Transformer health state assessment method and system, electronic equipment and storage medium

Abstract

The invention provides a transformer health state evaluation method and system, electronic equipment and a storage medium, and relates to the technical field of electric power, the method comprises the following steps: obtaining a transformer oil sample, and degassing the transformer oil sample to obtain a group of to-be-detected gases; introducing a group of to-be-detected gases into the detection pool; a group of excitation light sources are respectively used for irradiating the detection pool to excite a group of to-be-detected gases to generate a photoacoustic effect and convert a photoacoustic signal into a target electric signal, and the first laser light source is used for emitting a mid-infrared laser signal of a first wavelength matched with acetylene; the second laser light source is used for emitting near-infrared laser signals with different wavelengths matched with other gases in a time-sharing manner; obtaining a group of first detection results of the to-be-detected gas based on the target electric signal; and evaluating the health state of the transformer according to the first detection result. By implementing the technical scheme provided by the invention, the purpose of accurately evaluating the health state of the transformer is achieved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a method, system, electronic device and storage medium for evaluating the health status of a transformer. Background Art

[0002] When the transformer is in normal operation, the oil and solid insulation will gradually age and deteriorate, and decompose a very small amount of gas (mainly including hydrogen H2, methane CH4, ethane C2H6, ethylene C2H4, acetylene C2H2, carbon monoxide CO, carbon dioxide CO2 and other gases). When an overheating fault, discharge fault or internal insulation of the transformer occurs, the content of these gases will increase rapidly. Most of these gases are dissolved in the insulating oil. Experience has shown that the content of various components of the gas in the oil is directly related to the nature and degree of the fault. Therefore, during the operation of the equipment, regular measurement of the weak gas components and content dissolved in the oil is of great significance and practical effect for early detection of latent faults in oil-filled power equipment.

[0003] As an important equipment in the power system, the health status of the transformer is directly related to the stability and safety of the power system. Traditional assessment methods often rely on regular manual inspections and offline tests, which have problems such as long assessment cycles and insufficient accuracy, as well as the inability to effectively detect low-concentration gases, which in turn affects the accurate assessment of the health status of the transformer. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a transformer health status assessment method, system, electronic device and storage medium.

[0005] In a first aspect, the present application provides a method for evaluating the health status of a transformer, comprising: obtaining a transformer oil sample, degassing the transformer oil sample, and obtaining a group of gases to be tested; introducing the group of gases to be tested into a detection cell; using a group of excitation light sources to irradiate the detection cell respectively to excite the group of gases to be tested to produce a photoacoustic effect, and converting the photoacoustic signal into a target electrical signal, wherein the group of excitation light sources includes a first laser light source and a second laser light source, the first laser light source is used to emit a mid-infrared laser signal of a first wavelength, the first wavelength matches the absorption line intensity of acetylene, and the second laser light source is used to emit near-infrared laser signals of each wavelength in a group of preset wavelengths in a time-sharing manner, each wavelength in a group of preset wavelengths matches the absorption line intensity of a gas in a group of preset gases, and the group of gases to be tested includes acetylene and a group of preset gases; based on the target electrical signal, a first detection result of a group of gases to be tested is obtained, wherein the first detection result includes the content of various characteristic gases in the group of gases to be tested; and the health status of the transformer is evaluated according to the first detection result.

[0006] By adopting the above technical solution, the detection pool is illuminated by mid-infrared laser signals and near-infrared laser signals of specific wavelengths, which can effectively stimulate the photoacoustic effect of acetylene and other preset gases, thereby improving the detection sensitivity and selectivity, avoiding the problems of spectral cross-interference and cross-sensitivity; converting the photoacoustic signal into a target electrical signal, and obtaining the content of each characteristic gas based on the electrical signal, ensuring the accuracy and reliability of the detection results; through the analysis of different gas contents, the health status of the transformer can be timely and accurately evaluated, potential faults can be discovered in advance, and the stability and safety of the power system can be improved. This technical solution can achieve the purpose of accurate detection of trace gases in transformer oil samples.

[0007] Optionally, the above method also includes: obtaining a second detection result of the target sensor, wherein the target sensor has the ability to detect hydrogen at a 2ppm level, the target sensor is installed in a detection pool, and a group of gases to be tested also includes hydrogen; and evaluating the health status of the transformer based on the second detection result.

[0008] By adopting the above technical solution, high-sensitivity hydrogen detection can be achieved. The target sensor has the ability to detect hydrogen at the 2ppm level and can accurately identify the presence of hydrogen at low concentrations, thereby improving the early warning capability of potential faults inside the transformer. Specifically, this method can not only detect other characteristic gases such as acetylene, but also monitor the changes in hydrogen at the same time, further improving the comprehensiveness and accuracy of transformer health status assessment. By combining multiple detection methods, real-time monitoring and intelligent evaluation of the health status of the transformer can be achieved, further improving the level of intelligence in transformer management.

[0009] Optionally, a group of excitation light sources are used to irradiate the detection pool respectively to stimulate a group of gases to be tested to produce photoacoustic effect, and the photoacoustic signal is converted into a target electrical signal, including: controlling each laser light source in the first laser light source and the second laser light source to emit corresponding laser signals in time-sharing to stimulate a group of gases to be tested to produce photoacoustic effect; converting the first photoacoustic signal into a first electrical signal, and converting the second photoacoustic signal into a second electrical signal, wherein the target electrical signal includes a first electrical signal and a second electrical signal, the first photoacoustic signal is a photoacoustic signal generated by the photoacoustic effect of acetylene, and the second photoacoustic signal includes photoacoustic signals respectively generated when various gases in a group of preset gases produce photoacoustic effect.

[0010] By adopting the above technical solution, the first laser light source and the second laser light source are controlled to emit corresponding laser signals in time-sharing, which effectively avoids the spectral cross-interference between different gases and improves the detection accuracy; the first photoacoustic signal is converted into a first electrical signal, and the second photoacoustic signal is converted into a second electrical signal, which ensures that the photoacoustic effect of each gas can be individually identified and quantified, so as to accurately obtain the concentration value of each characteristic gas; the target electrical signal includes the first electrical signal and the second electrical signal, covering the information of all gases to be tested, making the final detection result more comprehensive and reliable. This technical solution realizes the accurate detection of multiple gases in transformer oil.

