A high-spectral imaging-based power equipment wire pipe internal joint state analysis system

Abstract

This invention provides a system for analyzing the internal joint status of electrical conduits based on hyperspectral imaging, belonging to the field of electrical equipment testing technology. It includes a signal acquisition module and a data processing module. The signal acquisition module comprises a probe-type hyperspectral imaging unit, a spectral feature extraction unit, and a spatial feature extraction unit. The probe-type hyperspectral imaging unit penetrates deep into the conduit containing the wires to acquire hyperspectral images of the internal environment and transmits these images to the spectral feature extraction unit and the spatial feature extraction unit. The spectral feature extraction unit extracts characteristic spectra from the hyperspectral images, generates a material distribution map, and transmits it to the data processing module. The spatial feature extraction module extracts morphological features from the hyperspectral images, generates a spatial feature map, and transmits it to the data processing module. The data processing module analyzes the internal joint status of the conduit based on the material distribution map and the spatial feature map.

Description

Technical Field

[0001] This invention relates to the field of power equipment testing technology, and in particular to a system for analyzing the internal joint status of power equipment conduits based on hyperspectral imaging. Background Technology

[0002] As a crucial protective structure for power lines, the condition of the internal joints in electrical conduits directly affects the safe operation of the power system. Inspecting the condition of the conductor joints inside the conduits to accurately identify whether they are joints on conductors rather than discarded joints or joints on other components is a key step in determining the presence of illegal joints within the conduit and a vital foundation for ensuring the safe operation of on-site electrical equipment.

[0003] Existing systems, such as the Chinese invention patent application number "202410606909.5", disclose a system for analyzing the internal joint status of electrical conduits using penetrating visual inspection. The system includes: a penetrating camera that enters the conduit containing wires to perform real-time video recording of the conduit's internal environment; and an audio warning mechanism that, when a binary identifier output by a deep neural network model indicates contact between the wires and joints, plays a warning audio file indicating that the internal joint is a wire joint, not a discarded joint or a joint on other components. However, this system primarily relies on the surface features of color and texture in visible light images for identification, making it susceptible to interference from uneven lighting inside the conduit, wire oxidation and discoloration, and dirt obscuring the surface. This limits the accuracy of the identification and makes it difficult to accurately distinguish between wire joints and discarded joints or joints on other components. Summary of the Invention

[0004] In view of this, it is necessary to provide a system for analyzing the internal joint status of electrical equipment conduits based on hyperspectral imaging, in order to solve the technical problem that the existing technology mainly relies on the surface features of color and texture of visible light images for identification, which is easily affected by factors such as uneven lighting inside the conduit, discoloration of the wires due to oxidation, and obstruction by dirt, resulting in limited identification accuracy and difficulty in accurately distinguishing wire joints from discarded joints or joints on other components.

[0005] This invention provides a system for analyzing the internal joint status of electrical conduits based on hyperspectral imaging, comprising a signal acquisition module and a data processing module. The signal acquisition module is connected to the data processing module. The signal acquisition module includes a probe-type hyperspectral imaging unit, a spectral feature extraction unit, and a spatial feature extraction unit. The spectral feature extraction unit and the spatial feature extraction unit are electrically connected to the probe-type hyperspectral imaging unit. The data processing module is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The probe-type hyperspectral imaging unit penetrates deep into the conduit containing the wires, acquires hyperspectral images of the internal environment of the conduit, and transmits the hyperspectral images to the spectral feature extraction unit and the spatial feature extraction unit. The spectral feature extraction unit extracts characteristic spectra from the hyperspectral images, generates a material distribution map, and transmits it to the data processing module. The spatial feature extraction module extracts morphological features from the hyperspectral images, generates a spatial feature map, and transmits it to the data processing module. The data processing module analyzes the state of the internal joints of the conduit based on the material distribution map and the spatial feature map.

[0006] Preferably, the probe-type hyperspectral imaging unit includes a probe rod, a miniature hyperspectral imaging probe, an illumination element, and a first transmission unit. The miniature hyperspectral imaging probe is disposed at the front end of the probe rod, the illumination element is arranged around the miniature hyperspectral imaging probe, the first transmission unit is disposed on the probe rod, the miniature hyperspectral imaging probe is electrically connected to the first transmission unit, and the first transmission unit is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The probe rod extends into the conduit to deliver the miniature hyperspectral imaging probe and the illumination unit to the test position inside the conduit. The illumination element is used to provide illumination inside the conduit. The miniature hyperspectral imaging probe is used to acquire hyperspectral images, and the first transmission unit is used to transmit the hyperspectral images to the spectral feature extraction unit and the spatial feature extraction unit.

