An oil leakage diagnosis and gas concentration compensation method and system for an oil and gas monitoring device

Abstract

A method and system for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device, which relate to the field of measuring electrical variables. In this method, the standard fluctuation range of the oil level height is calculated based on historical oil level height data; the theoretical oil level height is calculated based on real-time pressure data; if the real-time oil level height data is lower than the lower limit value of the standard fluctuation range and the theoretical oil level height is higher than the upper limit value of the standard fluctuation range, it is determined that oil leakage has occurred; the historical gas concentration data is used as the reference gas concentration; the attenuation rate of the real-time gas concentration data relative to the reference gas concentration is calculated; the target attenuation coefficient closest to the attenuation rate is matched; and the real-time gas concentration data is compensated according to the target attenuation coefficient to obtain the compensated gas concentration data. This application improves the true value of the gas concentration monitoring value, and thus improves the accuracy of gas concentration detection.

Description

Technical Field

[0001] This application belongs to the field of measuring electrical variables, and particularly relates to a method and system for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device. Background Art

[0002] During the long-term operation of an oil and gas monitoring device, since oil and solid insulating materials will gradually age and deteriorate, various gases including hydrogen, methane, ethane, ethylene, acetylene, carbon monoxide, and carbon dioxide will be decomposed. The content of these gases is directly related to the type and degree of internal faults of the oil and gas monitoring device. Therefore, timely and accurate detection of these dissolved gases is of great significance for preventing faults of the oil and gas monitoring device.

[0003] In the related art, the gas content in the oil of the oil and gas monitoring device can be monitored in real time by setting gas sensors, and the monitoring data can be used as the basis for fault diagnosis of the oil and gas monitoring device. This method can realize the real-time monitoring of the gas content in the oil of the oil and gas monitoring device, which is beneficial to timely discover potential faults of the oil and gas monitoring device.

[0004] However, in the actual monitoring process, there is a problem of insufficient sealing performance of the oil and gas monitoring device, and oil leakage is likely to occur. Oil leakage will cause the dissolved gases in the oil of the oil and gas monitoring device to escape, resulting in the deviation of the gas concentration monitoring value from the true value and reducing the accuracy of gas concentration detection. Summary of the Invention

[0005] This application provides a method and system for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device, which is used to improve the true value of the gas concentration monitoring value, and further improve the accuracy of gas concentration detection.

[0006] In a first aspect, this application provides a method for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device, which obtains real-time data of the oil level height in the oil and gas monitoring device and historical oil level height data within a preset time period;

[0007] Based on the historical oil level height data, calculate the standard fluctuation range of the oil level height. The upper limit value of the standard fluctuation range is the maximum value of the historical oil level height, and the lower limit value is the minimum value of the historical oil level height;

[0008] Obtain real-time data of the pressure in the oil and gas monitoring device, and calculate the theoretical oil level height based on the real-time pressure data;

[0009] Compare the real-time data of the oil level height, the theoretical oil level height with the standard fluctuation range. If the real-time data of the oil level height is lower than the lower limit value of the standard fluctuation range and the theoretical oil level height is higher than the upper limit value of the standard fluctuation range, it is determined that oil leakage has occurred;

[0010] When it is determined that an oil leak has occurred, obtain the historical gas concentration data within a preset time period before the current moment, and use the historical gas concentration data as the reference gas concentration;

[0011] Obtain the real-time gas concentration data, and calculate the attenuation rate of the real-time gas concentration data relative to the reference gas concentration;

[0012] Match the target attenuation coefficient corresponding to the target attenuation rate closest to the attenuation rate in the preset attenuation coefficient set;

[0013] Compensate the real-time gas concentration data according to the target attenuation coefficient to obtain the compensated gas concentration data.

[0014] By adopting the above technical solution, by obtaining the real-time data and historical data of the oil level height to establish a standard fluctuation range, and combining the real-time pressure data to calculate the theoretical oil level height for comparison, the accuracy of identifying oil leakage can be improved. When an oil leak occurs, due to the decrease in the oil level, the dissolution gas escapes faster. By obtaining the historical gas concentration data before the oil leak as the reference, calculating the attenuation rate of the real-time gas concentration relative to the reference concentration, and matching the closest target attenuation coefficient in the preset attenuation coefficient set, the real-time gas concentration is compensated, so that the gas concentration data can more accurately reflect the actual state of the oil and gas monitoring equipment. By establishing a dual judgment mechanism of the standard fluctuation range and the theoretical calculated value, the misjudgment probability is reduced; by selecting the compensation coefficient based on the actual attenuation rate, the compensation is more in line with the actual situation; by accurately compensating the gas concentration, the true value of the gas concentration monitoring value is improved, and thus the accuracy of the gas concentration detection is improved.

[0015] Combined with some embodiments of the first aspect, in some embodiments, calculating the theoretical oil level height based on the real-time pressure data specifically includes:

[0016] Obtain the current ambient atmospheric pressure value, the structural parameters of the oil and gas monitoring equipment, and the density parameters of the oil. The structural parameters include the cross-sectional area of the fuel tank and the height of the fuel tank;

[0017] Subtract the current ambient atmospheric pressure value from the real-time pressure data to obtain the relative pressure value;

[0018] According to the hydrostatic principle, calculate the theoretical oil column height based on the relative pressure value, the cross-sectional area of the fuel tank, and the density parameters.

[0019] By adopting the above technical solution, the relative pressure value is obtained by subtracting the ambient atmospheric pressure value from the real-time pressure data, and then the theoretical oil column height is calculated based on the hydrostatic principle, making the theoretical calculation result more in line with the actual physical process. By introducing ambient atmospheric pressure compensation, the influence of atmospheric pressure change on the calculation of the theoretical oil level is reduced; by considering the cross-sectional area and density parameters of the fuel tank, the theoretical calculation can more accurately reflect the actual oil level height; by applying the hydrostatic principle, an accurate corresponding relationship between pressure and oil level is established, improving the calculation accuracy of the theoretical oil level height, and thus improving the accuracy of oil leakage judgment.

