Method and system for detecting trace decomposition components of fluorine-containing insulating gases

Abstract

The application discloses a kind of fluorine-containing insulating gas trace decomposition component detection method and system, it is related to trace decomposition component gas detection technical field, obtain fluorine-containing gas sample and multiple training gas data, and all training gas data are preprocessed, generate gas feature set, gas feature set is used to train preset trace decomposition component classification model, generate target trace decomposition component classification model, trace decomposition component detection is carried out to fluorine-containing gas sample by the double-layer sensing device of pre-construction, generate trace decomposition component data, component detection is carried out to trace decomposition component data using target trace decomposition component classification model, obtain the detection data corresponding to fluorine-containing gas sample.The technical problem that the trace decomposition component gas in existing electrical equipment is mainly detected by sensor based on nanomaterial, but the interference of fluorine-containing gas to sensor is ignored, and the trace decomposition component in fluorine-containing gas cannot be accurately detected.

Description

Technical Field

[0001] This invention relates to the field of trace decomposition component gas detection technology, and in particular to a method and system for detecting trace decomposition components in fluorine-containing insulating gases. Background Technology

[0002] Fluorine-containing gases are widely used in various fields due to their excellent stability, chemical inertness, environmental compatibility, and thermal properties. However, when fluorine-containing gases in electrical equipment are exposed to the operating environment for extended periods, they can decompose and produce trace decomposition components (such as C4F7N, which decomposes under fault conditions to produce trace decomposition components like C3F6, CO, and CHF3). These trace decomposition components can damage the intrinsic properties of the equipment, leading to malfunctions. Therefore, timely detection of trace decomposition components in fluorine-containing gases within electrical equipment is crucial.

[0003] In existing electrical equipment, trace decomposition component gases are mainly detected by sensors based on nanomaterials. However, the interference of fluorine-containing gases on the sensors is ignored, making it impossible to accurately detect trace decomposition components in fluorine-containing gases and reducing the reliability of electrical equipment operation. Summary of the Invention

[0004] This invention provides a method and system for detecting trace decomposition components in fluorinated insulating gases. It solves the technical problem that existing electrical equipment mainly detects trace decomposition components in gases through nanomaterial-based sensors, but ignores the interference of fluorinated gases on the sensors, making it impossible to accurately detect trace decomposition components in fluorinated gases and reducing the reliability of electrical equipment operation.

[0005] The first aspect of this invention provides a method for detecting trace decomposition components of fluorine-containing insulating gases, comprising:

[0006] Acquire fluorine-containing gas samples and multiple training gas data, and preprocess all the training gas data to generate a gas feature set;

[0007] The gas feature set is used to train a preset trace decomposition component classification model to generate a target trace decomposition component classification model.

[0008] Trace decomposition components of the fluorine-containing gas sample are detected by a pre-constructed dual-layer sensing device, and trace decomposition component data are generated.

[0009] The target trace decomposition component classification model is used to perform component detection on the trace decomposition component data to obtain the detection data corresponding to the fluorine-containing gas sample.

[0010] Optionally, the step of training a preset trace decomposition component classification model using the gas feature set to generate a target trace decomposition component classification model includes:

[0011] The gas feature set is used as input to train a preset trace decomposition component classification model to obtain training detection data. The trace decomposition component classification model includes a classifier and a BP neural network.

[0012] The training loss function value of the gas feature set is calculated based on the training detection data;

[0013] When the training loss function value is greater than or equal to the preset standard loss value, the network parameters of the trace decomposition component classification model are adjusted using a preset parameter adjustment method until the training loss function value is less than the standard loss value.

[0014] When the training loss function value is less than the standard loss value, a target trace decomposition component classification model is generated.

[0015] Optionally, the step of using the gas feature set as input to train a preset trace decomposition component classification model to obtain training detection data includes:

[0016] The gas feature set is classified using the classifier to obtain training gas classification data.

[0017] The BP neural network is used to detect the concentration of the training gas classification data to obtain training detection data.

[0018] Optionally, the dual-layer sensing device includes a filter layer, a sensing layer, and interdigitated electrodes. The step of detecting trace decomposition components of the fluorine-containing gas sample using the pre-constructed dual-layer sensing device and generating trace decomposition component data includes:

[0019] The fluorine-containing gas sample is filtered through the filter layer to obtain a trace decomposition component gas sample.

