An artificial intelligence-based transformer oil storage cabinet capsule air tightness monitoring system

Abstract

The present invention belongs to the technical field of air tightness monitoring, and discloses an artificial intelligence-based transformer oil storage cabinet capsule air tightness monitoring system, the system comprising a temperature information acquisition module, a pressure information acquisition module, a temperature anomaly analysis module, a gas flow anomaly analysis module, an air tightness analysis module, an air tightness change trend identification module, a monitoring result display module and a data storage library. The present invention analyzes the capsule air tightness index by analyzing the temperature anomaly and gas flow anomaly of the transformer oil storage cabinet capsule, and evaluates whether the capsule air tightness meets the standard based on the capsule air tightness index, and analyzes the air tightness change trend of the capsule for the situation where the air tightness does not meet the standard, effectively improving the efficiency of capsule air tightness monitoring, improving the authenticity and effectiveness of the monitoring results, avoiding possible safety accidents during the monitoring process, optimizing the accuracy and scientificity of the monitoring results, and at the same time improving the efficiency and accuracy of maintenance.

Description

Technical Field

[0001] The invention belongs to the technical field of air tightness monitoring, and relates to an artificial intelligence-based transformer oil storage cabinet capsule air tightness monitoring system. Background Art

[0002] The transformer oil conservator capsule is an important component of the transformer oil pillow. Its main function is to ensure that the transformer oil can expand and contract normally, while preventing the oil from direct contact with the outside world. If the capsule is not airtight, the transformer oil may enter the capsule, which may not only cause abnormal oil level, but also cause transformer oil to gush and overflow due to the increase in oil temperature. In addition, external gas may also enter the oil pillow to cause a false oil level, affecting the safe and stable operation of the transformer. Therefore, airtightness monitoring of the transformer oil conservator capsule can timely detect and solve potential airtightness problems and ensure the normal operation of the transformer.

[0003] The existing transformer oil storage cabinet capsule air tightness monitoring is mainly carried out by manually observing whether there is oil leakage inside the capsule. Another way is to inject gas into the capsule to pressurize it and analyze the pressure fluctuation characteristics to analyze the air tightness of the capsule. This monitoring method has the following shortcomings: 1. The existing transformer oil storage cabinet capsule air tightness monitoring method requires the transformer oil storage cabinet to be shut down before subsequent monitoring steps. This shutdown monitoring method reduces the operating efficiency, increases the monitoring cost, and increases the probability of safety accidents during the monitoring process. It cannot simulate the actual air tightness conditions during the operation of the machine, making the monitoring results unscientific.

[0004] 2. The existing transformer oil storage cabinet capsule air tightness monitoring mainly analyzes the air tightness by observing the air pressure changes. This monitoring method ignores the possible influence of external factors such as ambient temperature, which is easy to cause misidentification and cannot truly reflect the actual situation of the transformer oil storage cabinet capsule air tightness, reducing the accuracy of the monitoring results, weakening the scientificity and comprehensiveness of the monitoring results, and increasing the probability of safety accidents.

[0005] 3. The existing transformer oil storage cabinet capsule air tightness monitoring mainly analyzes whether there is an air tightness problem, but does not identify the specific location of the air tightness problem. This monitoring method makes it impossible to quickly locate the problem during maintenance work, increases the difficulty and time cost of troubleshooting, reduces the maintenance efficiency of maintenance personnel, and weakens the effectiveness of monitoring work. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence, including: a temperature information acquisition module, which is used to use an infrared imager to enter the capsule at each detection time point and scan the inner surface of the capsule to obtain a thermal image of the inner surface of the capsule, and then analyze the temperature distribution in the capsule at each detection time point.

[0008] The pressure information acquisition module is used to set a pressure sensor in the capsule to collect the pressure information in the capsule and obtain the pressure value in the capsule at each detection time point.

[0009] The temperature anomaly analysis module is used to compare the pressure value in the capsule at each detection time point with the temperature and pressure correspondence table under normal conditions stored in the data storage library, obtain the normal temperature in the capsule at each detection time point, and compare it with the temperature distribution in the capsule at each detection time point, and then analyze the temperature anomaly at each detection time point, and identify the temperature anomaly location and the frequency of occurrence of each temperature anomaly location.