[0011] Optionally, a first detection result of a set of gases to be tested is obtained based on the target electrical signal, including: obtaining a target concentration value of acetylene according to the first electrical signal, and obtaining a set of concentration values ​​according to the second electrical signal, wherein a set of concentration values ​​includes concentration values ​​corresponding to various gases in a set of preset gases, and the first detection result includes the target concentration value and a set of concentration values.

[0012] By adopting the above technical solution, the concentration of acetylene and other preset gases in transformer oil can be accurately measured. Specifically, the first laser light source and the second laser light source are used to respectively excite acetylene and other preset gases to produce photoacoustic effects, and the generated photoacoustic signals are converted into electrical signals to obtain the specific concentration value of each gas. This method not only improves the detection accuracy, but also effectively reduces the influence of spectral cross-interference and cross-sensitivity, ensuring accurate assessment of the health status of the transformer. At the same time, through comprehensive analysis of different gas concentrations, it is possible to more comprehensively judge whether the transformer has potential faults and improve the stability and safety of the power system.

[0013] Optionally, the health status of the transformer is evaluated according to the first detection result, including: when the target concentration value is greater than the target concentration threshold, judging that the transformer has a first type of fault; when the first concentration value is greater than the first concentration threshold and the second concentration value is greater than the second concentration threshold, judging that the transformer has a second type of fault, wherein the first concentration value is the concentration value corresponding to the first gas, the second concentration value is the concentration value corresponding to the second gas, a group of concentration values ​​includes the first concentration value and the second concentration value, and a group of preset gases includes the first gas and the second gas.

[0014] By adopting the above technical solution, when the target concentration value is greater than the target concentration threshold, the first type of fault in the transformer, such as partial discharge, can be effectively identified, so that timely measures can be taken to avoid further deterioration of the fault; when the first concentration value is greater than the first concentration threshold and the second concentration value is greater than the second concentration threshold, the second type of fault in the transformer, such as overheating fault or other compound faults, can be accurately judged, ensuring that potential problems are discovered at an early stage, improving maintenance efficiency and equipment safety. This technical solution can achieve accurate assessment of the health status of the transformer.

[0015] Optionally, the health status of the transformer is evaluated according to the second detection result, including: when the second detection result indicates that a third concentration value corresponding to hydrogen is greater than a third concentration threshold, determining that a third type of fault exists in the transformer.

[0016] By adopting the above technical solution, high-sensitivity detection of hydrogen concentration in the transformer can be achieved. Specifically, the target sensor has the ability to detect hydrogen at the 2ppm level and can accurately measure the hydrogen content at low concentrations. When the second detection result shows that the hydrogen concentration exceeds the set third concentration threshold, it can be timely judged that the transformer has a third type of fault, such as local internal overheating or insulation material moisture and other potential problems; this method not only improves the accuracy of fault detection, but also shortens the evaluation cycle, which helps to discover and eliminate hidden dangers of the transformer in advance and ensure the stability and safety of the power system.

[0017] Optionally, a group of gases to be tested includes a small-component gas or a multi-component gas, wherein the small-component gas includes acetylene, hydrogen and carbon monoxide, and the multi-component gas includes acetylene, hydrogen, carbon monoxide, carbon dioxide, methane, ethane and ethylene.

[0018] By adopting the above technical solution, for small-component gases, this method can effectively monitor the content changes of these key gases, thereby quickly identifying potential partial discharge and overheating faults. For multi-component gases, this method not only covers the key indicators of small-component gases, but also further extends to other gas components that may indicate complex faults, improving the comprehensiveness and accuracy of the evaluation, and achieving the purpose of comprehensive detection of different types of gases to be tested in transformer oil samples. Through the precise detection of different component gases, the health status of the transformer can be more accurately reflected, and the timeliness and reliability of fault diagnosis can be improved.

[0019] In a second aspect of the present application, a transformer health status assessment system is also provided, which is used to execute any of the aforementioned methods, including: an oil-gas separation module, which is used to extract transformer oil samples from the transformer and perform vacuum degassing to obtain a group of gases to be tested; a sampling pump, which is used to pump a group of gases to be tested into a detection pool; a laser module, which is used to control a group of excitation light sources to output laser signals in a time-sharing manner to irradiate the detection pool to stimulate a group of gases to be tested to produce a photoacoustic effect; a microphone, which is used to detect gas photoacoustic signals and convert them into target electrical signals; a processing module, which is used to obtain a first detection result of a group of gases to be tested based on the target electrical signal, and evaluate the health status of the transformer according to the first detection result.

[0020] In a third aspect of the present application, an electronic device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, any of the above method steps is implemented.

[0021] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the above method steps is performed.

[0022] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. Using mid-infrared laser signals and near-infrared laser signals of specific wavelengths to illuminate the detection cell respectively can effectively stimulate the photoacoustic effect of acetylene and other preset gases, thereby improving the detection sensitivity and selectivity; 2. Through the analysis of different gas contents, the health status of the transformer can be evaluated timely and accurately, potential faults can be discovered in advance, and the stability and safety of the power system can be improved; 3. By combining multiple detection methods, it can realize real-time monitoring and intelligent evaluation of the health status of the transformer, further improving the intelligent level of transformer management; 4. Through the precise detection of different components of gas, the health status of the transformer can be reflected more accurately, and the timeliness and reliability of fault diagnosis can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a method for evaluating the health status of a transformer provided in an embodiment of the present application; Figure 2 It is a schematic diagram of a flow chart of oil and gas detection provided by an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present application.

[0024] Description of reference numerals: 300 - electronic device; 301 - processor; 302 - communication bus; 303 - user interface; 304 - network interface; 305 - memory. DETAILED DESCRIPTION

[0025] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0027] In the description of the embodiments of the present application, the term "plurality" means two or more. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0028] The following is combined with Figure 1-Figure 3 The embodiments of the present application are described.