[0020] In combination with some embodiments of the first aspect, in some embodiments, calculating the attenuation rate of the real-time gas concentration data relative to the reference gas concentration specifically includes:

[0021] Obtain the solubility coefficient and molecular mass parameters of different types of gases;

[0022] According to the real-time pressure data and real-time temperature data, calculate the dissolution equilibrium constant of each type of gas in the oil and gas monitoring equipment;

[0023] Based on the dissolution equilibrium constant, calculate the diffusion flux of each type of gas respectively;

[0024] According to the gas diffusion flux, calculate the mass of each type of gas escaping per unit time;

[0025] Divide the mass of gas escaping by the volume of the oil in the oil and gas monitoring equipment to obtain the concentration change amount of each type of gas per unit time;

[0026] According to the concentration change amount, calculate the monomer attenuation rate of each type of gas, where the monomer attenuation rate is equal to the ratio of the difference between the real-time gas concentration and the reference gas concentration to the product of the reference gas concentration and the gas attenuation duration;

[0027] Perform a weighted average calculation on the monomer attenuation rates of each type of gas to obtain the attenuation rate, and the weight coefficients of each type of gas are proportional to the corresponding gas molecular mass.

[0028] By adopting the above technical solution, calculate the dissolution equilibrium constant and diffusion flux, obtain the mass of each type of gas escaping, and then calculate the concentration change amount per unit time. When calculating the overall attenuation rate, a weighted average method based on molecular mass is adopted, making the contribution of different gases to the overall attenuation rate correspond to their physical properties, accurately reflecting the gas escape law; by calculating the monomer attenuation rate of each type of gas, the difference in the escape characteristics of different gases is reflected; through the way of molecular mass weighted average, the influence degree of each type of gas is reasonably balanced, improving the calculation accuracy of the attenuation rate, and thus improving the accuracy of gas concentration compensation.

[0029] In some embodiments in combination with some embodiments of the first aspect, after compensating the real-time gas concentration data according to the target attenuation coefficient to obtain the compensated gas concentration data, the method further includes:

[0030] Obtain the standard gas concentration thresholds under multiple preset working conditions, and each preset working condition corresponds to a different combination of load level and ambient temperature;

[0031] Determine the current working condition based on the preset working condition, the current load rate of the oil and gas monitoring device, and the current ambient temperature;

[0032] Compare the compensated gas concentration data with the standard gas concentration threshold corresponding to the current working condition;

[0033] If the compensated concentration data of any gas exceeds the corresponding standard gas concentration threshold, obtain the historical concentration change trend of the gas;

[0034] When it is determined according to the historical concentration change trend that the concentration of the gas is continuously rising, trigger an alarm signal.

[0035] By adopting the above technical solution, by obtaining the standard gas concentration thresholds under multiple preset working conditions and determining the current working condition based on the current load rate and ambient temperature, the differentiation of gas concentration alarm judgment is realized. Compare the compensated gas concentration with the standard threshold of the corresponding working condition, and combine the historical concentration change trend of the gas. By considering the historical change trend, the influence of short-term fluctuations in gas concentration is filtered; by requiring the gas concentration to continuously rise before triggering an alarm, the reliability of the alarm is improved, thereby reducing the false alarm rate and improving the accuracy and timeliness of the alarm.

[0036] In some embodiments in combination with some embodiments of the first aspect, determining the current working condition based on the preset working condition, the current load rate of the oil and gas monitoring device, and the current ambient temperature specifically includes:

[0037] Compare the current load rate of the oil and gas monitoring device with multiple preset load intervals to determine the target load interval where the current load rate is located;

[0038] Compare the current ambient temperature with multiple preset temperature intervals to determine the target temperature interval where the current ambient temperature is located;

[0039] Determine the current working condition according to the combination of the target load interval and the target temperature interval and the preset working condition. The preset load intervals include a low load interval, a medium load interval, and a high load interval. The preset temperature intervals include a low temperature interval, a normal temperature interval, and a high temperature interval. The preset working condition is composed of any two interval combinations of the preset load interval and the preset temperature interval.

[0040] By adopting the above technical solution, comparing the current load rate with the preset load range to determine the target load range, comparing the current ambient temperature with the preset temperature range to determine the target temperature range, and determining the current working condition based on the combination of the target load range and the target temperature range, the accurate positioning of the operating condition of the oil and gas monitoring equipment can be achieved. Since the gas dissolution characteristics of the oil and gas monitoring equipment vary under different load and temperature conditions, by subdividing the preset load range into a low load range, a medium load range, and a high load range, and subdividing the preset temperature range into a low temperature range, a normal temperature range, and a high temperature range, and combining any two ranges to form a preset working condition, the working condition division is more refined, and it can more accurately reflect the dissolved gas equilibrium state of the oil in the oil and gas monitoring equipment under different operating conditions.

[0041] In combination with some embodiments of the first aspect, in some embodiments, after triggering an alarm signal when it is determined according to the historical concentration change trend that the concentration of the gas is continuously rising, the method further includes:

[0042] Collect oil level, top oil temperature, and load current data;

[0043] Extract the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics of the compensated gas concentration data;

[0044] Calculate the correlation coefficients between the compensated gas concentration and the oil level, top oil temperature, load current, and current ambient temperature respectively;

[0045] Judge the alarm reliability according to the combination of the correlation coefficients and the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics.

[0046] By adopting the above technical solution, collecting the oil level, top oil temperature, and load current data, extracting the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics of the compensated gas concentration data, and calculating the correlation coefficients between the compensated gas concentration and each monitoring parameter, the law of gas concentration change can be comprehensively analyzed from multiple time scales and multiple relevant factors, and it can distinguish the gas anomalies caused by the equipment itself from the gas fluctuations caused by environmental factors and changes in operating conditions. By introducing the calculation of the correlation coefficient, the degree of association between the gas concentration change and each influencing factor can be quantitatively characterized, providing an objective basis for evaluating the alarm reliability, reducing the false alarm rate of the alarm, and improving the accuracy of fault diagnosis.

