Performance test platform and test method for thermal defect detection device of overhead line system

Abstract

The invention discloses a performance test platform and test method for a thermal defect detection device of a contact network. The platform comprises a thermal defect detection module, a contact network simulation device, a Sudoku temperature measurement test module and an intelligent control platform, the thermal defect detection module, the contact network simulation device and the Sudoku test module are respectively connected with the intelligent control platform. The trolley is controlled by the intelligent platform to move to simulate operation of the detection vehicle, the sliding table is driven to accurately position the black body to a sudoku designated position, the temperature of the heating piece is adjusted to simulate the heating defect of the contact network component, and automatic testing of five functions is achieved. According to the invention, the problems of low manual test efficiency and insufficient sampling coverage rate are solved, and the test efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of track equipment, and in particular to a performance test platform and a test method for a contact network thermal defect detection device. Background Art

[0002] While electrified railways offer speed, energy efficiency, and high efficiency, ensuring the safe operation of the catenary system in their traction power supply system is a crucial component. However, as line lengths increase and train speeds rise, ensuring reliable operation becomes increasingly challenging, and the workload for routine maintenance and inspections also increases. Due to the widespread distribution of catenary lines, complex equipment structures, volatile operating environments, and the lack of backup lines, monitoring equipment operating status and promptly identifying and eliminating potential hazards is an effective way to mitigate catenary faults and ensure safe train operation. Temperature measurement of the catenary during current-carrying operation directly reflects the reliability of contact at each connection point within the main current circuit. A roof-mounted cooled infrared thermal imager captures real-time temperature images of catenary components. Combined with visible light camera images, image processing and intelligent recognition technologies are used to track temperature changes in key catenary components, enabling the timely identification of thermal defects and potential faults.

[0003] When manufacturers produce contact network thermal defect detection systems, they need to perform performance testing and factory inspections on the assembled systems to verify that all functional and technical specifications meet requirements. Typically, manufacturers perform factory inspections manually, using random sampling. Obviously, when manufacturers need to produce in large quantities, manual factory inspections are labor-intensive and inefficient, and random sampling cannot guarantee product quality. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a performance test platform for a contact network thermal defect detection device, including a track, a thermal defect detection module, a contact network simulation device, a nine-square temperature measurement test module, and an intelligent control platform; The thermal defect detection module, the contact network simulation device, and the nine-square test module are respectively connected to the intelligent control platform; The thermal defect detection module includes a mobile trolley and a thermal defect detection device, which is used to collect images of thermal defects in the contact network to be tested; The catenary simulation device is used to simulate thermal defects of catenary components; The nine-square temperature measurement test module includes a nine-square test module and a linear module, which is used to calibrate the thermal defect detection module; The intelligent control platform is used to control the temperature of the heating plate in the contact network simulation device to simulate different heating defects, and control the thermal defect detection module to perform thermal defect detection.

[0005] Preferably, the nine-grid temperature measurement test module includes a nine-grid test module and a linear module, which is used to calibrate the thermal defect detection module, including: a blackbody radiation source driven by the linear module, verifying the temperature measurement consistency of the thermal defect detection module in the nine-grid test module.

[0006] Preferably, the verification of the temperature measurement consistency of the thermal defect detection module includes: The linear module drives the blackbody radiation source to the center of each of the nine squares of the nine-square grid, and calculates the temperature difference between the temperature value Ct at each position and the temperature of the center square C5 |Ct-C5|. If all temperature differences are less than the temperature difference, the test is passed; otherwise, it fails. In the temperature measurement accuracy verification of the central area, the blackbody is controlled to be positioned at the center square C5 of the nine-square grid. The temperature of the blackbody radiation source is set to different temperature values ​​in sequence to verify whether the temperature measurement error between the temperature collected by the thermal defect detection module and the set temperature is less than the temperature difference. If all temperature differences are less than the temperature difference, it is judged to pass; otherwise, it is failed.

[0007] Preferably, the catenary simulation device is used to simulate thermal defects of catenary components, and includes an insulator simulation module, a dropper wire clamp simulation module, and an isolating switch simulation module; The insulator simulation module, the dropper wire clamp simulation module and the disconnector simulation module are respectively connected to the intelligent control platform; The insulator simulation module includes a heating insulator module and a normal insulator module; the dropper string clamp simulation module includes a heating dropper string clamp module and a normal dropper string clamp module; the heating insulator module, normal insulator module, heating dropper string clamp module, and normal dropper string clamp module are respectively connected to the intelligent control platform; the intelligent control platform controls the heating insulator module, heating dropper string clamp module, and disconnector simulation module to perform heating simulation.

[0008] Preferably, the controlling the thermal defect detection module to perform thermal defect detection includes: The mobile cart is controlled by an intelligent platform to enable the thermal defect detection module to synchronously collect infrared and visible light images of the contact network simulation device; feature point matching and transformation registration are performed on the dual-mode images to generate a fused image; quantitative indicators of the fused image and the source image are calculated. If the quantitative indicators meet the standards, the fusion and registration function is judged to be qualified.