[0029] This application provides a method for evaluating the health status of a transformer. Figure 1 , Figure 1 : is a flow chart of a transformer health status assessment method provided by an embodiment of the present application, the method comprising: Step S101, obtaining a transformer oil sample, and degassing the transformer oil sample to obtain a group of gases to be tested; Step S102, introducing a group of gases to be tested into the detection cell; Step S103, using a group of excitation light sources to respectively irradiate the detection pool to excite a group of gases to be tested to produce a photoacoustic effect, and convert the photoacoustic signal into a target electrical signal, wherein the group of excitation light sources includes a first laser light source and a second laser light source, the first laser light source is used to emit a mid-infrared laser signal of a first wavelength, the first wavelength matches the absorption line intensity of acetylene, the second laser light source is used to emit near-infrared laser signals of each wavelength in a group of preset wavelengths in a time-sharing manner, each wavelength in a group of preset wavelengths matches the absorption line intensity of a gas in a group of preset gases, and the group of gases to be tested includes acetylene and a group of preset gases; Step S104, obtaining a first detection result of a group of gases to be tested based on the target electrical signal, wherein the first detection result includes the content of various characteristic gases in the group of gases to be tested; Step S105: Evaluate the health status of the transformer according to the first detection result.

[0030] Through the above steps, the detection pool is irradiated with mid-infrared laser signals and near-infrared laser signals of specific wavelengths respectively, which can effectively stimulate the photoacoustic effect of acetylene and other preset gases, thereby improving the detection sensitivity and selectivity, avoiding spectral cross-interference and cross-sensitivity problems; converting the photoacoustic signal into a target electrical signal, and obtaining the content of each characteristic gas based on the electrical signal, ensuring the accuracy and reliability of the detection result; through the analysis of different gas contents, the health status of the transformer can be timely and accurately evaluated, potential faults can be discovered in advance, and the stability and safety of the power system can be improved. This embodiment can achieve the purpose of accurate detection of trace gases in transformer oil samples.

[0031] This embodiment uses laser light sources of different wavelengths to illuminate the gas to be tested in the transformer oil sample, converts the optical signal into an electrical signal through the photoacoustic effect, and then detects the gas content. Specifically, an oil sample is obtained from the transformer and degassed to obtain a group of gases to be tested, that is, the dissolved gas is extracted from the transformer oil sample. The group of gases to be tested may include one or more of acetylene (C2H2), hydrogen (H2), methane (CH4), ethane (C2H6), ethylene (C2H4), carbon monoxide (CO) and carbon dioxide (CO2). The extracted gas to be tested is introduced into a specific detection cell, which may also be called a photoacoustic cell. A group of excitation light sources are used to illuminate the gas in the detection cell, including a first laser light that can emit a mid-infrared laser signal of a first wavelength that matches the intensity of the acetylene absorption line. A laser source and a second laser light source capable of emitting multiple near-infrared laser signals of preset wavelengths in time division, each preset wavelength corresponds to the absorption line intensity of different characteristic gases (such as methane CH4, ethane C2H6, etc.). When these gases are irradiated by lasers of corresponding wavelengths, they will undergo photoacoustic effect, that is, they will generate thermal expansion after absorbing light energy, thereby generating pressure waves or sounds; the generated photoacoustic signals are then converted into target electrical signals, and based on the converted electrical signals, a set of detection results of the gases to be tested is obtained, including the specific content of various characteristic gases. According to the changes in the composition and content of these gases, the possible fault types and severity inside the transformer can be evaluated. By selecting a laser light source of a specific wavelength and accurately exciting the absorption lines of different gases, spectral cross-interference is effectively avoided, and the accuracy of gas detection is improved; the method can monitor the changes in gas content in transformer oil in real time, timely detect weak signals at the initial stage of a fault, realize early warning, and evaluate the health status of the transformer based on the detection results. It can be combined with an intelligent diagnosis model to further improve the accuracy and reliability of the evaluation. Compared with the traditional method, the method of this embodiment reduces the frequency and complexity of manual inspections, while improving the efficiency of fault diagnosis, which helps to reduce operation and maintenance costs.

[0032] In an optional embodiment, the above method also includes: obtaining a second detection result of the target sensor, wherein the target sensor has the ability to detect 2ppm level hydrogen, the target sensor is installed in a detection pool, and a group of gases to be tested also includes hydrogen; and evaluating the health status of the transformer according to the second detection result.

[0033] In the above embodiment, high-sensitivity hydrogen detection can be achieved. The target sensor has the ability to detect hydrogen at the 2ppm level and can accurately identify the presence of hydrogen at low concentrations, thereby improving the early warning capability of potential faults inside the transformer. Specifically, this method can not only detect other characteristic gases such as acetylene, but also monitor the changes in hydrogen at the same time, further improving the comprehensiveness and accuracy of transformer health status assessment. By combining a variety of detection methods, real-time monitoring and intelligent evaluation of the health status of the transformer can be achieved, further improving the level of intelligence in transformer management.

[0034] This embodiment further introduces a target sensor to obtain a second detection result about hydrogen (H2), and also incorporates this result into the evaluation of the health status of the transformer. A target sensor capable of detecting 2ppm (parts per million) of hydrogen is installed in the detection pool. This sensor can measure the hydrogen content in the gas to be tested with high precision; while using the photoacoustic effect for gas detection, the target sensor also monitors the hydrogen content in real time and generates a second detection result; the first detection result obtained by the photoacoustic effect detection (including the content of acetylene and other preset gases) is combined with the second detection result (hydrogen content) obtained by the target sensor, and is used together to evaluate the health status of the transformer. The hydrogen content generated when the transformer fails may be very low, and traditional detection methods cannot accurately detect it due to insufficient sensitivity. This embodiment combines the photoacoustic effect detection and the hydrogen detection results of the target sensor to more comprehensively evaluate the health status of the transformer and reduce misjudgments or missed judgments caused by incomplete information. Since hydrogen is an important indicator gas for various faults inside the transformer, its presence and concentration changes are important for determining whether there are faults such as overheating or discharge. Therefore, accurate detection of hydrogen content can significantly improve the early warning capability of transformer faults and help to promptly discover and deal with potential problems.

[0035] In an optional embodiment, a group of excitation light sources are used to illuminate the detection pool respectively to stimulate a group of gases to be tested to produce photoacoustic effect, and the photoacoustic signal is converted into a target electrical signal, including: controlling each laser light source in the first laser light source and the second laser light source to emit corresponding laser signals in time-sharing to stimulate a group of gases to be tested to produce photoacoustic effect; converting the first photoacoustic signal into a first electrical signal, and converting the second photoacoustic signal into a second electrical signal, wherein the target electrical signal includes a first electrical signal and a second electrical signal, the first photoacoustic signal is a photoacoustic signal generated by the photoacoustic effect of acetylene, and the second photoacoustic signal includes photoacoustic signals generated by various gases in a group of preset gases when the photoacoustic effect occurs.