[0020] The trace decomposition component gas sample is added to the sensing layer to generate the target sensing layer;

[0021] The conductivity of the target sensing layer was detected using interdigitated electrodes to obtain initial trace decomposition component data.

[0022] The initial trace decomposition component data is preprocessed to obtain trace decomposition component data.

[0023] Optionally, the filter layer is made of Co3(HITP)2 material.

[0024] Optionally, the sensing layer is at least one of SnO2 material, Pd-SnO2 material, and MoS2-SnO2 material.

[0025] A second aspect of the present invention provides a trace decomposition component detection system for fluorine-containing insulating gases, comprising:

[0026] The acquisition module is used to acquire fluorine-containing gas sample and multiple training gas data, and to preprocess all the training gas data to generate a gas feature set;

[0027] The training module is used to train a preset trace decomposition component classification model using the gas feature set to generate a target trace decomposition component classification model.

[0028] The trace decomposition component detection module is used to detect trace decomposition components in the fluorine-containing gas sample through a pre-constructed dual-layer sensing device and generate trace decomposition component data.

[0029] The component detection module is used to perform component detection on the trace decomposition component data using the target trace decomposition component classification model, and obtain the detection data corresponding to the fluorine-containing gas sample.

[0030] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the preceding claims.

[0031] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the preceding claims.

[0032] The fifth aspect of the present invention provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the preceding claims.

[0033] As can be seen from the above technical solutions, the present invention has the following advantages:

[0034] This invention utilizes a pre-constructed dual-layer sensing device to detect trace decomposition components in fluorine-containing gas samples, generating trace decomposition component data. The dual-layer sensing device shields against interference from fluorine-containing gas during the detection of trace decomposition components, thereby accurately acquiring the data through changes in the conductivity of the dual-layer sensing device. This overcomes the technical problem in existing electrical equipment where trace decomposition component gas detection primarily relies on nanomaterial-based sensors, neglecting the interference of fluorine-containing gas, leading to inaccurate detection of trace decomposition components within the fluorine-containing gas and reduced reliability of the electrical equipment. Compared to traditional trace decomposition component gas detection methods, this invention eliminates the need to consider the interference of fluorine-containing gas in the detection process, improving detection efficiency while ensuring sample integrity, facilitating subsequent component analysis, and enhancing the reliability of electrical equipment operation. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of the steps for detecting trace decomposition components of fluorine-containing insulating gas according to Embodiment 1 of the present invention;

[0037] Figure 2 This is a schematic diagram of the structure of the sensing layer and shielding layer provided in Embodiment 1 of the present invention;

[0038] Figure 3 This is a schematic diagram of the structure of the dual-layer sensing device provided in Embodiment 1 of the present invention;

[0039] Figure 4 This is a schematic diagram of the response of the SnO2 sensor pair to trace decomposition component gases provided in Embodiment 1 of the present invention.

[0040] Figure 5 This is a schematic diagram of the response of a SnO2 sensor with a Co3(HITP)2 coating layer provided in Embodiment 1 of the present invention to trace decomposition component gases.

[0041] Figure 6 This is a schematic diagram of the response of the Pd-SnO2 sensor provided in Embodiment 1 of the present invention to trace decomposition component gases;

[0042] Figure 7This is a schematic diagram of the response of a Pd-SnO2 sensor pair coated with a Co3(HITP)2 capping layer to trace decomposition component gases provided in Embodiment 1 of the present invention.

[0043] Figure 8 This is a schematic diagram of the response of a MoS2-SnO2 sensor pair coated with a Co3(HITP)2 capping layer to trace decomposition component gases provided in Embodiment 1 of the present invention.

[0044] Figure 9 This is a schematic diagram of the response of the MoS2-SnO2 sensor provided in Embodiment 1 of the present invention to trace decomposition component gases;

[0045] Figure 10 This is a flowchart of the steps for detecting trace decomposition components of fluorine-containing insulating gas according to Embodiment 2 of the present invention;

[0046] Figure 11 This is a structural block diagram of a trace decomposition component detection system for fluorine-containing insulating gas provided in Embodiment 3 of the present invention;

[0047] Figure 12 This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention;

[0048] The meanings of the reference numerals in the attached figures are as follows:

[0049] 1. Fluorine-containing gas sample; 2. Shielding layer; 3. Sensing layer; 4. Interdigitated electrode. Detailed Implementation

[0050] This invention provides a method and system for detecting trace decomposition components in fluorinated insulating gases. It addresses the technical problem that existing electrical equipment primarily detects trace decomposition components using nanomaterial-based sensors, but neglects the interference of fluorinated gases on the sensors, resulting in inaccurate detection of trace decomposition components within the fluorinated gases and reduced reliability of electrical equipment operation.