[0010] The gas flow anomaly analysis module is used to set a gas flow detection device in the pipeline connecting the respirator and the capsule and use the gas flow detection device to detect the gas flow during the capsule exhaust process. At the same time, a pressure sensor and an infrared imager are used to detect pressure changes and temperature changes, thereby analyzing the gas flow of the pipeline under normal circumstances, and based on this, analyzing the gas flow abnormality.

[0011] The air tightness analysis module is used to analyze the capsule air tightness index based on the analyzed abnormality of the pressure inside the capsule and the abnormality of the gas flow.

[0012] The air tightness change trend identification module is used to evaluate whether the air tightness meets the standard based on the capsule air tightness index. When the air tightness is judged to be not up to the standard, the air tightness change trend of the capsule is identified based on the temperature abnormality at each detection time point.

[0013] The monitoring result display module is used to display the abnormal temperature position, capsule air tightness index and capsule air tightness change trend on the display terminal.

[0014] The data repository is used to store the temperature value corresponding to each chromaticity in the thermal image and the corresponding relationship table between temperature and pressure under normal conditions.

[0015] In a preferred embodiment of the present invention, the steps of analyzing the temperature distribution in the capsule at each detection time point are as follows: setting a monitoring period, taking a number of time points with equal time intervals within the monitoring period, and taking each time point as a detection time point.

[0016] The distribution position and chromaticity value corresponding to each temperature zone are extracted from the thermal image of the inner surface of the capsule at each detection time point.

[0017] Match the chromaticity value corresponding to each temperature zone with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature of each temperature zone corresponding to each detection time point ,in Indicates the detection time point number, , Indicates the temperature zone number, .

[0018] In a preferred embodiment of the present invention, the analysis of the temperature anomaly at each detection time point is specifically as follows: the temperature of each temperature zone corresponding to each detection time point The normal temperature in the capsule at each testing time point Substitute into the analysis formula Get the temperature anomaly of each temperature zone corresponding to each detection time point ,in Represents a natural constant.

[0019] The temperature anomaly coefficient values ​​of each temperature zone corresponding to each detection time point are compared, and the maximum temperature anomaly coefficient value is selected as the temperature anomaly coefficient of the detection time point.

[0020] In a preferred embodiment of the present invention, the steps of identifying the temperature anomaly positions and the frequency of occurrence of each temperature anomaly position are as follows: the temperature anomaly degree corresponding to each temperature zone at each detection time point obtained by analysis is compared with the allowable temperature anomaly degree set in advance. When the temperature anomaly degree corresponding to a temperature zone at a certain detection time point is greater than the allowable temperature anomaly degree set in advance, the distribution position corresponding to the temperature zone is used as the temperature anomaly position corresponding to the detection time point.

[0021] The temperature anomaly positions corresponding to each detection time point are counted, and then each temperature anomaly position is classified. The occurrence frequency corresponding to each temperature anomaly position is counted, and each temperature anomaly position is arranged from large to small according to the frequency of occurrence, which is then used as the basis for subsequent maintenance operations by staff.

[0022] In a preferred embodiment of the present invention, the pressure change and temperature change detection and analysis using the pressure sensor and the infrared imager are as follows: the pressure sensor is used to obtain the pressure value inside the capsule at the start time point corresponding to the capsule exhaust and the pressure value inside the capsule at the end time point, and then the pressure value inside the capsule at the end time point and the pressure value inside the capsule at the start time point are calculated by difference to obtain the pressure change value inside the capsule during the monitoring period. .

[0023] The inner surface of the capsule is scanned by using the set infrared imager, and then the thermal image of the capsule exhaust corresponding to the starting time point and the thermal image of the end time point is obtained.

[0024] The contours of each temperature region are extracted from the thermal image at the starting time point to obtain the area corresponding to the contours of each temperature region, and the chromaticity value of each temperature region is matched with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region.

[0025] The area of ​​each temperature zone corresponding to the thermal image at the starting time point and the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the starting time of capsule exhaust ,in Represents the inner surface area of ​​the capsule.

[0026] The contours of each temperature region are extracted from the thermal image at the end time point to obtain the area corresponding to the contours of each temperature region, and the chromaticity value of each temperature region is matched with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region.