[0036] In the above embodiment, the first laser light source and the second laser light source are controlled to emit corresponding laser signals in time-sharing, which effectively avoids the spectral cross-interference between different gases and improves the detection accuracy; the first photoacoustic signal is converted into a first electrical signal, and the second photoacoustic signal is converted into a second electrical signal, which ensures that the photoacoustic effect of each gas can be individually identified and quantified, so as to accurately obtain the concentration value of each characteristic gas; the target electrical signal includes the first electrical signal and the second electrical signal, covering the information of all gases to be tested, making the final detection result more comprehensive and reliable. This embodiment realizes the accurate detection of multiple gases in transformer oil.

[0037] By controlling the first laser light source (mid-infrared laser, used to detect acetylene) and the second laser light source (near-infrared laser, used to detect other gases) to emit laser signals in a time-sharing manner, the first wavelength mid-infrared laser emitted by the first laser light source is specifically used to excite acetylene (C2H2), causing it to undergo a photoacoustic effect, thereby generating a first photoacoustic signal. The second laser light source sequentially emits multiple near-infrared laser signals in a preset time sequence. The wavelength of each signal matches the absorption spectrum of a gas in a set of preset gases, thereby specifically exciting these gases to produce their own photoacoustic effects, forming a second photoacoustic signal. The generated photoacoustic signal (i.e., the absorption spectrum of the gas affected by the light) is The pressure wave or sound generated after the excitation is converted into a corresponding electrical signal through an appropriate sensor. The first photoacoustic signal corresponds to the first electrical signal, while the second photoacoustic signal corresponds to the second electrical signal. Finally, the two electrical signals together constitute the target electrical signal. To avoid mutual interference between lasers of different wavelengths, the photoacoustic effect is used. When the gas to be tested absorbs lasers of a specific wavelength, periodic pressure fluctuations (acoustic signals) are generated. These acoustic signals are converted into electrical signals through a highly sensitive pickup. The photoacoustic signal generated by acetylene is converted into the first electrical signal, and the photoacoustic signal generated by other gases is converted into the second electrical signal. Finally, the two electrical signals are combined for comprehensive analysis. In traditional spectral detection technology, the absorption spectra of different gases may interfere with each other and affect the detection accuracy. By controlling the laser light source in time-sharing, the cross-spectral interference of different gases during detection is avoided. The traditional method has low detection sensitivity for low-concentration gases, especially for changes in gas content in the early stage of failure. Photoacoustic spectroscopy technology can effectively detect low-concentration gases through highly sensitive acoustic sensors. Through this embodiment, by time-sharing control of the laser light source and the high-sensitivity acoustic sensor, the content of acetylene and other gases can be accurately detected, which is particularly suitable for the detection of low-concentration gases; the design of time-sharing control of the laser light source effectively avoids spectral cross-interference during detection of different gases, thereby improving the accuracy and reliability of detection; by separately detecting the photoacoustic signals of acetylene and other gases and comprehensively analyzing the results, the health status of the transformer can be more comprehensively reflected, thereby improving the accuracy of fault diagnosis.

[0038] In an optional embodiment, a first detection result of a set of gases to be tested is obtained based on the target electrical signal, including: obtaining a target concentration value of acetylene according to the first electrical signal, and obtaining a set of concentration values ​​according to the second electrical signal, wherein a set of concentration values ​​includes concentration values ​​corresponding to various gases in a set of preset gases, and the first detection result includes the target concentration value and a set of concentration values.

[0039] In the above embodiment, the concentration values ​​of acetylene and other preset gases in transformer oil can be accurately measured. Specifically, the first laser light source and the second laser light source are used to respectively excite acetylene and other preset gases to produce photoacoustic effects, and the generated photoacoustic signals are converted into electrical signals to obtain the specific concentration value of each gas. This method not only improves the detection accuracy, but also effectively reduces the influence of spectral cross-interference and cross-sensitivity, ensuring accurate assessment of the health status of the transformer. At the same time, through the comprehensive analysis of different gas concentrations, it is possible to more comprehensively judge whether the transformer has potential faults, thereby improving the stability and safety of the power system.

[0040] By analyzing the first electrical signal, the target concentration value of acetylene (C2H2) can be determined. Since the first laser light source is specially designed for the absorption characteristics of acetylene, the photoacoustic signal it generates mainly reflects the presence of acetylene. For the second electrical signal, a set of preset gases (such as methane CH4, ethane C2H6, etc.) is involved. Since the second laser light source emits near-infrared lasers of multiple wavelengths according to a preset time sequence, each wavelength corresponds to the absorption spectrum of a specific gas, the concentration values ​​of these gases can be respectively analyzed from the second electrical signal. The final first detection result includes the target concentration value of acetylene and the concentration values ​​corresponding to various gases in a set of preset gases, forming a complete set of gas component concentration information. Optionally, the first electrical signal can be converted into the target concentration value of acetylene and each electrical signal in the second electrical signal can be converted into a corresponding concentration value in a set of concentration values ​​through a specific algorithm or model. In actual applications, a preset correspondence between the concentration data of various gases and the electrical signal can be established based on historical data, so that the concentration value corresponding to each electrical signal can be determined based on the preset correspondence between the two during actual detection. The method of this embodiment can detect multiple gases at the same time and accurately calculate the concentration value of each gas, which enhances the multi-gas detection capability of the gas detection system.

[0041] In an optional embodiment, the health status of the transformer is evaluated according to the first detection result, including: when the target concentration value is greater than the target concentration threshold, it is judged that the transformer has a first type of fault; when the first concentration value is greater than the first concentration threshold and the second concentration value is greater than the second concentration threshold, it is judged that the transformer has a second type of fault, wherein the first concentration value is a concentration value corresponding to the first gas, the second concentration value is a concentration value corresponding to the second gas, a group of concentration values ​​includes the first concentration value and the second concentration value, and a group of preset gases includes the first gas and the second gas.