[0051] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0052] Please see Figure 1 , Figure 1 The flowchart illustrates the steps of a method for detecting trace decomposition components of fluorine-containing insulating gas according to Embodiment 1 of the present invention.

[0053] This invention provides a method for detecting trace decomposition components in fluorine-containing insulating gases, comprising:

[0054] Step 101: Obtain fluorine-containing gas samples and multiple training gas data, and preprocess all training gas data to generate a gas feature set;

[0055] Training gas data refers to trace decomposition component gas data of known components.

[0056] Preprocessing refers to cleaning and smoothing the data to generate a gas feature set consisting of multiple conductivity characteristics.

[0057] In this embodiment of the invention, after acquiring a fluorine-containing gas sample and multiple training gas data, all training gas data are preprocessed to generate a gas feature set.

[0058] Step 102: Train the preset trace decomposition component classification model using the gas feature set to generate the target trace decomposition component classification model.

[0059] In this embodiment of the invention, a gas feature set is used to train a preset trace decomposition component classification model to generate a target trace decomposition component classification model. The trace decomposition component classification model includes a classifier and a BP neural network connected in sequence.

[0060] Step 103: Detect trace decomposition components in a fluorine-containing gas sample using a pre-constructed dual-layer sensing device to generate trace decomposition component data.

[0061] In this embodiment of the invention, a preset dual-layer sensing device is used to detect trace decomposition components of fluorine-containing gas sample 1 to obtain trace decomposition component data.

[0062] It should be noted that, for reference Figures 2-3As shown, the dual-layer sensing device includes a sensing layer 3 and a shielding layer 2. Sensing layer 3 utilizes metal oxide nanofibers, a common material in metal oxide sensors, to detect trace decomposition component gases. Compared to other gas-sensitive materials, metal oxides offer advantages such as fast response, good stability, and simple preparation. Shielding layer 2 employs a two-dimensional metal-organic framework (MOF) as a capping layer to effectively mitigate interference from high-concentration fluorine-containing gases and couples it with the highly selective gas sensing layer 3. The molecular dynamics diameters and electron affinities of fluorine-containing greenhouse gases and their trace decomposition components differ, providing a unique opportunity for selective sensing via MOFs. The active metal sites in MOFs tend to interact strongly with fluorine-containing greenhouse gas molecules, effectively immobilizing them on the surface. Simultaneously, their high-flux microporous structure facilitates the unimpeded entry of trace decomposition component molecules into the underlying sensing substrate. Furthermore, the planar geometry of MOFs differs from that of three-dimensional MOFs, making them ideal capping layers that can introduce selective filtration while preserving and potentially amplifying the sensing characteristics of the substrate.

[0063] It is worth mentioning that the construction process of the dual-layer sensing device is as follows:

[0064] 1. Solutions of SnO2, Pd-SnO2, and MoS2-SnO2 were prepared separately, and after sonication for 1 hour, 10 μL of each solution was added dropwise to the surface of interdigitated electrode 4. After vacuum drying at 65℃ for 6 hours, a gas-sensitive layer (i.e., sensing layer) was formed. The concentrations of SnO2, Pd-SnO2, and MoS2-SnO2 solutions were all 1 mg / 40 μL.

[0065] 2. The screening layer material solution is dropped onto the surface of the dry gas-sensitive layer by screen printing in a 2.5 μL manner. After vacuum drying at 65℃ for 6 hours, the screening layer is formed, and a sensor for detecting the decomposition components of local faults in C4F7N is obtained. The screening layer material solution can be Co3(HITP)2, and the concentration of the screening layer material solution is 1 mg / 200 μL.