[0047] In combination with some embodiments of the first aspect, in some embodiments, judging the alarm reliability according to the combination of the correlation coefficients and the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics specifically includes:

[0048] Extract the periodic change component and the trend change component of the compensation gas concentration according to the combination of the daily change fluctuation characteristics, the weekly change cycle characteristics, and the monthly change trend characteristics;

[0049] When any one of the following conditions is met: the correlation coefficient between the compensation gas concentration and the oil level is greater than the first preset threshold and the daily change fluctuation characteristics meet the preset conditions; the correlation coefficient between the compensation gas concentration and the top oil temperature and the current ambient temperature is greater than the second preset threshold and the weekly change cycle characteristics are consistent with the temperature change cycle; the correlation coefficient between the compensation gas concentration and the load current is greater than the third preset threshold and the monthly change trend characteristics are consistent with the load change trend, set the alarm reliability to the first reliability;

[0050] When none of the above conditions are met and the trend change component is greater than the periodic change component, set the alarm reliability to the second reliability, and the second reliability is greater than the first reliability.

[0051] By adopting the above technical solution, when the gas concentration change has a significant correlation with certain external factors and the time characteristics meet the corresponding rules, the alarm reliability is set to a lower level, indicating that the gas anomaly may be caused by normal operation state fluctuations. When the gas concentration change has no correlation with external factors and the trend change dominates, the alarm reliability is set to a higher level, reflecting the possible existence of internal equipment failures. This alarm grading method based on the strength of correlation and change characteristics can help operation and maintenance personnel reasonably judge the urgency of alarms and improve the efficiency of fault handling.

[0052] In a second aspect, an embodiment of the present application provides an oil leakage diagnosis and gas concentration compensation system for an oil and gas monitoring device. The oil leakage diagnosis and gas concentration compensation system for the oil and gas monitoring device includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code. The computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0053] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, including instructions, which when running on the system, enable the system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0054] In a fourth aspect, an embodiment of the present application provides a computer program product, which when running on the system, enables the system to execute the method described in any possible implementation manner in the first aspect.

[0055] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0056] 1. The present application provides a method for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device. By obtaining real-time data and historical data of the oil level height to establish a standard fluctuation range, and calculating the theoretical oil level height in combination with real-time pressure data for comparison, the accuracy of identifying oil leakage can be improved. When oil leakage occurs, since the reduction of the oil level causes the dissolved gas to escape faster, by obtaining the historical data of the gas concentration before oil leakage as a reference, calculating the attenuation rate of the real-time gas concentration relative to the reference concentration, and matching the closest target attenuation coefficient in the preset attenuation coefficient set, the real-time gas concentration is compensated, so that the gas concentration data can more accurately reflect the actual state of the oil and gas monitoring device. By establishing a dual judgment mechanism of the standard fluctuation range and the theoretical calculation value, the misjudgment probability is reduced; by selecting the compensation coefficient based on the actual attenuation rate, the compensation is more in line with the actual situation; by accurately compensating the gas concentration, the true value of the gas concentration monitoring value is improved, and thus the accuracy of gas concentration detection is improved.

[0057] 2. The present application provides a method for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device. By obtaining the standard gas concentration thresholds under multiple preset working conditions and determining the current working condition based on the current load rate and environmental temperature, the differentiation of gas concentration alarm judgment is realized. Comparing the compensated gas concentration with the standard threshold of the corresponding working condition, and combining the historical change trend of the gas concentration. By considering the historical change trend, the influence of short-term fluctuations of the gas concentration is filtered; by requiring the gas concentration to continue to rise to trigger an alarm, the reliability of the alarm is improved, and thus the false alarm rate is reduced, and the accuracy and timeliness of the alarm are improved.

[0058] 3. The present application provides a method for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device. Collecting oil level, top layer oil temperature and load current data, extracting the daily change fluctuation characteristics, weekly change cycle characteristics and monthly change trend characteristics of the compensated gas concentration data, and calculating the correlation coefficients between the compensated gas concentration and each monitoring parameter, the law of gas concentration change can be comprehensively analyzed from multiple time scales and multiple relevant factors, and it can distinguish the gas anomalies caused by the device itself failure from the gas fluctuations caused by environmental factors and changes in operating conditions. By introducing the calculation of the correlation coefficient, the correlation degree between the gas concentration change and each influencing factor can be quantitatively characterized, providing an objective basis for evaluating the alarm reliability, which can reduce the false alarm rate of the alarm and improve the accuracy of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a schematic flow chart of a method for diagnosing oil leakage and compensating gas concentration of an oil and gas monitoring device in an embodiment of the present application.

[0060] Figure 2It is a schematic flowchart of a method for abnormal monitoring and alarm processing of gas concentration after compensation in an embodiment of the present application.

[0061] Figure 3 It is a schematic structural diagram of an entity device of an oil leakage diagnosis and gas concentration compensation system for an oil and gas monitoring device provided in an embodiment of the present application. Specific embodiments

[0062] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular forms "a", "an", "the", "above-mentioned", "said", and "this" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0063] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0064] Next, an embodiment is used in combination with Figure 1 to describe a method for oil leakage diagnosis and gas concentration compensation of an oil and gas monitoring device in an embodiment of the present application:

[0065] Please refer to Figure 1 which is a schematic flowchart of a method for oil leakage diagnosis and gas concentration compensation of an oil and gas monitoring device in an embodiment of the present application.

[0066] S101. Obtain real-time data of the oil level height in the oil and gas monitoring device and historical oil level height data within a preset time period;

[0067] In this step, the system first obtains real-time data of the oil level height in the oil and gas monitoring device, and this real-time data reflects the oil level height situation in the oil and gas monitoring device at the current moment. At the same time, the system also needs to obtain historical oil level height data within a preset time period, and this historical data records the change situation of the oil level height in the oil and gas monitoring device over a past period of time. These data provide important basic information for subsequent oil leakage diagnosis and gas concentration compensation.

[0068] The system can obtain real-time data and historical data of the oil level height in various ways. For example, the system can use a liquid level sensor to directly measure the oil level height in the fuel tank and transmit the measurement results to the system in real time. In addition, the system can also read historical oil level height records from the monitoring system or database of the oil and gas monitoring equipment, which is not limited here.

[0069] S102. Calculate the standard fluctuation range of the oil level height based on the historical oil level height data;

[0070] The system calculates the standard fluctuation range of the oil level height based on the historical oil level height data. The upper limit value of the standard fluctuation range is the maximum value of the historical oil level height, and the lower limit value is the minimum value of the historical oil level height.