[0027] Correspond the thermal image at the end time point to the area of ​​each temperature zone and the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the end time of capsule exhaust .

[0028] The temperature change value inside the capsule corresponding to the capsule exhaust is obtained by calculating the difference between the temperature value inside the capsule at the end time of the capsule exhaust and the temperature value inside the capsule at the start time of the capsule exhaust. .

[0029] In a preferred embodiment of the present invention, the steps of analyzing the gas flow rate of the pipeline under normal conditions are as follows: the pressure change value corresponding to the capsule exhaust process and temperature changes Substitute into the analysis formula Get the gas flow rate of the pipeline under normal conditions during the capsule exhaust process ,in represents the mass of gas, is the gas constant.

[0030] In a preferred embodiment of the present invention, the analysis of gas flow abnormality is specifically as follows: the gas flow rate of the pipeline corresponding to the normal condition during the capsule exhaust process and the gas flow rate detected by the gas flow detection device Substitute into the formula Get the corresponding gas flow anomaly during the capsule exhaust process .

[0031] In a preferred embodiment of the present invention, the analysis of the capsule air tightness index is as follows: the abnormal temperature of the capsule at each detection time point and the abnormality of gas flow during capsule exhaust Substitute into the analysis formula Get the airtightness index of the transformer oil conservator capsule ,in They represent the weights corresponding to the temperature anomaly and the gas flow anomaly, Indicates the number of detection time points.

[0032] In a preferred embodiment of the present invention, the evaluation of whether the air tightness meets the standard is analyzed as follows: the air tightness index of the transformer oil storage cabinet capsule obtained by analysis is Substitute into the airtightness judgment model The judgment result of whether the air tightness of the transformer oil storage cabinet meets the standard is obtained. It indicates that the air tightness of the transformer oil storage cabinet capsule meets the standard. It means that the air tightness of the transformer oil storage cabinet capsule does not meet the standard. Indicates the preset airtightness compliance index.

[0033] In a preferred embodiment of the present invention, the steps for identifying the air tightness change trend of the capsule are as follows: a two-dimensional coordinate system is constructed with the detection time point as the horizontal coordinate and the temperature anomaly as the vertical coordinate, and several points are marked in the constructed two-dimensional coordinate system corresponding to each temperature anomaly at each detection time point to form a capsule air tightness change curve.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention collects the temperature and pressure information in the capsule corresponding to the exhaust operation of the transformer oil storage cabinet by using a temperature sensor and a pressure sensor, and then analyzes the air tightness status of the capsule. This non-stop monitoring method can fully reflect the air tightness of the capsule in the actual working state, thereby improving the authenticity and effectiveness of the monitoring results; on the other hand, it can monitor the working state of the capsule in real time, thereby improving the timeliness of monitoring and the monitoring efficiency; on the other hand, the non-stop monitoring method reduces the expenditure due to additional expenses and avoids possible safety accidents during the monitoring process.

[0035] (2) The present invention comprehensively analyzes the air tightness of the capsule under static working state and gas flow working state, and comprehensively considers external influencing factors such as temperature and pressure. The analysis results obtained by this analysis method can accurately reflect the actual air tightness status of the transformer oil conservator capsule, thereby improving the accuracy and scientificity of the monitoring results; at the same time, the comprehensive analysis of the working status can avoid the accident risks caused by inaccurate monitoring results to the greatest extent, thereby improving the safety of the transformer oil conservator capsule.

[0036] (3) The present invention analyzes the temperature anomaly of the temperature zone at each detection time point and compares it with the pre-set allowable temperature anomaly to further analyze the specific location where the airtightness problem may occur. This monitoring method avoids blind inspection and repair of the entire system, improves the efficiency and accuracy of maintenance, and reduces maintenance costs. At the same time, accurately locating the temperature anomaly location helps to promptly discover and resolve potential safety hazards, reducing the risk of safety accidents caused by airtightness problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1 As shown, the present invention provides a transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence, including a temperature information acquisition module, a pressure information acquisition module, a temperature anomaly analysis module, a gas flow anomaly analysis module, an air tightness analysis module, an air tightness change trend identification module, a monitoring result display module and a data storage library, wherein the temperature information acquisition module and the pressure information acquisition module are both connected to the temperature anomaly analysis module, the temperature anomaly analysis module and the gas flow anomaly analysis module are both connected to the air tightness analysis module, the temperature anomaly analysis module and the air tightness analysis module are both connected to the air tightness change trend identification module, the temperature anomaly analysis module, the air tightness analysis module and the air tightness change trend identification module are all connected to the monitoring result display module, and the data storage library is respectively connected to the temperature information acquisition module and the temperature anomaly analysis module.