[0066] It is worth mentioning that, referring to Comparative Example 1: SnO2, Pd-SnO2, and MoS2-SnO2 were each prepared into 1 mg / 40 μL solutions. After 1 hour of sonication, 10 μL of each solution was added dropwise to the surface of the interdigitated electrode. After vacuum drying at 65°C for 6 hours, a sensor for detecting local fault decomposition components in C4F7N was obtained. At room temperature, the sensors prepared according to this invention and Comparative Example 1 were placed in a resistance detection device. A mixed gas (6% C4F7N / 94% CO2) was first introduced into the device for a period of time until the sensor resistance stabilized. Subsequently, different types and concentrations of fault decomposition component gases (C3F6, CO, CHF3) were introduced into the device, and the change in sensor resistance was observed. When the response approached saturation, the mixed gas (6% C4F7N / 94% CO2) was reintroduced. The test results are as follows... Figure 4-9 As shown, the SnO2 sensor exhibits a highly linear response to C3F6, CO, and CHF3 in the concentration range of 10–50 ppm. C3F6 shows the highest response value at 50 ppm (13.1%), while CO and CHF3 show lower response values ​​(7.3% and 6.0%, respectively). With a Co3(HITP)2 coating, the sensor responses to C3F6, CO, and CHF3 at 50 ppm increase to 43.1%, 21.4%, and 25.2%, respectively. At a concentration of 50 ppm, Pd-SnO2 shows a response of 101.77% to CO, 62.06% to C3F6, and 22.97% to CHF3. MoS2-SnO2 shows a response value of 56.36% to CHF3, 38.98% to CO, and 27.1% to C3F6. The introduction of the Co3(HITP)2 coating significantly improves the sensor response. Therefore from Figure 4-9 It can be seen that the presence of the Co3(HITP)2 screening layer greatly improves the sensor’s sensitivity to C3F6, CO, and CHF3.

[0067] Step 104: Use the target trace decomposition component classification model to perform component detection on the trace decomposition component data to obtain the detection data corresponding to the fluorine-containing gas sample.

[0068] In this embodiment of the invention, trace decomposition component data are input into a target trace decomposition component classification model for component detection to obtain detection data corresponding to the fluorine-containing gas sample.

[0069] It should be noted that the detection data includes the types of trace decomposition component gases and the concentration of each type of trace decomposition component gas.

[0070] In this embodiment of the invention, a pre-constructed dual-layer sensing device is used to detect trace decomposition components in a fluorine-containing gas sample, generating trace decomposition component data. The dual-layer sensing device shields the fluorine-containing gas from interference with the detection of trace decomposition components, thus accurately acquiring the trace decomposition component data of the fluorine-containing gas sample through changes in the conductivity of the dual-layer sensing device. This overcomes the technical problem in existing electrical equipment where trace decomposition component gas detection is mainly performed using nanomaterial-based sensors, but the interference of fluorine-containing gas on the sensor is ignored, resulting in inaccurate detection of trace decomposition components within the fluorine-containing gas and reduced reliability of the electrical equipment. Compared with traditional trace decomposition component gas detection methods, this invention does not need to consider the interference of fluorine-containing gas on the detection process, which not only improves detection efficiency but also ensures sample integrity, facilitating subsequent component analysis and improving the reliability of the electrical equipment.

[0071] Please see Figure 10 , Figure 10 This is a flowchart illustrating the steps of a method for detecting trace decomposition components of fluorine-containing insulating gas according to Embodiment 2 of the present invention.

[0072] This invention provides a method for detecting trace decomposition components in fluorine-containing insulating gases, comprising:

[0073] Step 201: Obtain fluorine-containing gas sample and multiple training gas data, and preprocess all training gas data to generate a gas feature set;

[0074] In this embodiment of the invention, after obtaining a fluorine-containing gas sample and multiple training gas data, all training gas data are cleaned and smoothed to generate a gas feature set.

[0075] Step 202: Train the pre-set trace decomposition component classification model using the gas feature set input to obtain training detection data. The trace decomposition component classification model includes a classifier and a BP neural network.

[0076] Further, step 202 includes the following sub-steps:

[0077] S11. Classify the gas feature set using a classifier to obtain training gas classification data;

[0078] In this embodiment of the invention, a classifier (k-nearest neighbor algorithm) is used to classify the gas feature set to obtain training gas classification data.