[0071] After obtaining the historical oil level height data within a preset time period, the system needs to calculate the standard fluctuation range of the oil level height based on these data. The standard fluctuation range reflects the fluctuation amplitude of the oil level height in the oil and gas monitoring equipment under normal operating conditions, and it provides an important reference basis for subsequent oil leakage diagnosis.

[0072] The system can adopt various statistical methods to calculate the standard fluctuation range. For example, calculate the mean and standard deviation of the historical data, and then determine the standard fluctuation range with the mean as the center and several standard deviations as the upper and lower limits. In addition, the system can also use other statistical indicators, such as quantiles, extreme values, etc., to describe the fluctuation characteristics of the oil level height.

[0073] When calculating the standard fluctuation range, the system may encounter problems such as insufficient historical data or low data quality, resulting in inaccurate calculation results. To solve this problem, the system can introduce machine learning algorithms, such as support vector machines, neural networks, etc., to establish a mathematical model of the oil level height fluctuation by training historical data, so as to more accurately predict the standard fluctuation range. At the same time, the system can also update the model regularly to adapt to the changes in the operating conditions of the oil and gas monitoring equipment.

[0074] S103. Obtain the real-time pressure data in the oil and gas monitoring equipment and calculate the theoretical oil level height based on the real-time pressure data;

[0075] The system obtains the real-time pressure data in the oil and gas monitoring equipment and calculates the theoretical oil level height based on the real-time pressure data. Specifically, obtain the current ambient atmospheric pressure value, the structural parameters of the oil and gas monitoring equipment, and the density parameters of the oil. The structural parameters include the cross-sectional area of the fuel tank and the height of the fuel tank; subtract the current ambient atmospheric pressure value from the real-time pressure data to obtain the relative pressure value; based on the hydrostatic principle, calculate the theoretical oil column height based on the relative pressure value, the cross-sectional area of the fuel tank, and the density parameters.

[0076] In this step, the system needs to obtain the real-time pressure data inside the oil and gas monitoring device, and calculate the theoretical oil level height based on the real-time pressure data. The theoretical oil level height refers to the theoretical value of the oil level height inside the oil and gas monitoring device under the current pressure conditions. By comparing it with the actually measured oil level height, it can be determined whether a leakage has occurred.

[0077] The system can obtain the real-time pressure data through the pressure sensor installed on the oil and gas monitoring device. While obtaining the pressure data, the system also needs to obtain the atmospheric pressure value of the current environment, the structural parameters of the fuel tank (such as cross-sectional area, height, etc.), and the density parameter of the oil. Based on these parameters, the system can calculate the theoretical oil level height according to the hydrostatic principle.

[0078] During the process of calculating the theoretical oil level height, the system may encounter problems such as pressure sensor failures or inaccurate parameters, resulting in deviations in the calculation results. To solve this problem, the system can use multiple pressure sensors for redundant measurement and improve the reliability of pressure measurement through data fusion algorithms. At the same time, the system can also regularly calibrate the structural parameters of the fuel tank and the oil density parameters to ensure the accuracy of the calculation results.

[0079] S104. Compare the real-time oil level height data, the theoretical oil level height with the standard fluctuation range. If the real-time oil level height data is lower than the lower limit value of the standard fluctuation range and the theoretical oil level height is higher than the upper limit value of the standard fluctuation range, it is determined that a leakage has occurred;

[0080] In this step, the system compares the real-time oil level height data, the theoretical oil level height with the standard fluctuation range to diagnose whether a leakage has occurred. Specifically, if the real-time oil level height data is lower than the lower limit value of the standard fluctuation range and the theoretical oil level height is higher than the upper limit value of the standard fluctuation range, the system determines that a leakage has occurred.

[0081] The principle of this diagnostic logic is that when a leakage occurs, the actual oil level height inside the fuel tank will be significantly lower than the normal fluctuation range, while the theoretical oil level height calculated based on the pressure will be higher than the normal fluctuation range. This is because the leakage will cause the pressure inside the fuel tank to drop, making the theoretical oil level height on the high side. By comparing the actual oil level height and the theoretical oil level height with the standard fluctuation range, the system can effectively determine whether a leakage has occurred.

[0082] S105. In the case of determining that a leakage has occurred, obtain the historical gas concentration data within a preset time period before the current moment, and use the historical gas concentration data as the reference gas concentration;

[0083] After determining that an oil leak has occurred, the system needs to obtain the historical gas concentration data within a preset time period before the current moment and use it as the reference gas concentration. This is because an oil leak will cause the rapid release of the gas dissolved in the oil, resulting in a change in the gas concentration in the gas space above the fuel tank. The historical gas concentration data reflects the normal level of the gas concentration before the oil leak and can be used as a reference basis for subsequent gas concentration compensation.

[0084] The system can obtain the historical gas concentration data from the online monitoring system or database of the oil-gas monitoring equipment. These data usually include the concentration values of various gas components (such as hydrogen, carbon monoxide, methane, etc.) in the gas space above the fuel tank, as well as information such as the measurement time. The system needs to select the corresponding historical data according to the preset time period (such as one day or one week before the oil leak).

[0085] S106. Obtain the real-time gas concentration data and calculate the attenuation rate of the real-time gas concentration data relative to the reference gas concentration;

[0086] The system obtains the real-time gas concentration data and calculates the attenuation rate of the real-time gas concentration data relative to the reference gas concentration. Specifically, it obtains the solubility coefficient and molecular mass parameters of different types of gases; calculates the dissolution equilibrium constant of each type of gas in the transformer oil according to the real-time pressure data and real-time temperature data; calculates the diffusion flux of each type of gas based on the dissolution equilibrium constant; calculates the mass of each type of gas escaping per unit time according to the gas diffusion flux; divides the mass of the gas escaping by the volume of the transformer oil to obtain the change in the concentration of each type of gas per unit time; calculates the monomer attenuation rate of each type of gas according to the change in concentration, where the monomer attenuation rate is equal to the ratio of the difference between the real-time gas concentration and the reference gas concentration to the product of the reference gas concentration and the gas attenuation duration; performs a weighted average calculation on the monomer attenuation rates of each type of gas to obtain the attenuation rate, and the weight coefficient of each type of gas is proportional to the corresponding gas molecular mass.