[0041] The temperature information acquisition module is used to use an infrared imager to enter the capsule and scan the inner surface of the capsule at each detection time point to obtain a thermal image of the inner surface of the capsule, and then analyze the temperature distribution in the capsule at each detection time point.

[0042] Preferably, a monitoring period is set, and several time points with equal time intervals are selected within the monitoring period, and each time point is used as a detection time point.

[0043] The distribution position and chromaticity value corresponding to each temperature zone are extracted from the thermal image of the inner surface of the capsule at each detection time point.

[0044] Match the chromaticity value corresponding to each temperature zone with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature of each temperature zone corresponding to each detection time point ,in Indicates the detection time point number, , Indicates the temperature zone number, .

[0045] It should be noted that the reason for selecting an infrared thermal imager to collect the temperature distribution information on the capsule surface is: first, the infrared imager can obtain thermal images, which can intuitively display the temperature distribution on the capsule surface, so that maintenance personnel can quickly identify abnormal temperature points or areas, which helps to timely discover potential thermal faults or problems, so as to take corresponding measures to repair or adjust them; secondly, thermal image analysis can provide detailed information on the temperature distribution of the capsule, including the highest temperature, the lowest temperature, and the temperature gradient, etc. This information helps to evaluate the working status of the capsule and determine whether it is within the normal working range. Through long-term monitoring and analysis, it is also possible to understand the changing trend of the capsule temperature distribution and predict its future performance; in addition, thermal image analysis also has the characteristics of non-contact, real-time and high resolution. Compared with traditional temperature measurement methods, thermal image analysis does not require direct contact with the capsule, avoiding potential measurement errors and damage risks. At the same time, it can obtain the temperature distribution data of the capsule in real time, so that maintenance personnel can timely understand the working status of the capsule. High-resolution thermal images can also provide more detailed temperature information, which helps to find smaller temperature anomalies.

[0046] The pressure information acquisition module is used to set a pressure sensor in the capsule, thereby acquiring the pressure information in the capsule, and then obtaining the pressure value in the capsule at each detection time point.

[0047] It should be noted that, considering the particularity of the air tightness of the transformer oil storage cabinet capsule, the selected pressure sensor can be a patch pressure sensor.

[0048] The temperature anomaly analysis module is used to compare the pressure value in the capsule at each detection time point with the temperature and pressure correspondence table under normal conditions stored in the data storage library, as shown in Table 1, to obtain the normal temperature in the capsule at each detection time point, and compare it with the temperature distribution in the capsule at each detection time point, and then analyze the temperature anomaly at each detection time point, and identify the temperature anomaly position and the frequency of occurrence of each temperature anomaly position.

[0049] Table 1

[0050]

[0051] It should be noted that the correlation between temperature and pressure mainly stems from the thermal motion of gas molecules. Temperature is a sign of the average kinetic energy of the thermal motion of the molecules of an object, and it reflects the intensity of the molecular motion. Pressure is the vertical force per unit area, and it is related to the collision of molecules with the container wall. When the temperature rises, the thermal motion of the gas or liquid molecules intensifies, and the average kinetic energy of the molecules increases, resulting in more frequent and intense collisions between molecules, thereby increasing the impact force on the container wall, that is, the pressure increases.

[0052] Preferably, each detection time point corresponds to the temperature of each temperature zone. The normal temperature in the capsule at each testing time point Substitute into the analysis formula Get the temperature anomaly of each temperature zone corresponding to each detection time point ,in Represents a natural constant.

[0053] It should be noted that the present invention collects the temperature and pressure information in the capsule corresponding to the exhaust operation of the transformer oil storage cabinet by using a temperature sensor and a pressure sensor, and then analyzes the air tightness status of the capsule. This non-stop monitoring method can fully reflect the air tightness of the capsule in the actual working state, thereby improving the authenticity and effectiveness of the monitoring results; on the other hand, it can monitor the working state of the capsule in real time, thereby improving the timeliness of monitoring and improving the monitoring efficiency; on the other hand, the non-stop monitoring method reduces the expenditure due to additional expenses and avoids possible safety accidents during the monitoring process.