[0009] Preferably, the absolute high temperature alarm verification step is also included: Control the temperature of the disconnector module to rise to the set temperature in sequence, and verify whether the third-level, second-level, and first-level absolute high-temperature alarm files are generated in sequence. If the corresponding high-temperature alarm files are generated, the absolute high-temperature alarm verification is qualified; otherwise, it is unqualified.

[0010] Preferably, it further includes a temperature difference alarm verification step: a. Set stepped temperatures T1, T2, T3 for the heating insulator module, where T1 < T2 < T3, and calculate the temperature difference ΔT from the environment; b. If ΔT reaches the preset alarm threshold, verify that the device under test generates the corresponding level of insulator heating alarm; c. Execute the same process for the heating suspension clamp module to verify the function of generating metal heating alarms.

[0011] A performance test method for a catenary thermal defect detection device, which is applied to the performance test platform of the catenary thermal defect detection device described above, includes: S1. Start the performance test platform S2. Calibrate the thermal defect detection module S21. Temperature measurement consistency verification: Drive the blackbody radiation source through the linear module to locate to the centers of the 9 squares of the nine-square grid in sequence, record the temperature measurement values Ct at each position, and calculate the temperature difference |Ct - C5| from the center square C5; if all temperature differences are less than the preset temperature difference value, it is determined to pass, otherwise it fails; S22. Temperature measurement accuracy verification in the central area: Control the blackbody radiation source to locate to the center square C5 of the nine-square grid, set different temperature values in sequence, and verify the error between the temperature collected by the device under test and the set temperature; if all errors are less than the preset temperature difference value, it is determined to pass, otherwise it fails; S3. Image acquisition and fusion registration function test The intelligent control platform controls the movement of the mobile trolley to enable the device under test to synchronously collect infrared images and visible light images of the catenary simulation device; perform feature point matching and transformation registration on the infrared images and visible light images to generate a fused image; calculate the quantization index of the fused image and the source image. If the index meets the standard, it is determined that the fusion registration function is qualified; S4. Absolute high-temperature alarm verification Control the temperature of the disconnector module in the catenary simulation device to rise to the set temperature in sequence, and verify whether the device under test generates the third-level, second-level, and first-level absolute high-temperature alarm files in sequence; if the corresponding alarm files are generated, it is determined to be qualified, otherwise it is unqualified; S5 Temperature difference alarm verification S51. Set stepped temperatures T1, T2, T3 (T1 < T2 < T3) for the heating insulator module, and calculate the temperature difference ΔT from the environment; when ΔT reaches the preset alarm threshold, verify whether the corresponding level of insulator heating alarm is generated; For the heating suspension clamp module, set step temperatures T1, T2, and T3 (T1 < T2 < T3), and calculate the temperature difference ΔT from the environment. When ΔT reaches the preset alarm threshold, verify the metal heating alarm generation function. If corresponding alarms can be generated, it is judged as qualified; otherwise, it is unqualified.

[0012] The beneficial effects of the present invention are as follows: 1) The performance test platform proposed by the present invention verifies the temperature measurement accuracy by controlling the horizontal / vertical slide table to move the black body to different positions in the nine-square grid up, down, left, and right. By controlling the movement of the trolley through the intelligent platform to simulate the running state of the inspection vehicle and controlling the temperature of the heating sheet to simulate the heating conditions of different components of the catenary, it is tested whether the heating components can be correctly identified during the normal driving of the inspection vehicle and the alarm is uploaded to the intelligent platform for inspection personnel to view, and then the faulty components are replaced. 2) The performance test platform proposed by the present invention simulates the speed of the inspection vehicle by controlling the trolley to travel at different speeds through the intelligent platform, and sets component heating simulation faults in advance in the above area to further verify whether the alarm function of the catenary thermal defect detection system is normal. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the verification process for the temperature measurement consistency of the nine-square grid; Figure 2 It is a schematic diagram of the verification process for the temperature measurement accuracy of the central area; Figure 3 It is a schematic diagram of the verification process for the absolute high-temperature alarm. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] The technical solution of the present invention will be further described in detail below with reference to the drawings, but the protection scope of the present invention is not limited to the following description.

[0015] The features and performance of the present invention will be further described in detail below with reference to the embodiments.

[0016] A performance test platform for a catenary thermal defect detection device includes a track, a thermal defect detection module, a catenary simulation device, a nine-square grid temperature measurement test module, and an intelligent control platform; The thermal defect detection module, the catenary simulation device, and the nine-square grid test module are respectively connected to the intelligent control platform; The thermal defect detection module includes a moving trolley and a thermal defect detection device, and is used to collect images of catenary thermal defects to be measured; The catenary simulation device is used to simulate catenary component thermal defects; The nine-square grid temperature measurement test module includes a nine-square grid test module and a linear module, and is used for calibrating the thermal defect detection module; The intelligent control platform is used to control the temperature of the heating plate in the contact network simulation device to simulate different heating defects, and control the thermal defect detection module to perform thermal defect detection.