[0087] After obtaining the reference gas concentration, the system needs to obtain the gas concentration data at the current moment in real time and calculate the attenuation rate of the real-time gas concentration relative to the reference gas concentration. The attenuation rate reflects the release speed of the gas dissolved in the oil after the oil leak, and it is an important parameter for gas concentration compensation.

[0088] The system can obtain the concentration data of various gas components in the gas space above the fuel tank in real time through an on-line gas monitoring device. When obtaining the real-time gas concentration, the system also needs to obtain physical property parameters such as the solubility coefficient and molecular mass of various gas components, as well as state parameters such as the temperature and pressure of the oil in the fuel tank. Based on these parameters, the system can calculate the dissolution equilibrium constant of various gas components in the oil, and further calculate the diffusion flux and escape mass of the gas, and finally obtain the change amount of the gas concentration per unit time, that is, the attenuation rate.

[0089] In the process of calculating the attenuation rate, the system may encounter problems such as inaccurate physical property parameters or fluctuations in the fuel tank state parameters, resulting in deviations in the calculation results. To solve this problem, the system can establish a mathematical model of gas dissolution and diffusion, and use machine learning algorithms to train and optimize the model parameters, so as to improve the accuracy and adaptability of the attenuation rate calculation. At the same time, the system can also use the method of multi-point measurement and data fusion to reduce the influence of fuel tank state parameter fluctuations on the calculation results.

[0090] S107. Match the target attenuation coefficient corresponding to the target attenuation rate closest to the attenuation rate in the preset attenuation coefficient set;

[0091] After calculating the attenuation rate of the gas concentration, the system needs to match the target attenuation coefficient corresponding to the target attenuation rate closest to the attenuation rate in the preset attenuation coefficient set. The attenuation coefficient is an empirical parameter used to describe the relationship between the gas concentration attenuation rate and time, and it determines the amplitude and speed of gas concentration compensation.

[0092] The preset attenuation coefficient set is usually obtained through a large number of experiments and statistical analyses based on factors such as the model, capacity, and oil product type of the oil and gas monitoring device. The set contains a series of typical attenuation rate values and their corresponding attenuation coefficients. The system can compare the calculated attenuation rate with the attenuation rate values in the set, find the closest target attenuation rate, and obtain the corresponding target attenuation coefficient.

[0093] S108. Compensate the real-time gas concentration data according to the target attenuation coefficient to obtain the compensated gas concentration data.

[0094] After obtaining the target attenuation coefficient, the system can compensate the real-time gas concentration data according to this coefficient to obtain the compensated gas concentration data. The purpose of compensation is to correct the decrease in gas concentration caused by oil leakage, so that the gas concentration data can reflect the true content of the gas in the oil, and provide a reliable basis for the state assessment and fault diagnosis of the oil and gas monitoring device.

[0095] Specifically, the system can use the product of real-time gas concentration data and the target attenuation coefficient as the compensation amount, and then add the compensation amount to the real-time gas concentration data to obtain the compensated gas concentration data. The compensation process can adopt a sliding window method to dynamically update the compensation result according to the latest real-time gas concentration data and the target attenuation coefficient.

[0096] During the process of compensating the gas concentration data, the system may encounter problems such as the compensation amount being too large or too small, resulting in the compensated gas concentration data being distorted or losing its meaning. To solve this problem, the system can set upper and lower limits for the compensation amount, and when the compensation amount exceeds the limit, automatically adjust or truncate it. At the same time, the system can also introduce an adaptive algorithm to automatically optimize the target attenuation coefficient and compensation strategy according to the changes in the gas concentration data before and after compensation to ensure the accuracy and reliability of the compensation result.

[0097] In the above embodiments, by obtaining real-time data and historical data of the oil level height to establish a standard fluctuation range, and combining real-time pressure data to calculate the theoretical oil level height for comparison, the accuracy of identifying oil leakage can be improved. When oil leakage occurs, due to the decrease in the oil level, the dissolution gas escapes faster. By obtaining the historical gas concentration data before oil leakage as a reference, calculating the attenuation rate of the real-time gas concentration relative to the reference concentration, and matching the closest target attenuation coefficient in the preset attenuation coefficient set, the real-time gas concentration can be compensated, so that the gas concentration data can more accurately reflect the actual state of the oil and gas monitoring equipment. By establishing a dual judgment mechanism of the standard fluctuation range and the theoretical calculated value, the misjudgment probability is reduced; by selecting the compensation coefficient based on the actual attenuation rate, the compensation is more in line with the actual situation; by accurately compensating the gas concentration, the true value of the gas concentration monitoring value is improved, and thus the accuracy of gas concentration detection is improved.

[0098] The above embodiments mainly introduce the basic processes of oil leakage diagnosis and gas concentration compensation of oil and gas monitoring equipment, including key steps such as oil leakage identification and gas concentration compensation. In practical applications, in order to further improve the reliability of gas monitoring, it is also necessary to perform abnormal judgment and alarm processing on the compensated gas concentration data. The following combines Figure 2 , to describe an abnormal monitoring and alarm processing method for compensated gas concentration in the embodiments of the present application:

[0099] Please refer to Figure 2 , which is a schematic flow diagram of an abnormal monitoring and alarm processing method for compensated gas concentration in the embodiments of the present application.

[0100] S201. Obtain standard gas concentration thresholds under multiple preset working conditions;

[0101] The system obtains the standard gas concentration thresholds under multiple preset working conditions, and each preset working condition corresponds to a different combination of load level and environmental temperature.

[0102] In this step, the system needs to obtain the standard gas concentration thresholds under multiple preset working conditions. These thresholds are obtained through a large number of experiments and statistical analyses based on factors such as the model, capacity, and oil product type of the oil and gas monitoring equipment, and reflect the normal range of gas concentration of the oil and gas monitoring equipment under different operating conditions. Each preset working condition corresponds to a different combination of load level and environmental temperature, representing a typical scenario of the operation of the oil and gas monitoring equipment.

[0103] The system can obtain the standard gas concentration thresholds from the factory data or operation and maintenance manual of the oil and gas monitoring equipment. These thresholds are usually given in the form of tables or curves, and for different gas components (such as hydrogen, carbon monoxide, methane, etc.), the normal concentration upper limits under each preset working condition are specified. The system can also collect and analyze gas concentration data through the online monitoring system for a long time, and independently generate and optimize the standard gas concentration thresholds to adapt to the actual operating state of the oil and gas monitoring equipment.