[0042] In the above embodiment, when the target concentration value is greater than the target concentration threshold, the first type of fault in the transformer, such as partial discharge, can be effectively identified, so that timely measures can be taken to avoid further deterioration of the fault; when the first concentration value is greater than the first concentration threshold and the second concentration value is greater than the second concentration threshold, the second type of fault in the transformer, such as overheating fault or other compound faults, can be accurately judged, ensuring that potential problems are discovered at an early stage, improving maintenance efficiency and equipment safety. This embodiment can achieve accurate assessment of the health status of the transformer.

[0043] This embodiment sets different concentration thresholds and combines the changing characteristics of gas concentration to determine whether the transformer has a specific type of fault. When the target concentration value of acetylene (C2H2) exceeds the set target concentration threshold, it is determined that the transformer has a first type of fault, such as a discharge fault; when the concentration values ​​of other preset gases (such as ethane or ethylene or hydrogen) exceed their respective set concentration thresholds, it is determined that the transformer has a second type of fault, such as an overheating fault. By analyzing the concentration changes of various gases and combining the typical combination of fault characteristic gases, an accurate judgment of the transformer fault type is achieved, thereby improving the accuracy of fault diagnosis. A comprehensive analysis of the concentration changes of multiple gases such as acetylene and ethane is used to achieve a multi-dimensional assessment of the health status of the transformer, avoiding the limitations of single gas judgment and reducing false alarms or missed alarms.

[0044] In an optional embodiment, the health status of the transformer is evaluated according to the second detection result, including: when the second detection result indicates that a third concentration value corresponding to hydrogen is greater than a third concentration threshold, determining that a third type of fault exists in the transformer.

[0045] In the above embodiment, high-sensitivity detection of hydrogen concentration in the transformer can be achieved. Specifically, the target sensor has the ability to detect hydrogen at the 2ppm level, and can accurately measure the hydrogen content at low concentrations. When the second detection result shows that the hydrogen concentration exceeds the set third concentration threshold, it can be timely judged that the transformer has a third type of fault, such as potential problems such as local internal overheating or moisture in the insulation material; this method not only improves the accuracy of fault detection, but also shortens the evaluation cycle, which helps to discover and eliminate hidden dangers of the transformer in advance and ensure the stability and safety of the power system.

[0046] The concentration of hydrogen in the transformer is detected by a high-sensitivity target sensor to obtain a second detection result, which includes a third concentration value corresponding to hydrogen. That is, the concentration of hydrogen dissolved in the transformer oil can be accurately measured by a high-sensitivity target sensor installed in the detection pool to obtain a third concentration value. A third concentration threshold is preset, which is determined based on the hydrogen concentration characteristics under normal operating conditions and fault conditions of the transformer. When the third concentration value in the second detection result exceeds the third concentration threshold, it is determined that the transformer has a third type of fault. This type of fault is usually related to problems such as overheating or moisture in the transformer, because these problems will cause a significant increase in hydrogen concentration. By setting the hydrogen concentration threshold, it is possible to accurately determine whether the transformer has a third type of fault, thereby improving the accuracy of fault diagnosis and providing more specific information for subsequent fault handling and maintenance.

[0047] For example, the hydrogen concentration threshold is 500uL / L (or other values), that is, when the detected hydrogen concentration is greater than the threshold, it means that the transformer may have an overheating fault; or, when the acetylene concentration is greater than 5uL / L (or other values), it means that the transformer may have a partial discharge fault; or, when the methane concentration is greater than 200uL / L (or other values), it means that the transformer may have oil aging or partial discharge faults. The above is only an example, and different judgment criteria can be set for transformers in different application scenarios.

[0048] In an optional embodiment, a group of gases to be tested includes a small-component gas or a multi-component gas, wherein the small-component gas includes acetylene, hydrogen and carbon monoxide, and the multi-component gas includes acetylene, hydrogen, carbon monoxide, carbon dioxide, methane, ethane and ethylene.

[0049] In the above embodiment, for small-component gas, the method can effectively monitor the content changes of these key gases, so as to quickly identify potential partial discharge and overheating faults. For multi-component gas, the method not only covers the key indicators of small-component gas, but also further extends to other gas components that may indicate complex faults, improving the comprehensiveness and accuracy of the evaluation, and can achieve the purpose of comprehensive detection of different types of gases to be tested in transformer oil samples. Through the accurate detection of different component gases, the health status of the transformer can be more accurately reflected, and the timeliness and reliability of fault diagnosis can be improved.

[0050] In some application scenarios, the gases dissolved in transformer oil may mainly include acetylene (C2H2), hydrogen (H2) and carbon monoxide (CO), which are usually associated with specific types of faults, such as partial discharge or overheating. In more complex scenarios, in addition to the above three gases, carbon dioxide (CO2), methane (CH4), ethane (C2H6) and ethylene (C2H4) may also be included. Based on these gases, more comprehensive information can be provided to help identify more types of potential faults. In actual applications, some scenarios only require the detection of a few components of gas, and some scenarios require the detection of multiple components of gas. The evaluation method of this embodiment is applicable to both. In actual applications, the detection of gases of different components can be matched by adjusting each specific laser light source in the second laser light source.

[0051] In an optional embodiment, the above method also includes: inputting the first detection result and the second detection result into a target neural network model to obtain a target fault type, wherein the target neural network model is trained using a training sample data set containing gas concentration data in a variety of transformer oils, and each training sample in the training sample data set includes gas concentration data and the corresponding health status of the transformer.

[0052] In the above embodiment, the first detection result and the second detection result are input into the target neural network model, so as to realize the intelligent evaluation of the health status of the transformer. The method uses a pre-trained neural network model, which can comprehensively consider a variety of gas concentration data and their combinations to improve the accuracy and reliability of fault diagnosis. Specifically, the neural network model can quickly identify the potential fault types of the transformer in practical applications by learning a large amount of historical data, so as to take timely measures for maintenance and repair to ensure the stable operation of the power system. The model performs complex nonlinear transformations on the input data through connections and weight adjustments between multiple layers of neurons to extract information related to the health status of the transformer. The model finally outputs the target fault type, which is based on the relationship between the input data (i.e., the gas concentration value) and the health status of the transformer learned inside the model. The target neural network model is trained using a training sample data set containing gas concentration data in various transformer oils. Each training sample not only includes concentration data of different gases, but also is associated with the corresponding transformer health status information, so that the model can learn the relationship between different gas combinations and specific fault types. Since the neural network model can learn the complex relationship between gas concentration and transformer health status, this method can more accurately determine the fault type of the transformer. The introduction of the neural network model makes the fault judgment process more automated and intelligent, reducing the impact of manual intervention and subjective judgment.