[0079] It should be noted that the classifier is the k-nearest neighbor algorithm, which performs preliminary classification of the gas feature set by comparing it with known gas data. For example, the type of gas is identified by calculating the distance between the change in conductivity and the known gas concentration.

[0080] In another embodiment, the classifier can be a Support Vector Machine (SVM), K-Nearest Neighbors algorithm, XGBoost algorithm, or LightGBM algorithm, up to one. When multiple classifiers are used, weights are assigned to each algorithm, and the classification results calculated by each algorithm are weighted to obtain the final classification result.

[0081] S12. Use a BP neural network to detect the concentration of the training gas classification data to obtain training detection data.

[0082] In this embodiment of the invention, a BP neural network is used to detect the concentration of training gas classification data to obtain training detection data.

[0083] It should be noted that the classifier and the BP neural network are connected in sequence, and the weights are adjusted through the backpropagation algorithm of the BP neural network to minimize the error and further improve the detection accuracy.

[0084] Step 203: Calculate the training loss function value of the gas feature set based on the training detection data;

[0085] In this embodiment of the invention, training result data associated with training detection data in the gas feature set is obtained, the deviation value between the training detection data and the training result data is calculated, and the deviation value is used as the training loss function value of the gas feature set.

[0086] Step 204: When the training loss function value is greater than or equal to the preset standard loss value, the network parameters of the trace decomposition component classification model are adjusted using the preset parameter adjustment method until the training loss function value is less than the standard loss value.

[0087] It should be noted that the parameter adjustment method can be gradient descent, grid search, or random search.

[0088] In this embodiment of the invention, it is determined that the training loss function value is less than the preset standard loss value. If the training loss function value is greater than or equal to the standard loss value, the network parameters of the trace decomposition component classification model are adjusted by gradient descent, grid search, or random search until the training loss function value is less than the standard loss value.

[0089] Step 205: When the training loss function value is less than the standard loss value, a target trace decomposition component classification model is generated.

[0090] In this embodiment of the invention, if the training loss function value is less than the standard loss value, a target trace decomposition component classification model is generated.

[0091] Step 206: Detect trace decomposition components in a fluorine-containing gas sample using a pre-constructed dual-layer sensing device to generate trace decomposition component data.

[0092] Furthermore, the dual-layer sensing device includes a filter layer, a sensing layer, and interdigitated electrodes. Step 206 includes the following sub-steps:

[0093] It should be noted that the mass ratio of the filter layer material to the sensing layer material is 20:1.

[0094] S21. The fluorine-containing gas sample is filtered through a filter layer to obtain a trace decomposition component gas sample.

[0095] It should be noted that the filter layer is made of Co3(HITP)2 material.

[0096] In this embodiment of the invention, based on the active metal sites of the filter layer (i.e., the two-dimensional metal-organic framework capping layer), fluorine-containing gas molecules in the fluorine-containing gas sample are fixed to the surface of the filter layer, and the high-throughput microporous structure of the filter layer allows trace decomposition component molecules to pass through unimpeded, thereby achieving filtration of the fluorine-containing gas sample and obtaining a trace decomposition component gas sample.

[0097] S22. Add the trace decomposition component gas sample to the sensing layer to generate the target sensing layer;

[0098] It should be noted that the sensing layer is at least one of SnO2 material, Pd-SnO2 material, and MoS2-SnO2 material.

[0099] In this embodiment of the invention, a trace decomposition component gas sample is added to the sensing layer, and the trace decomposition component gas sample reacts chemically with the metal oxide gas-sensitive material (such as SnO2, Pd-SnO2, MoS2-SnO2) of the sensing layer to obtain the target sensing layer.

[0100] S23. Use interdigitated electrodes to detect the conductivity of the target sensing layer to obtain initial trace decomposition component data;

[0101] In this embodiment of the invention, the conductivity changes during the chemical reaction between the trace decomposition component gas sample and the metal oxide gas-sensitive material (such as SnO2, Pd-SnO2, MoS2-SnO2) of the sensing layer are obtained in real time using interdigitated electrodes to obtain initial trace decomposition component data.

[0102] S24. Perform data preprocessing on the initial trace decomposition component data to obtain trace decomposition component data.

[0103] In this embodiment of the invention, the initial trace decomposition component data is filtered and denoised to obtain trace decomposition component data.

