings of the temperature sensor and the micro-moisture sensor at a set frequency until the temperature rise reaches the target value, at which point the solid-state relay is disconnected. During the natural cooling stage, the heating element is de-energized, and the gas inside the measurement chamber cools naturally through the housing. The data logger continues to record the temperature and micro-moisture readings until the temperature drops back to within ±0.5℃ of the baseline value.

[0037] The temperature data sequence and micro-water reading data sequence of the entire modulation process constitute the response curve of this self-calibration. The firmware program inside the acquisition unit compares this response curve with the reference temperature response curve pre-stored at the factory when the sensor leaves the factory.

[0038] The reference temperature response curve is calibrated by the sensor manufacturer using a standard device and written into the sensor's built-in EEPROM chip when the sensor is shipped. It is delivered with the sensor, and the data acquisition unit reads it through the sensor communication interface and stores it in the local memory when the equipment is put into operation.

[0039] The deviation D is calculated in the data acquisition firmware. 40 sampling points are taken from the response curve in the heating and cooling sections (corresponding to about 8 seconds of data). 80 micro-water readings at the corresponding time points of the reference curve are added. The relative deviation between the two sets of readings (the percentage of micro-water reading deviation to the reference reading) is calculated point by point. The root mean square of the 80 relative deviation values ​​is taken as the deviation D for this self-calibration.

[0040] The drift alarm threshold is preset to 8%. When D≤8%, the sensor response characteristics are considered normal, and the timestamp of the current self-calibration and the D value are recorded in the operation log. When D>8% and≤15%, the sensor is considered to have experienced slight drift, and the data acquisition unit sends a yellow alarm to the host computer to remind maintenance personnel to pay attention. When D>15%, the sensor is considered to have experienced severe drift, and a red alarm is sent, prompting that replacement or offline calibration should be arranged as soon as possible.

[0041] Example 3, as Figure 1 and Figure 4 As shown, this is the third embodiment of the present invention. Unlike the previous embodiments, this embodiment provides the overall workflow of the method for simultaneous monitoring of SF6 gas density and micro-water content.

[0042] When the equipment is put into operation, sensor installation and baseline value recording are completed. After commissioning, the data acquisition unit continuously executes S1 and S2 according to the set cycle, synchronously storing and uploading the density value and the compensated micro-moisture value. S3 is executed intermittently according to the trigger condition. During operation, if S2 detects that V_comp shows a monotonically increasing trend and P shows a monotonically decreasing trend after multiple consecutive samplings, the data acquisition unit simultaneously reads the sensor drift correction factor Δ stored in step S4. When |Δ| does not exceed the preset threshold, it is determined that the equipment has a leakage defect, and a leakage alarm signal is output to prompt the operation and maintenance personnel to go to the site to check for leaks; When |Δ| exceeds the preset threshold, it is determined that the sensor is abnormal, and a sensor abnormality alarm is output to prompt maintenance personnel to check the sensor status first.

[0043] When S3 determines that the micro-water sensor has experienced performance drift (D exceeds the 8% drift alarm threshold), the data logger immediately executes the S4 procedure: Step 1: Lock storage operation; The data logger records the current time point as t1, stops storing the subsequently collected V_comp values ​​into the main storage area of ​​the density-micro water synchronous record, but still temporarily stores them in the buffer, and marks the sensor status as "drift compensation mode".

[0044] Step 2: Calculate the baseline mean M_baseline; the data collector backtracks historical data to find the last self-calibration point t0 before the locking time that determined the sensor to be normal (i.e., the self-calibration when D≤8%); from t0 to t1, all historical data of compensated micro-moisture content V_comp are filtered out, and abnormal data points whose temperature deviates from the current sampling point temperature by more than ±2℃ are removed. Then, the remaining data are sorted according to the sampling time, and the arithmetic mean of the middle 50% of the data is calculated to obtain the baseline mean M_baseline.

[0045] Step 3: Calculate the drift correction factor Δ. After determining that drift has occurred, the data logger immediately performs an additional sampling to obtain the current raw water reading V_raw_current, which is then compensated by S2 to obtain V_comp_current. Calculate Δ = M_baseline - V_comp_current. This Δ value reflects the system deviation caused by the sensor changing from its normal state to the current drift state.

[0046] Step 4: Storage and Compensation; Δ is stored in the non-volatile memory (EEPROM) of the data logger; for each subsequent sample, the data logger first calculates V_comp according to S2, then executes V_final=V_comp+Δ, outputs V_final as the final trace moisture content value, and stores it in the main storage area of ​​the density-trace moisture synchronous record; at the same time, the original V_comp and Δ values ​​are still recorded for each sample for log and trend analysis.

[0047] Step 5: Termination and Reset of Compensation; When the micro-water sensor is replaced or put back into operation after offline calibration, the maintenance personnel can manually reset Δ to 0 through external commands and exit the "drift compensation mode"; If the sensor shows that D returns to within 8% after subsequent self-calibration during the compensation process (drift recovers on its own), Δ will be automatically gradually reduced to 0 (reduced proportionally with each sampling) to avoid data jumps.

[0048] Step 6: Anomaly handling of continuous Δ growth; During the drift compensation process, the data acquisition unit continuously monitors the change in the absolute value of Δ; If the absolute value of Δ increases for 5 consecutive samplings exceeding the drift growth threshold, the anomaly self-check process is triggered as one of the triggering conditions for step S3, to confirm whether the sensor has experienced accelerated degradation and to issue an emergency alarm.