[0054] The temperature anomalies of each temperature zone corresponding to each detection time point are compared, and the maximum temperature anomaly is selected as the temperature anomaly of the detection time point.

[0055] It should be noted that the maximum temperature abnormality is selected as the temperature abnormality at the detection time point because: first, the maximum temperature abnormality can directly reflect the extreme temperature changes during the monitoring process, so that management personnel can promptly discover potential air tightness problems; in addition, the change in temperature during air tightness monitoring may be affected by many factors, such as ambient temperature and equipment operating status. Selecting the maximum temperature abnormality can reduce the non-display impact caused by these factors, and the maximum temperature is least affected. When the maximum temperature abnormality is lower than the allowable temperature abnormality, it means that all temperature abnormalities are lower than the allowable temperature abnormality, thereby improving the accuracy and reliability of monitoring.

[0056] Preferably, the temperature anomaly corresponding to each temperature zone at each detection time point obtained by analysis is compared with the allowable temperature anomaly set in advance. When the temperature anomaly corresponding to a temperature zone at a detection time point is greater than the allowable temperature anomaly set in advance, the distribution position corresponding to the temperature zone is used as the temperature anomaly position corresponding to the detection time point.

[0057] Exemplarily, the allowable temperature anomaly degree may be 0.15.

[0058] It should be noted that temperature anomalies are directly related to the air tightness of the capsule. Specifically, when there is a problem with the air tightness of the capsule, such as slight damage or leakage, the oil in the oil storage tank may be exchanged with the external environment, resulting in a reduction in the amount of oil and causing changes in the oil temperature. Especially when the external temperature is significantly different from the internal temperature of the oil storage tank, leakage will cause obvious temperature fluctuations, which will manifest as temperature anomalies.

[0059] The temperature anomaly positions corresponding to each detection time point are counted, and then each temperature anomaly position is classified. The occurrence frequency corresponding to each temperature anomaly position is counted, and each temperature anomaly position is arranged from large to small according to the frequency of occurrence, which is then used as the basis for subsequent maintenance operations by staff.

[0060] It needs to be explained that the frequency of occurrence of abnormal temperature positions has a direct impact on the air tightness of the abnormal position. If the abnormal temperature position appears frequently, it is likely to point to a specific fault area, which helps maintenance personnel to quickly find the problem, reduce the time for troubleshooting, and improve maintenance efficiency. On the other hand, the higher the frequency of occurrence of abnormal temperature positions, the more serious the fault. Frequent temperature abnormalities may indicate that there is a large damage or leakage in the capsule, which requires emergency treatment to prevent the fault from further expanding.

[0061] It should be further explained that the present invention analyzes the temperature anomaly of the temperature zone at each detection time point and compares it with the pre-set allowable temperature anomaly to further analyze the specific location where the airtightness problem may occur. This monitoring method avoids blind troubleshooting and repair of the entire system, improves the efficiency and accuracy of maintenance, and reduces maintenance costs. At the same time, accurately locating the temperature anomaly position helps to promptly discover and resolve potential safety hazards, reducing the risk of safety accidents caused by airtightness problems.

[0062] The gas flow anomaly analysis module is used to set a gas flow detection device in the pipeline connecting the respirator and the capsule and use the gas flow detection device to detect the gas flow during the capsule exhaust process. At the same time, a pressure sensor and an infrared imager are used to detect pressure changes and temperature changes, thereby analyzing the gas flow of the pipeline under normal circumstances, and based on this, analyzing the gas flow abnormality.

[0063] Preferably, the pressure sensor is used to obtain the pressure value inside the capsule at the start time point and the pressure value inside the capsule at the end time point corresponding to the capsule exhaust, and then the pressure value inside the capsule at the end time point and the pressure value inside the capsule at the start time point are calculated by difference to obtain the pressure change value inside the capsule during the monitoring period. .

[0064] The inner surface of the capsule is scanned by using the set infrared imager, and then the thermal image of the capsule exhaust corresponding to the starting time point and the thermal image of the end time point is obtained.