[0053] The present application also provides a transformer health status assessment system, which is used to execute the transformer health status assessment method of any of the aforementioned embodiments, and the system includes: an oil-gas separation module, which is used to extract transformer oil samples from the transformer and perform vacuum degassing to obtain a group of gases to be tested; a sampling pump, which is used to pump the group of gases to be tested into a detection pool; a laser module, which is used to control a group of excitation light sources to output laser signals in a time-sharing manner to irradiate the detection pool to excite a group of gases to be tested to produce a photoacoustic effect; a microphone, which is used to perform gas photoacoustic signal detection and convert it to obtain a target electrical signal; a processing module, which is used to obtain a first detection result of a group of gases to be tested based on the target electrical signal, and evaluate the health status of the transformer according to the first detection result.

[0054] In the above embodiment, the oil-gas separation module effectively extracts various characteristic gases dissolved in the oil by vacuum degassing the transformer oil sample, ensuring the purity of the sample for subsequent detection; the sampling pump smoothly delivers the extracted gas to be tested into the detection pool, ensuring the consistency and stability of the gas entering the detection environment; the laser module uses a laser source with a specific wavelength (such as a mid-infrared laser for acetylene and different near-infrared lasers for other preset gases) to sequentially irradiate the gas mixture in the detection pool, stimulating a photoacoustic signal with a specific absorption line intensity response, thereby improving the detection sensitivity and selectivity; the microphone accurately captures the subtle pressure changes caused by the vibration of different gas molecules and converts them into an electrical signal form, realizing the effective conversion from optical signals to analyzable electronic data; the processing module comprehensively analyzes the data from the microphone to obtain the specific concentration value of each characteristic gas, and further judges whether the transformer has potential faults and the fault type based on these concentration indicators, significantly improving the accuracy and timeliness of the evaluation results. The transformer health status evaluation system can accurately detect trace gas components and their contents in transformer oil.

[0055] In an optional embodiment, the system further includes: a target sensor, wherein the target sensor has the ability to detect hydrogen at a 2ppm level, the target sensor is installed in a detection pool, and a group of gases to be tested also includes hydrogen; the health status of the transformer is evaluated based on a second detection result, wherein the second detection result is the detection result of hydrogen by the target sensor.

[0056] In the above embodiment, high-sensitivity hydrogen detection can be achieved. The target sensor has the ability to detect hydrogen at the 2ppm level and can accurately identify the presence of hydrogen at low concentrations, thereby improving the early warning capability of potential faults inside the transformer. Specifically, this method can not only detect other characteristic gases such as acetylene, but also monitor the changes in hydrogen at the same time, further improving the comprehensiveness and accuracy of transformer health status assessment. By combining a variety of detection methods, real-time monitoring and intelligent evaluation of the health status of the transformer can be achieved, further improving the level of intelligence in transformer management.

[0057] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application will be described in detail below in conjunction with specific embodiments.

[0058] The measurement objects of the dissolved gas detection device in multi-component transformer oil include the following characteristic gases: acetylene (C2H2), hydrogen (H2), carbon monoxide (CO), ethylene (C2H4), methane (CH4), ethane (C2H6), and carbon dioxide (CO2); the measurement objects of the dissolved gas detection device in small-component transformer oil include the following characteristic gases: acetylene (C2H2), hydrogen (H2), and carbon monoxide (CO).

[0059] The following is the detailed technical solution: 1. Laser selection The interference of cross-sensitivity, especially the cross-sensitivity problem at low concentrations, has always been a key factor in gas separation and detection solutions. Broad-spectrum light source type dissolved gas detection equipment uses filters with bandwidths of tens to hundreds of nm to remove part of the interference, and uses data models and algorithms to remove part of the interference, but these two methods cannot meet the interference problem in ultra-low concentration detection. Selecting a narrow linewidth laser as the excitation source to detect dissolved gas in oil has good monochromaticity and can avoid most gas interference for characteristic gas detection. The interference suppression ability can be controlled below three orders of magnitude or even higher, but this requires careful wavelength screening based on experience.

[0060] A spectral test platform is built based on the laser driving platform, photoacoustic spectroscopy gas detection platform, etc., and the data of the spectral database is combined to customize the laser for the wavelengths selected from the database (as shown in Table 1).

[0061] Table 1

[0062] Since the absorption intensity of C2H2 gas is the largest near 1533nm in the near-infrared band, laser photoacoustic spectroscopy in related technologies generally selects lasers with wavelengths near 1533nm for the research and development and production of gas detection equipment, but the detection accuracy is low; according to the standards and operation requirements of the power industry, in transformer oil and gas detection, mass-produced equipment requires the detection of C2H2 concentration to reach 0.2ppm (where the detected gas is about 1ppm, and considering the ratio conversion of oil and gas, the detection accuracy in oil can reach 0.2ppm), but there are very few manufacturers that actually have a detection capability of 0.2ppm. The embodiment of this application selects a quantum cascade laser QCL of 3025.75nm (absorption line intensity 2.464E-19) as a mid-infrared light source, and based on the double feedback Pound–Drever–Hall frequency locking method, the QCL frequency is locked in a continuously scanned optical cavity to achieve ultra-sensitive gas detection by resonant photoacoustic effect. Introducing mid-infrared quantum cascade lasers into the field of transformer oil and gas online detection can effectively improve the situation of insufficient dissolved gas detection capability and further improve the accuracy of oil and gas detection.

[0063] The selection of photoacoustic cell materials is crucial, as it is directly related to the damping, viscosity and heat loss of the gas, and has a great impact on improving the detection sensitivity. Photoacoustic cavities generally use materials such as aluminum and brass with large thermal conductivity and Poisson's ratio. Copper has a large Young's modulus and Poisson's ratio, but the density of copper is very large compared to aluminum, resulting in a relatively high processing cost for copper. Considering the performance of the material and the processing characteristics, it is more appropriate to use aluminum as the material for the photoacoustic cell. In order to reduce the adsorption of gas molecules by the inner wall of the photoacoustic cell, the roughness of the inner wall of the photoacoustic cell should be below 0.4. At the same time, in order to reduce the absorption of lasers by the cell wall, the inner wall of the photoacoustic cell should be gold-plated.