[0104] S202. Determine the current working condition based on the preset working condition, the current load rate of the oil and gas monitoring equipment, and the current environmental temperature;

[0105] The system determines the current working condition based on the preset working condition, the current load rate of the oil and gas monitoring equipment, and the current environmental temperature, specifically including: comparing the current load rate of the oil and gas monitoring equipment with multiple preset load intervals to determine the target load interval where the current load rate is located; comparing the current environmental temperature with multiple preset temperature intervals to determine the target temperature interval where the current environmental temperature is located; determining the current working condition according to the combination of the target load interval and the target temperature interval and the preset working condition. The preset load intervals include a low load interval, a medium load interval, and a high load interval, the preset temperature intervals include a low temperature interval, a normal temperature interval, and a high temperature interval, and the preset working conditions are composed of any two intervals of the preset load interval and the preset temperature interval.

[0106] After obtaining the standard gas concentration thresholds, the system needs to determine the current working condition based on the preset working condition, the current load rate of the oil and gas monitoring equipment, and the current environmental temperature. The current working condition reflects the current operating state of the oil and gas monitoring equipment and is an important basis for judging abnormal gas concentration.

[0107] Specifically, the system first compares the current load rate of the oil and gas monitoring equipment with the preset load intervals (such as low load, medium load, high load) to determine the target load interval to which the current load rate belongs. At the same time, the system also compares the current ambient temperature with the preset temperature intervals (such as low temperature, normal temperature, high temperature) to determine the target temperature interval to which the current ambient temperature belongs. Then, based on the combination of the target load interval and the target temperature interval, the system finds the corresponding current operating condition in the preset operating conditions.

[0108] During the process of determining the current operating condition, the system may encounter problems where the current load rate or ambient temperature falls on the boundary of the preset interval or exceeds the preset interval range, resulting in an unclear definition of the current operating condition. To solve this problem, the system can use fuzzy logic or weighted average methods to comprehensively consider the membership degrees or weights of the current load rate and ambient temperature in adjacent intervals to determine the current operating condition. At the same time, the system can also introduce an adaptive algorithm to dynamically adjust the interval division of the preset operating conditions according to the historical operation data of the oil and gas monitoring equipment and the gas concentration change law, so as to improve the accuracy and sensitivity of the current operating condition judgment.

[0109] S203. Compare the compensated gas concentration data with the standard gas concentration threshold corresponding to the current operating condition;

[0110] After determining the current operating condition, the system needs to compare the compensated gas concentration data with the standard gas concentration threshold corresponding to the current operating condition to determine whether the gas concentration is abnormal.

[0111] Specifically, the system compares the compensated concentration value of each gas component with its standard concentration threshold under the current operating condition to determine whether the compensated concentration value exceeds the threshold. If the compensated concentration value does not exceed the threshold, it indicates that the concentration of this gas component is within the normal range; on the contrary, if the compensated concentration value exceeds the threshold, it indicates that the concentration of this gas component is abnormal and further analysis and processing are required.

[0112] During the process of comparing the compensated concentration with the threshold, the system may encounter problems such as unreasonable threshold settings or being too sensitive, resulting in normal gas concentration fluctuations triggering abnormal judgments. To solve this problem, the system can use the method of adaptive threshold, dynamically adjust the standard gas concentration threshold according to the operating state of the oil and gas monitoring equipment and the historical gas concentration data, so as to balance the sensitivity and reliability of abnormal judgments. At the same time, the system can also introduce a multi-parameter joint judgment mechanism to comprehensively consider the concentration change trends and mutual relationships of multiple gas components to improve the accuracy of abnormal judgments.

[0113] S204. If the compensated concentration data of any gas exceeds the corresponding standard gas concentration threshold, obtain the historical concentration change trend of the gas;

[0114] If the compensated concentration value of a certain gas component exceeds the standard threshold in the comparison of the previous step, the system needs to further obtain the historical concentration change trend of the gas to judge the nature and severity of the abnormal gas concentration.

[0115] The system can obtain the concentration data of the gas component for a period of time from the online monitoring system or the database and conduct trend analysis on it. By analyzing characteristic parameters such as the change rate, change amplitude, and fluctuation period of the gas concentration, the system can judge whether the abnormal gas concentration is an instantaneous anomaly caused by an emergency or a continuous anomaly caused by long-term accumulation. At the same time, the system can also judge the source and cause of the abnormal gas through correlation analysis with the concentrations of other gas components.

[0116] S205. When it is judged according to the historical concentration change trend that the gas concentration is continuously rising, trigger an alarm signal.

[0117] After obtaining the historical change trend of the gas concentration, the system needs to further judge whether the gas concentration is continuously rising. If the gas concentration shows a continuous rising trend, it indicates that there may be serious potential faults or abnormal operating states in the oil and gas monitoring equipment, and it is necessary to trigger an alarm signal in time to remind the operation and maintenance personnel to conduct inspections and handling.

[0118] Specifically, the system can judge whether it is in a continuously rising state by performing threshold judgment or slope test on the change rate of the gas concentration. For example, if the change rate of the gas concentration exceeds the preset rising rate threshold in multiple consecutive monitoring periods, or the slope of its linear fitting is significantly greater than zero, it can be determined that the gas concentration is in a continuously rising state. When this state is detected, the system immediately triggers an alarm signal and determines the alarm level according to the magnitude of the rising rate (such as general alarm, serious alarm, etc.).

[0119] In the above embodiments, by obtaining the standard gas concentration thresholds under multiple preset working conditions and determining the current working condition based on the current load rate and ambient temperature, the differentiation of gas concentration alarm judgment is realized. Compare the compensated gas concentration with the standard threshold of the corresponding working condition, and combine the historical concentration change trend of the gas. By considering the historical change trend, the short-term fluctuation influence of the gas concentration is filtered; by requiring the gas concentration to continuously rise before triggering an alarm, the reliability of the alarm is improved, thereby reducing the false alarm rate and improving the accuracy and timeliness of the alarm.