[0007] Preferably, the first transmission unit includes an image preprocessing unit and a transmission unit. The image preprocessing unit is electrically connected to the miniature hyperspectral imaging probe, and the transmission unit is electrically connected to the image preprocessing unit. The spectral feature extraction unit and the spatial feature extraction unit are both connected to the transmission unit. The image preprocessing unit is used to correct, denoise, and normalize the hyperspectral image acquired by the miniature hyperspectral imaging probe. The transmission unit is used to transmit the hyperspectral image processed by the image preprocessing unit to the spectral feature extraction unit and the spatial feature extraction unit.

[0008] Preferably, the spectral feature extraction unit includes a first receiving unit, a spectral database, a spectral matching unit, and a second transmission unit. The first receiving unit, the spectral matching unit, and the second transmission unit are electrically connected in sequence. The spectral database is electrically connected to the spectral matching unit. The probe-type hyperspectral imaging unit is electrically connected to the first receiving unit. The data processing module is connected to the second transmission unit. The spectral database module is used to store standard characteristic spectral curves of wire materials, insulating materials, and other component materials. The spectral matching unit is used to match the spectral curves of each pixel in the hyperspectral image received by the first receiving unit with the standard characteristic spectral curves to generate a material distribution map. The second transmission unit is used to transmit the material distribution map to the data processing module.

[0009] Preferably, the spatial feature extraction unit includes a second receiving unit, an edge feature extraction unit, a texture feature extraction unit, a fusion unit, and a third transmission unit. The edge feature extraction unit and the texture feature extraction unit are both electrically connected to the second receiving unit. The fusion unit is electrically connected to the edge feature extraction unit, the texture feature extraction unit, and the third transmission unit. The data processing module is connected to the third transmission unit. The edge feature extraction unit is used to perform edge detection on the hyperspectral image received by the second receiving unit, extract edge features, and generate an edge feature map. The texture feature extraction unit is used to perform texture analysis on the hyperspectral image received by the second receiving unit, extract texture features, and generate a texture feature map. The fusion unit is used to fuse the edge feature map and the texture feature map to generate a spatial feature map. The third transmission unit is used to transmit the spatial feature map to the data processing module.

[0010] Preferably, the data processing module includes a third receiving unit, a fusion analysis unit, and an output unit. The third receiving unit is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The fusion analysis unit is electrically connected to the third receiving unit, and the output unit is electrically connected to the fusion analysis unit. The third receiving unit is used to receive material distribution maps and spatial feature maps. The fusion analysis unit is used to fuse and analyze the material distribution maps and spatial feature maps to identify the contact state and material type of the wire and the connector. The output unit is used to output the identification results.

[0011] Preferably, the fusion analysis unit incorporates a deep neural network model to perform feature fusion and classification recognition on the material distribution map and spatial feature map.

[0012] Preferably, the output unit includes a display screen for visually displaying the recognition results.

[0013] As can be seen from the above technical solution, the present invention provides a system for analyzing the internal joint status of electrical equipment conduits based on hyperspectral imaging, including a signal acquisition module and a data processing module. The signal acquisition module is connected to the data processing module. The signal acquisition module includes a probe-type hyperspectral imaging unit, a spectral feature extraction unit, and a spatial feature extraction unit. The spectral feature extraction unit and the spatial feature extraction unit are electrically connected to the probe-type hyperspectral imaging unit. The data processing module is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The probe-type hyperspectral imaging unit penetrates deep into the conduit through which the wires pass, acquires a hyperspectral image of the environment inside the conduit, and transmits the hyperspectral image to the spectral feature extraction unit and the spatial feature extraction unit. The spectral feature extraction unit is used to extract the characteristic spectra in the hyperspectral image, generate a material distribution map, and transmit it to the data processing module. The spatial feature extraction module is used to extract the morphological features of the hyperspectral image, generate a spatial feature map, and transmit it to the data processing module. The data processing module is used to analyze the state of the internal joints of the conduit based on the material distribution map and the spatial feature map.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention uses hyperspectral imaging technology to acquire continuous spectral information for each pixel, effectively distinguishing the different materials of wire metal, insulating materials, and other components. It overcomes the shortcomings of traditional visible light images, which are easily affected by factors such as uneven illumination, wire oxidation, and dirt obstruction, significantly improving the accuracy of joint status identification. Specifically, this invention generates a material distribution map for material identification through a spectral feature extraction unit, and generates a spatial feature map through a spatial feature extraction unit to extract texture and edge morphology features. The data processing module fuses and analyzes the spectral information and spatial information to comprehensively judge the contact status of the wire and the joint from both material and morphology aspects, making the identification results more reliable. Attached Figure Description

[0015] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Figure 1 The functional block diagram of the power equipment conduit internal joint status analysis system based on hyperspectral imaging provided by the present invention is shown.