[0064] The near-infrared other gas photoacoustic spectroscopic sensor uses a coherent light source in the range of 1500~1700nm as the excitation light source. Due to the large wavelength range distribution, it is impossible to use a wide-range tunable laser to meet the design requirements. Taking into account the laser volume, cost, band, line width, power and other factors, this application uses a fiber-optic output high-power (>20mW) DFB laser to perform photoacoustic spectroscopic detection of gases. The five gases to be detected, CH4, C2H4, C2H6, CO, and CO2, require five near-infrared lasers and their corresponding photoacoustic spectroscopic detection systems. In order to reduce the gas volume demand and further reduce the degassing dependence, the embodiment of the present application designs a scheme in which the optical signals emitted by five DFB lasers are combined through a fiber optic combiner with higher safety and lower failure rate. The combined optical signal is collimated and enters a single photoacoustic cell. The laser is driven in time-sharing and the gas photoacoustic signal is detected through a microphone. The demand for the amount of gas to be tested is effectively reduced. At the same time, the DFB semiconductor laser as the excitation light source of the detection device has excellent characteristics such as electrically tunable wavelength and fiber coupling. The output bandwidth is only tens of pm. DFB lasers with specific wavelengths can be selected to correspond to the absorption peak of each gas, avoiding interference from the absorption peaks of other gases, and fundamentally eliminating interference between different gases during the detection process.

[0065] 2. Hydrogen detection The most commonly used H2 sensors in related technologies are palladium film sensors in oil and electrochemical sensors (solid fuel cell type, conventional liquid electrolyte type). However, the ultrasonic method and photoacoustic spectroscopy resonant frequency change method (H2 causes sound velocity change) studied by many universities cannot test concentrations at the ppm level. Mems type and thermal conductivity type sensors are also difficult to meet the needs of trace H2 detection.

[0066] The palladium membrane sensor hydrogen detection is widely used abroad because there is no gas cross interference, but the domestic power grid hydrogen detection index is high, and the palladium membrane sensor has an accuracy of 25ppm, which cannot meet the accuracy requirements, so it is not used; liquid electrolyte electrochemical sensors have a short life and are greatly affected by CO. They cannot measure trace amounts of H2 under high-concentration CO background gas, so they are also not used. The embodiment of the present application uses a solid-state fuel cell type hydrogen sensor for hydrogen detection in oil and gas detection.

[0067] 3. Degassing The detection performance of the oil and gas online detection device is not only related to the gas detection accuracy, but also to the oil and gas separation performance. There are detection devices for dissolved gas in multi-component transformer oil and detection devices for dissolved gas in small-component transformer oil (<50kg). In particular, the lightweight and portable properties of small-component devices require a lightweight design of the equipment degasser. Specifically, stirring negative pressure headspace degassing and expansion vacuum degassing solutions can be used.

[0068] During the degassing process of the magnetic stirring negative pressure headspace degassing scheme, the vacuum pump evacuates the oil storage chamber, opens the oil inlet valve, and fills the transformer oil to a specified liquid level in the oil storage chamber according to the indication of the float level gauge. Thereafter, the magnetic stirring rotor is driven to stir the transformer oil. During the stirring process, the fault gas dissolved in the transformer oil will gradually separate into the negative pressure headspace. After stirring for a specified time, the vacuum pump transfers the released gas to the detection tank. Multiple stirring and transfers complete the degassing process.

[0069] When the expansion type vacuum degassing solution is used for the first time, the oil storage chamber is first filled with transformer oil (indicated by the liquid level switch). The volume of the piston cylinder is larger than the volume of the oil storage chamber, and the height is lower than the piston cylinder. By pushing the piston cylinder to expand, the transformer oil in the oil storage chamber is sucked into the piston cylinder to achieve degassing, and the degassing process is completed by reciprocating multiple times. This solution is relatively complex, the oil inlet volume is poorly adjustable, and the piston cylinder is involved, which makes it difficult to lightweight mass production, but this solution has high degassing efficiency and higher repeatability, and is a better choice for all-component oil dissolved gas detection equipment.

[0070] In actual gas detection, the oil-gas separation system, temperature control system, and control system can be combined to detect the gas in the transformer oil. Figure 2 As shown, the oil-gas separation system extracts a quantitative oil sample from the transformer and performs vacuum degassing; the degassed oil sample is returned to the transformer by means of a pump; the separated gas is pumped into each detection module for measurement through a sampling pump; each measurement module communicates with the main control board to upload and display the measured component concentration; at the same time, the temperature control system ensures that the temperature of the entire machine is constant, improves the consistency and stability of the oil-gas separation system, and ensures the stability of the measurement system.

[0071] Figure 2This is a schematic diagram of a process of oil and gas detection provided by an embodiment of the present application, comprising the following steps: S201, timing detection or receiving instruction detection; S202, determining whether the temperature is normal; If the judgment result of the above step S202 is no, proceed to S203; if the judgment result of the above step S202 is yes, proceed to S206; S203, upload error information, shutdown warning; S204, self-check whether it is normal; If the judgment result of the above step S204 is no, proceed to S205; if the judgment result of the above step S204 is yes, proceed to S206; S205, upload error information, shutdown warning; S206, equipment oil supply; It should be noted that the above steps S202-S203 correspond to the temperature control self-test sub-process, and steps S204-S205 correspond to the light source self-test sub-process. The above steps S202 and S204 are not in any particular order and can be performed simultaneously. Only when the temperature and light source self-tests are normal will step S206 be entered; S207, judging whether the oil injection is successful; If the judgment result of the above step S207 is no, proceed to S208; if the judgment result of the above step S207 is yes, proceed to S211; S208, executing the oil intake process again; S209, determine whether the oil injection is successful; if successful, proceed to S211, if unsuccessful, proceed to S210; S210, upload error information, shutdown warning; S211, performing degassing treatment; S212, determining whether degassing is completed; If the judgment result of the above step S212 is no, proceed to S213; if the judgment result of the above step S212 is yes, proceed to S215; S213, waiting for the degassing to time out; if so, proceed to S214, if not, proceed to S211; S214, upload error information, shutdown warning; S215, performing gas detection; S216, determining whether the detection is completed; If the judgment result of the above step S216 is no, proceed to S217; if the judgment result of the above step S216 is yes, proceed to S219; S217, waiting for detection to time out; if the detection timed out, then enter S218, if not timed out, then enter S215 to continue detection; S218, upload timeout information, shutdown warning; S219, perform data analysis; S220, uploading the data; S221, waiting for the demand to be measured on time or on demand; if a command or instruction is received, then enter S201, if no command or instruction is received, then continue to wait or exit; S222, determining whether the analysis result of step S219 contains false alarm information; If the judgment result of the above step S222 is yes, enter S223; if the judgment result of the above step S222 is no, no operation is performed, that is, there is no need to upload the alarm; S223, upload alarm; S224, judging or waiting whether to retest; if retest is required, entering S201 to restart the test, if retest is not required, continuing to wait for instructions or instructions.