[0065] The contours of each temperature region are extracted from the thermal image at the starting time point to obtain the area corresponding to the contours of each temperature region, and the chromaticity value of each temperature region is matched with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region.

[0066] The area of ​​each temperature zone corresponding to the thermal image at the starting time point and the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the starting time of capsule exhaust ,in Represents the inner surface area of ​​the capsule.

[0067] The contours of each temperature region are extracted from the thermal image at the end time point to obtain the area corresponding to the contours of each temperature region, and the chromaticity value of each temperature region is matched with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region.

[0068] Correspond the thermal image at the end time point to the area of ​​each temperature zone and the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the end time of capsule exhaust .

[0069] The temperature change value inside the capsule corresponding to the capsule exhaust is obtained by calculating the difference between the temperature value inside the capsule at the end time of the capsule exhaust and the temperature value inside the capsule at the start time of the capsule exhaust. .

[0070] Further preferably, the pressure change value corresponding to the capsule exhaust process and temperature changes Substitute into the analysis formula Get the gas flow rate of the pipeline under normal conditions during the capsule exhaust process ,in represents the mass of gas, is the gas constant.

[0071] It should be added that, under ideal conditions, the transformer oil storage cabinet capsule has good airtightness, and the gas only enters and exits the capsule through the respirator, so that the change in gas volume can be detected at the breathing point. When the external temperature or the oil storage cabinet pressure changes, the capsule needs to exchange gas through the respirator in order to balance the air pressure, which is specifically manifested as a change in the capsule volume.

[0072] It should be noted that the above , .

[0073] Further preferably, the gas flow rate of the pipeline in the normal condition during the capsule exhaust process is and the gas flow rate detected by the gas flow detection device Substitute into the formula Get the corresponding gas flow anomaly during the capsule exhaust process .

[0074] It should be noted that the reason for choosing gas flow abnormality as an influencing factor of capsule air tightness is: first, if the air tightness of the capsule is good, the gas flow in the transformer oil pillow should be maintained within a stable range. When the gas flow increases abnormally, this may indicate that the capsule is damaged or leaking, causing external air to enter the oil pillow, or the insulating oil in the oil pillow leaks into the external environment. This situation will not only affect the normal operation of the transformer, but may also cause a series of safety problems; secondly, the abnormal decrease in gas flow may also be related to the air tightness of the capsule. If blockage or adhesion occurs inside the capsule, the gas may not flow normally.

[0075] The air tightness analysis module is used to analyze the capsule air tightness index based on the analyzed abnormality of the pressure inside the capsule and the abnormality of the gas flow.

[0076] Preferably, the abnormal temperature of the capsule at each detection time point is and the abnormality of gas flow during the capsule exhaust process Substitute into the analysis formula Get the airtightness index of the transformer oil conservator capsule ,in They represent the weights corresponding to the temperature anomaly and the gas flow anomaly, Indicates the number of detection time points.

[0077] As a preferred example of the above scheme, .

[0078] It should be noted that the present invention comprehensively analyzes the air tightness of the capsule in a static working state and a gas flow working state, and comprehensively considers external influencing factors such as temperature and pressure. The analysis result obtained by this analysis method can accurately reflect the real air tightness state of the transformer oil conservator capsule, and improves the accuracy and scientificity of the monitoring result; at the same time, the comprehensive analysis of the working state can avoid the accident risk caused by inaccurate monitoring results to the greatest extent, thereby improving the safety of the transformer oil conservator capsule.

[0079] The air tightness change trend identification module is used to evaluate whether the air tightness meets the standard based on the capsule air tightness index. When the air tightness is judged to be not up to the standard, the air tightness change trend of the capsule is identified based on the temperature abnormality at each detection time point.

[0080] Preferably, the air tightness index of the transformer oil storage cabinet capsule obtained by analysis is Substitute into the airtightness judgment model The judgment result of whether the air tightness of the transformer oil storage cabinet meets the standard is obtained. It indicates that the air tightness of the transformer oil storage cabinet capsule meets the standard. It means that the air tightness of the transformer oil storage cabinet capsule does not meet the standard. Indicates the preset airtightness compliance index.

[0081] For example, .