[0104] It should be noted that by filtering and denoising the initial trace decomposition component data, errors caused by background noise or internal sensor interference are removed.

[0105] Step 207: Use the target trace decomposition component classification model to perform component detection on the trace decomposition component data to obtain the detection data corresponding to the fluorine-containing gas sample.

[0106] In this embodiment of the invention, trace decomposition component data are input into a target trace decomposition component classification model for component detection to obtain detection data corresponding to the fluorine-containing gas sample.

[0107] It's worth noting that after obtaining the detection data for the fluorine-containing gas sample, the data can be loaded into the feedback component within the detection page, rendered, and a detection page containing the data generated can be created. Simultaneously, if the concentration of trace decomposition component gas in the detection data exceeds a set safety threshold, an alarm will be triggered on the detection page.

[0108] In this embodiment of the invention, a pre-constructed dual-layer sensing device is used to detect trace decomposition components in a fluorine-containing gas sample, generating trace decomposition component data. The dual-layer sensing device shields the fluorine-containing gas from interference with the detection of trace decomposition components, thus accurately acquiring the trace decomposition component data of the fluorine-containing gas sample through changes in the conductivity of the dual-layer sensing device. This overcomes the technical problem in existing electrical equipment where trace decomposition component gas detection is mainly performed using nanomaterial-based sensors, but the interference of fluorine-containing gas on the sensor is ignored, resulting in inaccurate detection of trace decomposition components within the fluorine-containing gas and reduced reliability of the electrical equipment. Compared with traditional trace decomposition component gas detection methods, this invention does not need to consider the interference of fluorine-containing gas on the detection process, which not only improves detection efficiency but also ensures sample integrity, facilitating subsequent component analysis and improving the reliability of the electrical equipment.

[0109] Please see Figure 11 , Figure 11 This is a structural block diagram of a trace decomposition component detection system for fluorine-containing insulating gas provided in Embodiment 3 of the present invention.

[0110] This invention provides a trace decomposition component detection system for fluorine-containing insulating gases, comprising:

[0111] The acquisition module 301 is used to acquire fluorine-containing gas sample and multiple training gas data, and preprocess all training gas data to generate a gas feature set.

[0112] Training module 302 is used to train a preset trace decomposition component classification model using a gas feature set to generate a target trace decomposition component classification model.

[0113] The trace decomposition component detection module 303 is used to detect trace decomposition components in a fluorine-containing gas sample through a pre-constructed dual-layer sensing device and generate trace decomposition component data.

[0114] The component detection module 304 is used to perform component detection on trace decomposition component data using a target trace decomposition component classification model to obtain the detection data corresponding to the fluorine-containing gas sample.

[0115] Furthermore, training module 302 includes:

[0116] The training submodule is used to train a pre-set trace decomposition component classification model using a gas feature set as input to obtain training detection data. The trace decomposition component classification model includes a classifier and a BP neural network.

[0117] The first analysis submodule is used to calculate the training loss function value of the gas feature set based on the training detection data;

[0118] The second analysis submodule is used to adjust the network parameters of the trace decomposition component classification model using a preset parameter adjustment method when the training loss function value is greater than or equal to the preset standard loss value, until the training loss function value is less than the standard loss value.

[0119] When the training loss function value is less than the standard loss value, a target trace decomposition component classification model is generated.

[0120] Furthermore, the training submodule includes:

[0121] The classification unit is used to classify the gas feature set by a classifier to obtain training gas classification data.

[0122] The concentration detection unit is used to detect the concentration of training gas classification data using a BP neural network to obtain training detection data.

[0123] Furthermore, the dual-layer sensing device includes a filter layer, a sensing layer, and interdigitated electrodes; the trace decomposition component detection module 303 includes:

[0124] The filtration submodule is used to filter fluorine-containing gas samples through a filter layer to obtain trace decomposition component gas samples.

[0125] The mixing submodule is used to add trace decomposition component gas samples into the sensing layer to generate the target sensing layer;

[0126] The conductivity detection submodule is used to perform conductivity detection on the target sensing layer using interdigitated electrodes to obtain initial trace decomposition component data.

[0127] The preprocessing submodule is used to preprocess the initial trace decomposition component data to obtain the trace decomposition component data.

[0128] Furthermore, the filter layer is made of Co3(HITP)2 material.