[0017] Figure 2 This is a functional block diagram of the probe-type hyperspectral imaging unit provided by the present invention.

[0018] Figure 3 This is a functional block diagram of the spectral feature extraction unit provided by the present invention.

[0019] Figure 4 A functional block diagram of the spatial feature extraction unit provided by the present invention.

[0020] Figure 5 A functional block diagram of the data processing module provided by the present invention.

[0021] The figure shows: a power equipment conduit internal joint status analysis system based on hyperspectral imaging 10, a signal acquisition module 110, a probe-type hyperspectral imaging unit 111, a probe rod 1111, a miniature hyperspectral imaging probe 1112, an illumination component 1113, a first transmission unit 1114, an image preprocessing component 11141, a transmission component 11142, a spectral feature extraction unit 112, a first receiving unit 1121, a spectral database 1122, a spectral matching unit 1123, a second transmission unit 1124, a spatial feature extraction unit 113, a second receiving unit 1131, an edge feature extraction unit 1132, a texture feature extraction unit 1133, a fusion unit 1134, a third transmission unit 1135, a data processing module 120, a third receiving unit 121, a fusion analysis unit 122, and an output unit 123. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] In the description of this invention, it should be understood that the terms "upper", "middle", "outer", "inner", "lower", etc., which indicate orientation or positional relationship, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting this invention.

[0024] Please refer to Figures 1 to 5This invention provides a system 10 for analyzing the internal joint status of electrical equipment conduits based on hyperspectral imaging, including a signal acquisition module 110 and a data processing module 120. The signal acquisition module 110 is connected to the data processing module 120. The signal acquisition module 110 includes a probe-type hyperspectral imaging unit 111, a spectral feature extraction unit 112, and a spatial feature extraction unit 113. The spectral feature extraction unit 112 and the spatial feature extraction unit 113 are both electrically connected to the probe-type hyperspectral imaging unit 111. The data processing module 120 is connected to both the spectral feature extraction unit 112 and the spatial feature extraction unit 113. An in-situ hyperspectral imaging unit 111 penetrates deep into a conduit containing wires to acquire hyperspectral images of the environment inside the conduit. The hyperspectral images are then transmitted to a spectral feature extraction unit 112 and a spatial feature extraction unit 113. The spectral feature extraction unit 112 extracts characteristic spectra from the hyperspectral images, generates a material distribution map, and transmits it to a data processing module 120. The spatial feature extraction module extracts morphological features from the hyperspectral images, generates a spatial feature map, and transmits it to the data processing module 120. The data processing module 120 analyzes the state of the joints inside the conduit based on the material distribution map and the spatial feature map.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention can acquire continuous spectral information of each pixel through hyperspectral imaging technology, effectively distinguishing the different materials of wire metal, insulating materials, and other components. It overcomes the defects of traditional visible light images that are easily interfered with by factors such as uneven lighting, wire oxidation, and dirt obstruction, and significantly improves the accuracy of joint status identification. Specifically, the present invention generates a material distribution map through the spectral feature extraction unit 112 for material identification, generates a spatial feature map through the spatial feature extraction unit 113 to extract texture and edge morphology features, and the data processing module 120 fuses and analyzes the spectral information and spatial information to comprehensively judge the contact status of the wire and the joint from both material and morphology aspects, making the identification results more reliable.

[0026] Furthermore, the probe-type hyperspectral imaging unit 111 includes a probe rod 1111, a miniature hyperspectral imaging probe 1112, an illumination element 1113, and a first transmission unit 1114. The miniature hyperspectral imaging probe 1112 is disposed at the front end of the probe rod 1111, the illumination element 1113 is arranged around the miniature hyperspectral imaging probe 1112, and the first transmission unit 1114 is disposed on the probe rod 1111. The miniature hyperspectral imaging probe 1112 is electrically connected to the first transmission unit 1114. The first transmission unit 1114 is connected to both the spectral feature extraction unit 112 and the spatial feature extraction unit 113. In use, the operator can hold the probe rod 1111 and slowly insert the miniature hyperspectral imaging probe 1112 and the illumination element 1113 at its front end into the conduit from the inlet end until it reaches the joint position to be inspected. After reaching the predetermined position, the illumination element 1113 is activated to provide illumination for the environment inside the conduit, and at the same time, the miniature hyperspectral imaging probe 1112 is activated to acquire a hyperspectral image of the current position. The hyperspectral images acquired by the miniature hyperspectral imaging probe 1112 are transmitted in real time to the spectral feature extraction unit 112 and the spatial feature extraction unit 113 via the first transmission unit 1114 for subsequent analysis and processing.