[0120] Further, after the alarm signal is triggered in step S205 of the above embodiments, the system can also collect data on the oil level, top oil temperature, and load current;

[0121] Extract the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics of the compensated gas concentration data;

[0122] Calculate the correlation coefficients of the compensation gas concentration with the oil level, top oil temperature, load current, and current ambient temperature respectively;

[0123] Judge the alarm reliability according to the combination of the correlation coefficients and the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics, specifically including:

[0124] Extract the periodic change component and the trend change component of the compensation gas concentration according to the combination of the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics;

[0125] When any one of the following conditions is met: the correlation coefficient of the compensation gas concentration with the oil level is greater than the first preset threshold and the daily change fluctuation characteristics meet the preset conditions; the correlation coefficient of the compensation gas concentration with the top oil temperature and the current ambient temperature is greater than the second preset threshold and the weekly change cycle characteristics are consistent with the temperature change cycle; the correlation coefficient of the compensation gas concentration with the load current is greater than the third preset threshold and the monthly change trend characteristics are consistent with the load change trend, set the alarm reliability to the first reliability;

[0126] When none of the above conditions are met and the trend change component is greater than the periodic change component, set the alarm reliability to the second reliability, and the second reliability is greater than the first reliability.

[0127] After triggering the abnormal gas concentration alarm, the system can further collect other relevant operation parameter data, such as the oil level, top oil temperature, load current, etc., and combine the change characteristics of the compensation gas concentration data to comprehensively judge the reliability of the alarm. This can effectively identify the gas concentration fluctuations caused by normal periodic changes or environmental factors and reduce the probability of false alarms.

[0128] Specifically, the system first needs to extract the daily change fluctuation characteristics, weekly change cycle characteristics, and monthly change trend characteristics of the compensation gas concentration data. The daily change fluctuation characteristics reflect the fluctuations of the gas concentration within a day and can be quantified by statistical indicators such as variance and peak-to-peak value. The weekly change cycle characteristics reflect the periodic change law of the gas concentration within a week and can be extracted by methods such as Fourier transform or autocorrelation analysis. The monthly change trend characteristics reflect the overall change trend of the gas concentration on a monthly scale and can be characterized by methods such as regression analysis or time series decomposition.

[0129] At the same time, the system also needs to calculate the correlation coefficients of the compensation gas concentration with other operation parameters (oil level, top oil temperature, load current, and ambient temperature) to measure the linear correlation between them. The value range of the correlation coefficient is [-1, 1], and the larger the absolute value, the stronger the correlation.

[0130] After extracting the change characteristics of gas concentration and calculating the correlation coefficient, the system can combine them to judge the reliability of the alarm. One judgment logic is as follows:

[0131] If the correlation coefficient between the compensated gas concentration and the oil level exceeds a preset threshold (such as 0.8), and the daily change fluctuation characteristics of the gas concentration meet the preset conditions (such as the variance is less than a certain threshold), it indicates that the abnormal gas concentration may be related to the change of the oil level, and the reliability of the alarm is relatively low;

[0132] If the correlation coefficient between the compensated gas concentration and the top oil temperature and the ambient temperature exceeds a preset threshold (such as 0.8), and the weekly change cycle characteristics of the gas concentration are consistent with the periodic change of the temperature, it indicates that the abnormal gas concentration may be related to the periodic fluctuation of the temperature, and the reliability of the alarm is also relatively low;

[0133] If the correlation coefficient between the compensated gas concentration and the load current exceeds a preset threshold (such as 0.8), and the monthly change trend characteristics of the gas concentration are consistent with the change trend of the load, it indicates that the abnormal gas concentration may be related to the change of the load, and the reliability of the alarm is also relatively low.

[0134] When one of the above three situations occurs, the system can set the alarm reliability to the first reliability level (such as low reliability). This prompts the operation and maintenance personnel that the abnormal gas concentration at this time may be caused by the normal change of the operating conditions and does not need to be overly concerned.

[0135] On the other hand, the system can further decompose the gas concentration data into periodic change components and trend change components. When the abnormal gas concentration alarm does not meet the above three situations and the trend change component is significantly greater than the periodic change component, it indicates that the increase in the gas concentration at this time is a long-term and continuous abnormal trend rather than a periodic fluctuation, and the reliability of the alarm is very high. At this time, the system can set the alarm reliability to the second reliability level (such as high reliability), prompting the operation and maintenance personnel to attach great importance and promptly check and handle potential fault hazards.

[0136] In the above embodiments, the oil level, top oil temperature and load current data are collected, the daily change fluctuation characteristics, weekly change cycle characteristics and monthly change trend characteristics of the compensated gas concentration data are extracted, and the correlation coefficients between the compensated gas concentration and each monitoring parameter are calculated. The law of gas concentration change can be comprehensively analyzed from multiple time scales and multiple relevant factors, and the gas abnormality caused by the equipment itself can be distinguished from the gas fluctuation caused by environmental factors and operating condition changes. By introducing the calculation of the correlation coefficient, the correlation degree between the gas concentration change and each influencing factor can be quantitatively characterized, providing an objective basis for alarm reliability evaluation, reducing the false alarm rate of the alarm, and improving the accuracy of fault diagnosis.

[0137] The following describes the system in the embodiments of the present invention application from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic structural diagram of an entity device of an oil leakage diagnosis and gas concentration compensation system for an oil and gas monitoring device provided in the embodiments of the present application.

[0138] It should be noted that Figure 3 The structure of the system shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0139] As Figure 3 shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage section 308 into the random access memory (RAM) 303, such as executing the methods in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0140] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD), a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. The drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that the computer program read from it can be installed into the storage section 308 as needed.

[0141] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are executed.

[0142] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. And in the present invention, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above.

[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this context, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or by a combination of dedicated hardware and computer instructions.

[0144] As another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist separately without being assembled into the system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a system, the system implements the method provided in the above embodiments.

[0145] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0146] As used in the above embodiments, depending on the context, the term "when..." may be interpreted as "if...", or "after...", or "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if detecting (the stated condition or event)" may be interpreted as "if determining...", or "in response to determining...", or "when detecting (the stated condition or event)", or "in response to detecting (the stated condition or event)".

[0147] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state drive), etc.

[0148] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware with a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The foregoing storage medium includes: various media that can store program codes such as ROM or random access memory RAM, magnetic disks, or optical discs.