[0072] By detecting the gas in the transformer oil, the purpose of effectively evaluating the health status of the transformer can be achieved.

[0073] The present application also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed, any one of the method steps described above is executed.

[0074] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0075] The present application also discloses an electronic device. Figure 3 As shown, Figure 3 The electronic device 300 may include: at least one processor 301 , at least one communication bus 302 , a user interface 303 , at least one network interface 304 , and a memory 305 .

[0076] The communication bus 302 is used to realize the connection and communication between these components.

[0077] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0078] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0079] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts of the entire electronic device (such as a server), and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0080] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a transformer health status assessment method.

[0081] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call an application program of a transformer health status evaluation method stored in the memory 305, and when executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0082] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0083] In the several implementation modes provided in this application, it should be understood that the disclosed device or system can be implemented in other ways. For example, the device or system embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0084] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0086] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0087] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification, those skilled in the art will easily think of other embodiments of the present disclosure.

[0088] This application is intended to cover any modifications, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the technical field not recorded in the present disclosure.

Claims

1. A method for evaluating the health status of a transformer, characterized in that: include: Obtaining a transformer oil sample, and degassing the transformer oil sample to obtain a group of gases to be tested; Introducing the group of gases to be tested into the detection cell; A group of excitation light sources are used to irradiate the detection pool respectively to excite the group of gases to be tested to produce a photoacoustic effect and convert the photoacoustic signal into a target electrical signal, wherein the group of excitation light sources includes a first laser light source and a second laser light source, the first laser light source is used to emit a mid-infrared laser signal of a first wavelength, the first wavelength matches the absorption line intensity of acetylene, and the second laser light source is used to emit near-infrared laser signals of each wavelength in a group of preset wavelengths in a time-sharing manner, each wavelength in the group of preset wavelengths matches the absorption line intensity of one gas in a group of preset gases, and the group of gases to be tested includes acetylene and the group of preset gases; Obtaining a first detection result of the group of gases to be tested based on the target electrical signal, wherein the first detection result includes the content of various characteristic gases in the group of gases to be tested; The health status of the transformer is evaluated according to the first detection result.

2. The method according to claim 1, characterized in that: The method further comprises: Obtaining a second detection result of the target sensor, wherein the target sensor has the ability to detect 2 ppm level hydrogen, the target sensor is installed in the detection cell, and the group of gases to be detected also includes the hydrogen; The health status of the transformer is evaluated according to the second detection result.

3. The method according to claim 1, characterized in that: Using a group of excitation light sources to illuminate the detection cells respectively to stimulate the group of gases to produce photoacoustic effect, and converting the photoacoustic signals into target electrical signals, including: Controlling each of the first laser light source and the second laser light source to emit corresponding laser signals in a time-sharing manner to stimulate the group of gases to be measured to produce a photoacoustic effect; The first photoacoustic signal is converted into a first electrical signal, and the second photoacoustic signal is converted into a second electrical signal, wherein the target electrical signal includes the first electrical signal and the second electrical signal, the first photoacoustic signal is a photoacoustic signal generated by the photoacoustic effect of the acetylene, and the second photoacoustic signal includes photoacoustic signals respectively generated when various gases in the set of preset gases undergo photoacoustic effect.

4. The method according to claim 3, characterized in that Obtaining a first detection result of the group of gases to be detected based on the target electrical signal includes: A target concentration value of acetylene is obtained according to the first electrical signal, and a group of concentration values ​​are obtained according to the second electrical signal, wherein the group of concentration values ​​includes concentration values ​​corresponding to various gases in the group of preset gases, and the first detection result includes the target concentration value and the group of concentration values.

5. The method according to claim 4, characterized in that Evaluating the health status of the transformer according to the first detection result includes: When the target concentration value is greater than the target concentration threshold, it is determined that a first type of fault exists in the transformer; When the first concentration value is greater than the first concentration threshold and the second concentration value is greater than the second concentration threshold, it is determined that the transformer has a second type of fault, wherein the first concentration value is a concentration value corresponding to a first gas, the second concentration value is a concentration value corresponding to a second gas, the group of concentration values ​​includes the first concentration value and the second concentration value, and the group of preset gases includes the first gas and the second gas.

6. The method according to claim 2, characterized in that Evaluating the health status of the transformer according to the second detection result includes: When the second detection result indicates that the third concentration value corresponding to the hydrogen is greater than a third concentration threshold, it is determined that a third type of fault exists in the transformer.

7. The method according to claim 2, characterized in that: The group of gases to be tested includes a small number of components gas or a multi-component gas, wherein the small number of components gas includes acetylene, hydrogen and carbon monoxide, and the multi-component gas includes acetylene, hydrogen, carbon monoxide, carbon dioxide, methane, ethane and ethylene.

8. A transformer health status assessment system, characterized in that: The method for performing any one of claims 1 to 7 comprises: An oil-gas separation module is used to extract the transformer oil sample from the transformer and perform vacuum degassing to obtain the group of gases to be tested; A sampling pump, used for pumping the group of gases to be tested into the detection cell; A laser module, used for controlling the group of excitation light sources to output laser signals in a time-sharing manner to illuminate the detection pool, so as to excite the group of gases to be detected to produce a photoacoustic effect; A microphone, used for detecting gas photoacoustic signals and converting them into the target electrical signals; A processing module is used to obtain a first detection result of the group of gases to be tested based on the target electrical signal, and to evaluate the health status of the transformer according to the first detection result.

9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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