[0027] Furthermore, to ensure prominent features in the hyperspectral images transmitted to the spectral feature extraction unit 112 and the spatial feature extraction unit 113, thereby improving the accuracy of subsequent recognition, the first transmission unit 1114 includes an image preprocessing unit 11141 and a transmission unit 11142. The image preprocessing unit 11141 is electrically connected to the miniature hyperspectral imaging probe 1112, and the transmission unit 11142 is electrically connected to the image preprocessing unit 11141. Both the spectral feature extraction unit 112 and the spatial feature extraction unit 113 are connected to the transmission unit 11142. After the hyperspectral images acquired by the miniature hyperspectral imaging probe 1112 are transmitted to the image preprocessing unit 11141, the image preprocessing unit 11141 sequentially performs the following corrections. The hyperspectral image undergoes denoising and normalization processing. Specifically, calibration processing enables radiometric calibration and spectral alignment of the hyperspectral image to ensure the accuracy of spectral information. Denoising processing removes random noise and background interference from the image, improving the signal-to-noise ratio. Normalization processing maps the hyperspectral image to a uniform scale, eliminating the effects of illumination differences and uneven contrast, enhancing the consistency and comparability of the hyperspectral image, and eliminating errors in the spatial feature extraction unit 113. Finally, the hyperspectral image processed by the image preprocessor 11141 is transmitted by the transmission unit 11142 to the spectral feature extraction unit 112 and the spatial feature extraction unit 113, respectively, for use in the subsequent generation of material distribution maps and spatial feature maps.

[0028] Furthermore, the spectral feature extraction unit 112 includes a first receiving unit 1121, a spectral database 1122, a spectral matching unit 1123, and a second transmission unit 1124. The first receiving unit 1121, the spectral matching unit 1123, and the second transmission unit 1124 are electrically connected in sequence. The spectral database 1122 is electrically connected to the spectral matching unit 1123. The probe-type hyperspectral imaging unit 111 is electrically connected to the first receiving unit 1121. The data processing module 120 is connected to the second transmission unit 1124. During operation, the first receiving unit 1121 receives hyperspectral images from the probe-type hyperspectral imaging unit 111 and transmits the hyperspectral images to the spectral matching unit 1123. The spectral matching unit 1123 first calls the standard characteristic spectral curves pre-stored in the spectral database 1122. The standard characteristic spectral curves include, but are not limited to, standard spectral curves of wire materials, standard spectral curves of insulating materials, and standard spectral curves of common foreign objects. Among them, the wire materials include copper or aluminum, and the insulating materials include PVC or rubber. Next, the spectral matching unit 1123 extracts the spectral curve of each pixel in the hyperspectral image and compares the spectral curve of each pixel with the standard feature spectral curve to calculate similarity indices such as spectral angle or spectral information divergence; thereby determining the material category matched to each pixel based on the above similarity indices. Then, the spectral matching unit 1123 generates a material distribution map based on the material category identification result of each pixel; in the material distribution map, different material regions are marked with different colors or labels to present the spatial distribution of wire regions, joint regions, and other materials. Finally, the second transmission unit 1124 transmits the material distribution map generated by the spectral matching unit 1123 to the data processing module 120.