[0082] Preferably, a two-dimensional coordinate system is constructed with the detection time point as the horizontal coordinate and the temperature anomaly as the vertical coordinate, and several points are marked in the constructed two-dimensional coordinate system for each detection time point corresponding to each temperature anomaly to form a capsule airtightness change curve.

[0083] It should be noted that the air tightness change curve is drawn because: first, drawing the air tightness change curve is more intuitive. The air tightness change curve can intuitively show the changes in the capsule air tightness over time. Through the trend of the curve, it is possible to quickly determine whether the air tightness is stable, whether there are abnormal fluctuations or a downward trend; secondly, by observing the trend of the curve, the change trend of the capsule air tightness can be analyzed and its future changes can be predicted, which helps to timely discover potential air tightness problems and take corresponding maintenance measures; thirdly, when the capsule air tightness is abnormal, the change curve can help locate the time point or stage when the problem occurs. By comparing the curves of different time periods, the starting point or acceleration point of the air tightness decline can be found, thereby determining the area that needs to be focused on; finally, by monitoring and analyzing the capsule air tightness change curve, a reasonable threshold or alarm mechanism can be set. When the curve exceeds the set threshold, the system will automatically issue an alarm to remind maintenance personnel to deal with it in time to prevent the fault from expanding.

[0084] The monitoring result display module is used to display the temperature abnormality position, the capsule air tightness index and the capsule air tightness change trend on the display terminal.

[0085] The data storage repository is used to store the temperature value corresponding to each chromaticity in the thermal image and store the corresponding relationship table between temperature and pressure under normal conditions.

[0086] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence, characterized in that: The system includes: The temperature information acquisition module is used to use an infrared imager to enter the capsule and scan the inner surface of the capsule at each detection time point to obtain a thermal image of the inner surface of the capsule, and then analyze the temperature distribution in the capsule at each detection time point; A pressure information acquisition module is used to set a pressure sensor in the capsule to collect pressure information in the capsule and obtain the pressure value in the capsule at each detection time point; The temperature anomaly analysis module is used to compare the pressure value in the capsule at each detection time point with the temperature and pressure correspondence table under normal conditions stored in the data storage library, obtain the normal temperature in the capsule at each detection time point, and compare it with the temperature distribution in the capsule at each detection time point, and then analyze the temperature anomaly at each detection time point, and identify the temperature anomaly position and the frequency of occurrence of each temperature anomaly position; A gas flow anomaly analysis module is used to set a gas flow detection device in the pipeline connecting the respirator and the capsule and use the gas flow detection device to detect the gas flow during the capsule exhaust process, and use a pressure sensor and an infrared imager to detect pressure changes and temperature changes, thereby analyzing the gas flow of the pipeline under normal conditions, and based on this, analyzing the gas flow anomaly; An air tightness analysis module, used to analyze the capsule air tightness index based on the analyzed abnormal temperature and gas flow in the capsule; The air tightness change trend identification module is used to evaluate whether the air tightness meets the standard based on the capsule air tightness index. If the air tightness does not meet the standard, the air tightness change trend of the capsule is identified based on the temperature abnormality at each detection time point. A monitoring result display module is used to display the abnormal temperature position, capsule air tightness index and capsule air tightness change trend on a display terminal; A data repository, used to store the temperature values ​​corresponding to each chromaticity in the thermal image and the corresponding relationship table between temperature and pressure under normal conditions; The steps of analyzing the temperature distribution in the capsule at each detection time point are as follows: Set the monitoring period, select a number of time points with equal time intervals within the monitoring period, and use each time point as the detection time point; Extract the distribution position and chromaticity value corresponding to each temperature area from the thermal image of the inner surface of the capsule at each detection time point; Match the chromaticity value corresponding to each temperature zone with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature of each temperature zone corresponding to each detection time point ,in Indicates the detection time point number, , Indicates the temperature zone number, ; The analysis of the temperature anomaly at each detection time point is as follows: Correspond each detection time point to the temperature of each temperature zone The normal temperature in the capsule at each testing time point Substitute into the analysis formula Get the temperature anomaly of each temperature zone corresponding to each detection time point ,in represents a natural constant; Compare the temperature anomaly of each temperature zone corresponding to each detection time point, and then select the maximum temperature anomaly as the temperature anomaly of the detection time point; The steps for analyzing the gas flow rate of the pipeline under normal conditions are as follows: The pressure change value corresponding to the capsule exhaust process and temperature changes Substitute into the analysis formula Get the gas flow rate of the pipeline under normal conditions during the capsule exhaust process ,in represents the mass of gas, is the gas constant; The analysis gas flow abnormality is specifically as follows: The gas flow rate of the pipeline under normal conditions during the capsule exhaust process and the gas flow rate detected by the gas flow detection device Substitute into the formula Get the corresponding gas flow anomaly during the capsule exhaust process ; The analysis capsule air tightness index is specifically as follows: The temperature anomaly of the capsule at each detection time point and the abnormality of gas flow during the capsule exhaust process Substitute into the analysis formula Get the airtightness index of the transformer oil conservator capsule ,in They represent the weights corresponding to the temperature anomaly and the gas flow anomaly, Indicates the number of detection time points.