Claims

1. A method for oil leakage diagnosis and gas concentration compensation of oil and gas monitoring equipment, characterized in that: include: Obtain real-time oil level data in oil and gas monitoring equipment and historical oil level data within a preset time period; Calculating a standard fluctuation range of the oil level based on the historical oil level data, wherein the upper limit of the standard fluctuation range is the maximum value of the historical oil level and the lower limit is the minimum value of the historical oil level; Acquire real-time pressure data in the oil and gas monitoring device, and calculate theoretical oil level height based on the real-time pressure data; Comparing the real-time data of the oil level height, the theoretical oil level height and the standard fluctuation range, if the real-time data of the oil level height is lower than the lower limit value of the standard fluctuation range and the theoretical oil level height is higher than the upper limit value of the standard fluctuation range, determining that an oil leak occurs; When it is determined that an oil leak has occurred, historical data of gas concentration within a preset time period before the current moment is obtained, and the historical data of gas concentration is used as a reference gas concentration; Acquiring real-time gas concentration data, and calculating a decay rate of the real-time gas concentration data relative to the reference gas concentration; Matching a target attenuation coefficient corresponding to a target attenuation rate closest to the attenuation rate in a preset attenuation coefficient set; The real-time gas concentration data is compensated according to the target attenuation coefficient to obtain compensated gas concentration data.

2. The method according to claim 1, characterized in that The calculating of the theoretical oil level height based on the real-time pressure data specifically includes: Acquire the current ambient atmospheric pressure value, the structural parameters of the oil and gas monitoring equipment and the density parameters of the oil, wherein the structural parameters include the cross-sectional area and height of the oil tank; Subtract the current ambient atmospheric pressure value from the real-time pressure data to obtain a relative pressure value; According to the static pressure principle, the theoretical oil column height is calculated based on the relative pressure value, the oil tank cross-sectional area, and the density parameter.

3. The method according to claim 1, characterized in that: The calculating the decay rate of the real-time gas concentration data relative to the reference gas concentration specifically includes: Obtain solubility coefficients and molecular mass parameters of different types of gases; Calculating the dissolution equilibrium constant of each type of gas in the oil and gas monitoring device according to the real-time pressure data and the real-time temperature data; Calculating the diffusion flux of each type of gas based on the dissolution equilibrium constant; Calculating the dissipated mass of each type of gas per unit time according to the gas diffusion flux; Dividing the gas escape mass by the volume of oil in the oil and gas monitoring device to obtain the concentration change of each type of gas per unit time; Calculating a monomer decay rate of each type of gas according to the concentration change, wherein the monomer decay rate is equal to the difference between the real-time gas concentration data and the reference gas concentration divided by the product of the reference gas concentration and the gas decay time; The monomer decay rates of each type of gas are weighted averaged to obtain the decay rate, and the weight coefficient of each type of gas is proportional to the molecular mass of the corresponding gas.

4. The method according to claim 1, characterized in that: After compensating the real-time gas concentration data according to the target attenuation coefficient to obtain compensated gas concentration data, the method further includes: Obtaining standard gas concentration thresholds under a plurality of preset working conditions, each of the preset working conditions corresponding to a different load level and ambient temperature combination; Determining a current operating condition based on the preset operating condition, a current load rate of the oil and gas monitoring device, and a current ambient temperature; Comparing the compensation gas concentration data with the standard gas concentration threshold corresponding to the current working condition; If the compensated concentration data of any gas exceeds the corresponding standard gas concentration threshold, the historical concentration change trend of the gas is obtained; When it is determined according to the historical concentration change trend that the concentration of the gas continues to rise, an alarm signal is triggered.

5. The method according to claim 4, characterized in that The determining of the current operating condition based on the preset operating condition, the current load rate of the oil and gas monitoring device and the current ambient temperature specifically includes: Comparing the current load rate of the oil and gas monitoring device with a plurality of preset load intervals to determine a target load interval in which the current load rate is located; Comparing the current ambient temperature with a plurality of preset temperature intervals to determine a target temperature interval in which the current ambient temperature is located; The current operating condition is determined based on a combination of the target load range and the target temperature range and the preset operating condition, wherein the preset load range includes a low load range, a medium load range and a high load range, the preset temperature range includes a low temperature range, a normal temperature range and a high temperature range, and the preset operating condition is composed of a combination of any two ranges of the preset load range and the preset temperature range.

6. The method according to claim 4, characterized in that When it is determined according to the historical concentration change trend that the concentration of the gas continues to rise, after triggering an alarm signal, the method further includes: Collect oil level, top oil temperature and load current data; Extracting daily fluctuation characteristics, weekly cycle characteristics and monthly trend characteristics of the compensation gas concentration data; respectively calculating correlation coefficients of the compensation gas concentration with the oil level, the top oil temperature, the load current and the current ambient temperature; The alarm reliability is determined based on a combination of the correlation coefficient and the daily variation fluctuation characteristics, the weekly variation cycle characteristics, and the monthly variation trend characteristics.

7. The method according to claim 6, characterized in that The determining of the alarm reliability according to the combination of the correlation coefficient and the daily change fluctuation feature, the weekly change cycle feature and the monthly change trend feature specifically includes: Extracting the periodic change component and the trend change component of the compensation gas concentration according to the combination of the daily change fluctuation feature, the weekly change period feature and the monthly change trend feature; When any one of the following conditions is met: the correlation coefficient between the compensation gas concentration and the oil level is greater than a first preset threshold and the daily variation fluctuation characteristic meets a preset condition; the correlation coefficient between the compensation gas concentration and the top oil temperature and the current ambient temperature is greater than a second preset threshold and the weekly variation cycle characteristic is consistent with the temperature variation cycle; and the correlation coefficient between the compensation gas concentration and the load current is greater than a third preset threshold and the monthly variation trend characteristic is consistent with the load variation trend, the alarm reliability is set to the first reliability; When neither condition is satisfied and the trend change component is greater than the periodic change component, the alarm reliability is set to a second reliability, which is greater than the first reliability.

8. An oil leakage diagnosis and gas concentration compensation system for oil and gas monitoring equipment, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to execute the method according to any one of claims 1 to 7.

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