[0029] Furthermore, the spatial feature extraction unit 113 includes a second receiving unit 1131, an edge feature extraction unit 1132, a texture feature extraction unit 1133, a fusion unit 1134, and a third transmission unit 1135. The edge feature extraction unit 1132 and the texture feature extraction unit 1133 are both electrically connected to the second receiving unit 1131. The fusion unit 1134 is electrically connected to the edge feature extraction unit 1132, the texture feature extraction unit 1133, and the third transmission unit 1135. The data processing module 120 is connected to the third transmission unit 1135. During operation, the second receiving unit 1131 receives hyperspectral images from the probe-type hyperspectral imaging unit 111 and synchronously transmits the hyperspectral images to the edge feature extraction unit 1132 and the texture feature extraction unit 1133. The edge feature extraction unit 1132 performs edge detection processing on the received hyperspectral image. Specifically, the edge feature extraction unit 1132 can use one or more algorithms selected from the Canny operator, Sobel operator, or Laplacian operator to extract edge information from the hyperspectral image and generate an edge feature map. The edge feature map highlights the wire outline, joint boundary, and edge details of the contact area between the two. The texture feature extraction unit 1133 performs texture analysis processing on the received hyperspectral image. Specifically, the texture feature extraction unit 1133 can use one or more algorithms selected from the gray-level co-occurrence matrix, LBP operator, or Gabor filter to extract texture features from the hyperspectral image and generate a texture feature map. The texture feature map reflects the texture distribution, roughness, and uniformity information of the object surface. The fusion unit 1134 receives the edge feature map and the texture feature map and performs feature fusion processing on the two to generate a comprehensive spatial feature map. The spatial feature map simultaneously contains edge contour information and surface texture information, thereby comprehensively reflecting the morphological features of the wire and the joint. Finally, the third transmission unit 1135 transmits the spatial feature map generated by the fusion unit 1134 to the data processing module 120 for subsequent fusion analysis with the material distribution map.

[0030] Furthermore, the data processing module 120 includes a third receiving unit 121, a fusion analysis unit 122, and an output unit 123. The third receiving unit 121 is connected to both the second transmission unit 1124 and the third transmission unit 1135. The fusion analysis unit 122 is electrically connected to the third receiving unit 121, and the output unit 123 is electrically connected to the fusion analysis unit 122. During operation, the third receiving unit 121 simultaneously receives a material distribution map from the spectral feature extraction unit 112 and a spatial feature map from the spatial feature extraction unit 113, and performs time-based processing on the material distribution map and the spatial feature map. The system performs a registration process to ensure that the two data points correspond to the same detection location. The fusion analysis unit 122 comprehensively analyzes the received material distribution map and spatial feature map: First, it identifies the material type of the conductor region and the connector region based on the material distribution map. Second, it verifies the identification result based on the spatial feature map, analyzing whether the relative position and spatial relationship between the conductor and the connector in the material distribution map are correct. Finally, it fuses the material identification result with the spatial relationship analysis result to comprehensively determine whether the conductor and the connector are in contact and whether the connector is a valid connector on the conductor. The output unit 123 outputs identification information based on the judgment result of the fusion analysis unit 122. The identification information includes: contact state (i.e., whether the conductor and the connector are in contact or not); material type (i.e., whether the identified object is a conductor connector, a discarded connector, or a foreign object); and confidence level (i.e., the probability value that the identification result is correct).

[0031] In a preferred embodiment, the fusion analysis unit 122 incorporates a deep neural network model, which is pre-trained using labeled samples. This deep neural network model can comprehensively utilize spectral and spatial information to perform feature fusion and classification recognition of material distribution maps and spatial feature maps, thereby improving the accuracy of identifying the internal joint status of conduits.

[0032] In a preferred embodiment, the output unit 123 is a display screen, which is electrically connected to the fusion analysis unit 122. The display screen can simultaneously display a material distribution map, a spatial feature map, and a detection image marked with the identification results, so that operators can intuitively understand the actual situation of the internal joints of the conduit, thereby providing a basis for on-site decision-making.

[0033] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the invention. Those skilled in the art will understand that implementing all or part of the above-described embodiments and making equivalent changes in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A hyperspectral imaging-based power equipment wire tube internal joint state analysis system, characterized in that: The system includes a signal acquisition module and a data processing module. The signal acquisition module is connected to the data processing module. The signal acquisition module includes a probe-type hyperspectral imaging unit, a spectral feature extraction unit, and a spatial feature extraction unit. The spectral feature extraction unit and the spatial feature extraction unit are electrically connected to the probe-type hyperspectral imaging unit. The data processing module is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The probe-type hyperspectral imaging unit penetrates deep into a conduit containing wires to acquire hyperspectral images of the environment inside the conduit and transmits these images to the spectral feature extraction unit and the spatial feature extraction unit. The spectral feature extraction unit extracts characteristic spectra from the hyperspectral images, generates a material distribution map, and transmits it to the data processing module. The spatial feature extraction module extracts morphological features from the hyperspectral images, generates a spatial feature map, and transmits it to the data processing module. The data processing module analyzes the state of the internal joints of the conduit based on the material distribution map and the spatial feature map.