[0129] Furthermore, the sensing layer is at least one of SnO2 material, Pd-SnO2 material, and MoS2-SnO2 material.

[0130] Please see Figure 12 , Figure 12 This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention.

[0131] An electronic device according to an embodiment of the present invention includes: a memory 401 and a processor 402. The memory 401 stores a computer program. When the computer program is executed by the processor 402, the processor 402 performs the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the above embodiments.

[0132] Memory 401 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 401 has storage space 403 for program code 413 for performing any of the method steps described above. For example, storage space 403 for program code may include individual program codes 413 for implementing the various steps in the methods described above. This program code may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above.

[0133] Embodiment 5 of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the above embodiments.

[0134] Embodiment 6 of the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer performs the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any of the above embodiments.

[0135] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0137] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0138] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0140] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting trace decomposition components in fluorine-containing insulating gases, characterized in that, include: Acquire fluorine-containing gas samples and multiple training gas data, and preprocess all the training gas data to generate a gas feature set; The gas feature set is used to train a preset trace decomposition component classification model to generate a target trace decomposition component classification model. Trace decomposition components of the fluorine-containing gas sample are detected by a pre-constructed dual-layer sensing device, and trace decomposition component data are generated. The target trace decomposition component classification model is used to perform component detection on the trace decomposition component data to obtain the detection data corresponding to the fluorine-containing gas sample.

2. The method for detecting trace decomposition components of fluorine-containing insulating gas according to claim 1, characterized in that, The step of training a preset trace decomposition component classification model using the gas feature set to generate a target trace decomposition component classification model includes: The gas feature set is used as input to train a preset trace decomposition component classification model to obtain training detection data. The trace decomposition component classification model includes a classifier and a BP neural network. The training loss function value of the gas feature set is calculated based on the training detection data; When the training loss function value is greater than or equal to the preset standard loss value, the network parameters of the trace decomposition component classification model are adjusted using a preset parameter adjustment method until the training loss function value is less than the standard loss value. When the training loss function value is less than the standard loss value, a target trace decomposition component classification model is generated.

3. The method for detecting trace decomposition components of fluorine-containing insulating gas according to claim 2, characterized in that, The step of training a preset trace decomposition component classification model using the gas feature set to obtain training detection data includes: The gas feature set is classified using the classifier to obtain training gas classification data. The BP neural network is used to detect the concentration of the training gas classification data to obtain training detection data.

4. The method for detecting trace decomposition components of fluorine-containing insulating gas according to claim 1, characterized in that, The dual-layer sensing device includes a filter layer, a sensing layer, and interdigitated electrodes. The step of detecting trace decomposition components of the fluorine-containing gas sample using the pre-constructed dual-layer sensing device and generating trace decomposition component data includes: The fluorine-containing gas sample is filtered through the filter layer to obtain a trace decomposition component gas sample. The trace decomposition component gas sample is added to the sensing layer to generate the target sensing layer; The conductivity of the target sensing layer was detected using interdigitated electrodes to obtain initial trace decomposition component data. The initial trace decomposition component data is preprocessed to obtain trace decomposition component data.

5. The method for detecting trace decomposition components of fluorine-containing insulating gas according to claim 4, characterized in that, The filter layer is made of Co3(HITP)2 material.

6. The method for detecting trace decomposition components of fluorine-containing insulating gas according to claim 4, characterized in that, The sensing layer is at least one of SnO2 material, Pd-SnO2 material, and MoS2-SnO2 material.

7. A system for detecting trace decomposition components of fluorine-containing insulating gases, characterized in that, include: The acquisition module is used to acquire fluorine-containing gas sample and multiple training gas data, and to preprocess all the training gas data to generate a gas feature set; The training module is used to train a preset trace decomposition component classification model using the gas feature set to generate a target trace decomposition component classification model. The trace decomposition component detection module is used to detect trace decomposition components in the fluorine-containing gas sample through a pre-constructed dual-layer sensing device and generate trace decomposition component data. The component detection module is used to perform component detection on the trace decomposition component data using the target trace decomposition component classification model, and obtain the detection data corresponding to the fluorine-containing gas sample.

8. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the method for detecting trace decomposition components of fluorine-containing insulating gas as described in any one of claims 1-6.

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