2. The transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence as claimed in claim 1 is characterized by: The steps of identifying the temperature abnormality locations and the occurrence frequency of each temperature abnormality location are as follows: The temperature anomaly degree of each temperature zone corresponding to each detection time point obtained by analysis is compared with the pre-set allowable temperature anomaly degree. When the temperature anomaly degree of a temperature zone corresponding to a detection time point is greater than the pre-set allowable temperature anomaly degree, the distribution position corresponding to the temperature zone is used as the temperature anomaly position corresponding to the detection time point; The temperature anomaly positions corresponding to each detection time point are counted, and then each temperature anomaly position is classified. The occurrence frequency corresponding to each temperature anomaly position is counted, and each temperature anomaly position is arranged from large to small according to the frequency of occurrence, which is then used as the basis for subsequent maintenance operations by staff.

3. The transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence as claimed in claim 2 is characterized by: The pressure change and temperature change detection and analysis using the pressure sensor and infrared imager are as follows: The pressure sensor is used to obtain the pressure value inside the capsule at the start time point and the end time point corresponding to the capsule exhaust, and then the pressure value inside the capsule at the end time point and the pressure value inside the capsule at the start time point are calculated to obtain the pressure change value inside the capsule during the monitoring period. ; The inner surface of the capsule is scanned by using the set infrared imager, so as to obtain the thermal image of the capsule exhaust corresponding to the start time point and the thermal image of the end time point; Extract the contours of each temperature region from the thermal image at the starting time point to obtain the area corresponding to the contours of each temperature region, and match the chromaticity value of each temperature region with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region; The area of ​​each temperature zone corresponding to the thermal image at the starting time point And the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the starting time of capsule exhaust ,in represents the inner surface area of ​​the capsule; Extract the contours of each temperature region from the thermal image at the end time point to obtain the area corresponding to the contours of each temperature region, and match the chromaticity value of each temperature region with the temperature value corresponding to each chromaticity in the thermal image to obtain the temperature value corresponding to each temperature region; Correspond the thermal image at the end time point to the area of ​​each temperature zone And the corresponding temperature value Substitute into the formula Get the temperature value inside the capsule at the end time of capsule exhaust ; The temperature change value inside the capsule corresponding to the capsule exhaust is obtained by calculating the difference between the temperature value inside the capsule at the end time of the capsule exhaust and the temperature value inside the capsule at the start time of the capsule exhaust. .

4. The transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence as claimed in claim 1 is characterized by: The analysis of whether the air tightness meets the standard is as follows: The air tightness index of the transformer oil conservator capsule obtained by analysis Substitute into the airtightness judgment model The judgment result of whether the air tightness of the transformer oil storage cabinet meets the standard is obtained. It indicates that the air tightness of the transformer oil storage cabinet capsule meets the standard. It means that the air tightness of the transformer oil storage cabinet capsule does not meet the standard. Indicates the preset airtightness compliance index.

5. The transformer oil storage cabinet capsule air tightness monitoring system based on artificial intelligence as claimed in claim 1 is characterized by: The steps of identifying the change trend of the air tightness of the capsule are as follows: A two-dimensional coordinate system is constructed with the detection time point as the horizontal coordinate and the temperature anomaly as the vertical coordinate. Several points are marked in the constructed two-dimensional coordinate system corresponding to each temperature anomaly at each detection time point to form a capsule airtightness change curve.

Images