[0049] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for simultaneous monitoring of SF6 gas density and trace moisture content, characterized in that, Includes the following steps: S1: Simultaneously collect the absolute pressure value P of the air chamber, the temperature value T of the air chamber, and the raw reading V_raw of the micro water sensor at the same sampling time, and mark the above three data as a set of synchronous sampling data with the same timestamp; S2: Based on the pressure-temperature-micro water three-phase parameter coupling compensation model, the pressure deviation of the absolute pressure value P of the gas chamber at the current sampling time relative to the reference pressure value P0, and the temperature deviation of the current temperature value T relative to the reference temperature value T0, are used to perform real-time compensation and correction on the original reading V_raw of the micro water sensor, and output the compensated micro water content V_comp. S3: When the triggering conditions are met, the online self-calibration process of the micro water sensor is started; the micro heating element installed on the outer wall of the measurement chamber of the micro water sensor is controlled to perform temperature pulse modulation on the micro volume gas in the measurement chamber, and the response curve of the micro water sensor at the rising and falling edges of the temperature pulse is recorded. The response curve is compared with the reference temperature response curve stored at the factory, and the deviation D between the two is calculated. When the deviation D exceeds the preset drift alarm threshold, it is determined that the micro water sensor has experienced performance drift and a maintenance alarm signal is output. S4: After determining that the micro-water sensor has experienced performance drift, lock the storage operation of the compensated micro-water content V_comp in step S2, determine the sensor drift correction factor Δ according to the preset rule, perform drift compensation on the subsequently compensated micro-water content V_comp, and output the final micro-water content value V_final after drift compensation.

2. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 1, characterized in that, The calculation method for the compensated micro-moisture content V_comp in step S2 is as follows: V_comp = V_raw × (P0 / P) × f(T0 / T) Where f is a temperature correction function, determined by the temperature characteristic curve provided by the micro-water sensor manufacturer; the reference pressure value P0 is the absolute pressure value of the air chamber sampled for the first time under the rated inflation pressure when the equipment is put into operation; and the reference temperature value T0 is the temperature value of the air chamber sampled for the first time when the equipment is put into operation.

3. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 1, characterized in that, Step S2 further includes: substituting the absolute pressure value P and temperature value T of the gas chamber at the same sampling time into the Beattie-Bridgman SF6 gas state equation to calculate the SF6 gas density value ρ, storing the density value ρ in pairs with the compensated micro-moisture content V_comp to form a density-micro-moisture synchronous record; and simultaneously recording the status information of each self-verification execution, including the self-verification timestamp, deviation D, whether a drift alarm is triggered, and whether the S4 locking operation is triggered.

4. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 1, characterized in that, The triggering conditions for step S3 include at least one of the following: The time interval since the last online self-calibration process of the sensor was completed has reached the preset self-calibration cycle; The compensated micro-moisture content V_comp experienced a sudden change exceeding the statistical fluctuation range in multiple consecutive samplings; It is triggered instantly by external control commands.

5. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 1, characterized in that, The sensor drift correction factor in step S4 is calculated as follows: Let the execution time of the last self-verification process before the locking time be t0, and the self-verification process determines that the micro water sensor is normal (D≤drift alarm threshold). Let the current time point be t1, and the micro water sensor has experienced performance drift (D exceeds the drift alarm threshold). From all the historical data of the compensated micro water content V_comp during the period from t0 to t1, abnormal data exceeding the preset time window are removed, and the average value is taken as the baseline average value M_baseline. The original micro-water reading V_raw, which was sampled for the first time after the self-calibration determination of drift, is compensated to obtain V_comp_current. The difference between M_baseline and V_comp_current is used as the sensor drift correction factor Δ, Δ=M_baseline-V_comp_current. Δ is stored in non-volatile memory and used to compensate for the drift of all subsequent compensated micro-water contents.

6. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 5, characterized in that, The drift compensation method for the subsequently compensated micro-water content V_comp is: V_final = V_comp + Δ, where Δ is the sensor drift correction factor. The drift compensation is continuously performed until the micro-water sensor is replaced or Δ is reset after offline calibration.

7. The method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 5, characterized in that, The benchmark mean M_baseline is calculated as follows: the median value is taken after sorting all V_comp values ​​within 30 days before the locking time according to the sampling time, or it is calculated using a moving average algorithm.

8. The method for simultaneous monitoring of SF6 gas density and trace moisture according to claim 6, characterized in that, When the compensated micro-water content V_comp shows a monotonically increasing trend and the absolute pressure value P of the air chamber shows a monotonically decreasing trend in multiple consecutive samplings, the sensor drift correction factor Δ mentioned in step S4 is also considered. When |Δ| does not exceed the preset threshold, the device is determined to have a leakage defect and a leakage alarm signal is output. When |Δ| exceeds the preset threshold, an alarm is output for sensor abnormality, prompting the user to first check the status of the micro-water sensor. During the drift compensation process in step S4, when the absolute value of the sensor drift correction factor Δ continues to increase beyond a preset threshold, an abnormal self-check process is initiated as one of the triggering conditions for step S3.

9. The method for simultaneous monitoring of SF6 gas density and trace moisture according to claim 1, characterized in that, The micro water sensor is a dew point type micro water sensor. Its measurement chamber is connected to the sampling valve port of the device body through a sampling pipeline. The measurement chamber is equipped with a dew point mirror, a photoelectric detection unit and a semiconductor cooling chip. The micro heating element is a ceramic heating chip attached to the outer wall of the measurement chamber.

10. A method for simultaneous monitoring of SF6 gas density and micro-water content according to claim 1, characterized in that, The deviation D in step S3 is calculated as follows: the response curve is discretized into N sampling points on the rising and falling edges of the pulse, and the relative deviation between the response curve and the reference temperature response curve at each sampling point is calculated. The root mean square value of the relative deviation of all sampling points is taken as the deviation D.

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