2. The hyperspectral imaging based power equipment cable tray interior joint condition analysis system of claim 1, wherein: The probe-type hyperspectral imaging unit includes a probe rod, a miniature hyperspectral imaging probe, an illumination element, and a first transmission unit. The miniature hyperspectral imaging probe is disposed at the front end of the probe rod, and the illumination element is arranged around the miniature hyperspectral imaging probe. The first transmission unit is disposed on the probe rod, and the miniature hyperspectral imaging probe is electrically connected to the first transmission unit. The first transmission unit is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The probe rod extends into the conduit to deliver the miniature hyperspectral imaging probe and the illumination unit to the test position inside the conduit. The illumination element is used to provide illumination inside the conduit. The miniature hyperspectral imaging probe is used to acquire hyperspectral images, and the first transmission unit is used to transmit the hyperspectral images to the spectral feature extraction unit and the spatial feature extraction unit.

3. The hyperspectral imaging-based power equipment cable tray interior joint condition analysis system of claim 2, wherein: The first transmission unit includes an image preprocessing unit and a transmission unit. The image preprocessing unit is electrically connected to the miniature hyperspectral imaging probe, and the transmission unit is electrically connected to the image preprocessing unit. The spectral feature extraction unit and the spatial feature extraction unit are both connected to the transmission unit. The image preprocessing unit is used to perform correction, noise reduction, and normalization processing on the hyperspectral image acquired by the miniature hyperspectral imaging probe. The transmission unit is used to transmit the hyperspectral image processed by the image preprocessing unit to the spectral feature extraction unit and the spatial feature extraction unit.

4. The hyperspectral imaging based power utility cable tray internal joint condition analysis system as claimed in claim 1 wherein: The spectral feature extraction unit includes a first receiving unit, a spectral database, a spectral matching unit, and a second transmission unit. The first receiving unit, the spectral matching unit, and the second transmission unit are electrically connected in sequence. The spectral database is electrically connected to the spectral matching unit. The probe-type hyperspectral imaging unit is electrically connected to the first receiving unit. The data processing module is connected to the second transmission unit. The spectral database module is used to store standard characteristic spectral curves of wire materials, insulating materials, and other component materials. The spectral matching unit is used to match the spectral curves of each pixel in the hyperspectral image received by the first receiving unit with the standard characteristic spectral curves to generate a material distribution map. The second transmission unit is used to transmit the material distribution map to the data processing module.

5. The hyperspectral imaging based power utility cable tray joint inside condition analysis system as claimed in claim 1 wherein: The spatial feature extraction unit includes a second receiving unit, an edge feature extraction unit, a texture feature extraction unit, a fusion unit, and a third transmission unit. The edge feature extraction unit and the texture feature extraction unit are electrically connected to the second receiving unit. The fusion unit is electrically connected to the edge feature extraction unit, the texture feature extraction unit, and the third transmission unit. The data processing module is connected to the third transmission unit. The edge feature extraction unit is used to perform edge detection on the hyperspectral image received by the second receiving unit, extract edge features, and generate an edge feature map. The texture feature extraction unit is used to perform texture analysis on the hyperspectral image received by the second receiving unit, extract texture features, and generate a texture feature map. The fusion unit is used to fuse the edge feature map and the texture feature map to generate a spatial feature map. The third transmission unit is used to transmit the spatial feature map to the data processing module.

6. The hyperspectral imaging based power utility cable tray joint inside condition analysis system as claimed in claim 1 wherein: The data processing module includes a third receiving unit, a fusion analysis unit, and an output unit. The third receiving unit is connected to both the spectral feature extraction unit and the spatial feature extraction unit. The fusion analysis unit is electrically connected to the third receiving unit, and the output unit is electrically connected to the fusion analysis unit. The third receiving unit is used to receive material distribution maps and spatial feature maps. The fusion analysis unit is used to fuse and analyze the material distribution maps and spatial feature maps to identify the contact state and material type of the wire and connector. The output unit is used to output the identification results.

7. The system for analyzing the internal joint status of electrical equipment conduits based on hyperspectral imaging as described in claim 6, characterized in that: The fusion analysis unit incorporates a deep neural network model to perform feature fusion and classification recognition on material distribution maps and spatial feature maps.

8. The system for analyzing the internal joint status of electrical equipment conduits based on hyperspectral imaging as described in claim 6, characterized in that: The output unit includes a display screen, which is used to visually display the recognition results.

Images