[0017] The nine-grid temperature measurement test module includes a nine-grid test module and a linear module, which is used to calibrate the thermal defect detection module, including: a blackbody radiation source driven by the linear module, verifying the temperature measurement consistency of the thermal defect detection module in the nine-grid test module.

[0018] The verification of the temperature measurement consistency of the thermal defect detection module includes: The linear module drives the blackbody radiation source to the center of each of the nine squares of the nine-square grid, and calculates the temperature difference between the temperature value Ct at each position and the temperature of the center square C5 |Ct-C5|. If all temperature differences are less than the temperature difference, the test is passed; otherwise, it fails. In the temperature measurement accuracy verification of the central area, the blackbody is controlled to be positioned at the center square C5 of the nine-square grid. The temperature of the blackbody radiation source is set to different temperature values ​​in sequence to verify whether the temperature measurement error between the temperature collected by the thermal defect detection module and the set temperature is less than the temperature difference. If all temperature differences are less than the temperature difference, it is judged to pass; otherwise, it is failed.

[0019] The catenary simulation device is used to simulate thermal defects of catenary components, and includes an insulator simulation module, a dropper wire clamp simulation module, and an isolating switch simulation module; The insulator simulation module, the dropper wire clamp simulation module and the disconnector simulation module are respectively connected to the intelligent control platform; The insulator simulation module includes a heating insulator module and a normal insulator module; the dropper string clamp simulation module includes a heating dropper string clamp module and a normal dropper string clamp module; the heating insulator module, normal insulator module, heating dropper string clamp module, and normal dropper string clamp module are respectively connected to the intelligent control platform; the intelligent control platform controls the heating insulator module, heating dropper string clamp module, and disconnector simulation module to perform heating simulation.

[0020] The controlling thermal defect detection module to perform thermal defect detection includes: The mobile cart is controlled by an intelligent platform to enable the thermal defect detection module to synchronously collect infrared and visible light images of the contact network simulation device; feature point matching and transformation registration are performed on the dual-mode images to generate a fused image; quantitative indicators of the fused image and the source image are calculated. If the quantitative indicators meet the standards, the fusion and registration function is judged to be qualified.

[0021] Also included are the absolute high temperature alarm verification steps: Control the temperature of the disconnector module to rise to the set temperature in sequence, and verify whether the third-level, second-level, and first-level absolute high-temperature alarm files are generated in sequence. If the corresponding high-temperature alarm file is generated, the absolute high-temperature alarm verification is qualified; otherwise, it is unqualified.

[0022] The steps for differential temperature alarm verification include: a. Set stepped temperatures T1, T2, T3 for the heating insulator module, where T1 < T2 < T3, and calculate the temperature difference ΔT from the environment; b. If ΔT reaches the preset alarm threshold, verify that the device under test generates the corresponding level of insulator heating alarm; c. Execute the same process for the heating suspension clamp module to verify the function of generating metal heating alarms.

[0023] A performance test method for a catenary thermal defect detection device, which is applied to the performance test platform of the catenary thermal defect detection device described above, includes: S1. Start the performance test platform S2. Calibrate the thermal defect detection module S21. Verification of temperature measurement consistency: Drive the blackbody radiation source through the linear module to locate to the centers of the 9 squares of the nine-square grid in sequence, record the temperature measurement values Ct at each position, and calculate the temperature difference |Ct - C5| from the center square C5; if all temperature differences are less than the preset temperature difference, it is determined to pass, otherwise it fails; S22. Verification of temperature measurement accuracy in the central area: Control the blackbody radiation source to locate to the center square C5 of the nine-square grid, set different temperature values in sequence, and verify the error between the temperature collected by the device under test and the set temperature; if all errors are less than the preset temperature difference, it is determined to pass, otherwise it fails; S3. Image acquisition and fusion registration function test The intelligent control platform controls the movement of the mobile trolley to enable the device under test to synchronously collect infrared images and visible light images of the catenary simulation device; perform feature point matching and transformation registration on the infrared image and the visible light image to generate a fused image; calculate the quantization index of the fused image and the source image. If the index meets the standard, it is determined that the fusion registration function is qualified; S4. Absolute high-temperature alarm verification Control the temperature of the disconnector module in the catenary simulation device to rise to the set temperature in sequence, and verify whether the device under test generates third-level, second-level, and first-level absolute high-temperature alarm files in sequence; if the corresponding alarm files are generated, it is determined to be qualified, otherwise it is unqualified; S5 Differential temperature alarm verification S51. Set stepped temperatures T1, T2, T3 (T1 < T2 < T3) for the heating insulator module, and calculate the temperature difference ΔT from the environment; when ΔT reaches the preset alarm threshold, verify whether the corresponding level of insulator heating alarm is generated; For the heating suspension clamp module, set the stepped temperatures T1, T2, T3 (T1 < T2 < T3), and calculate the temperature difference ΔT from the environment. When ΔT reaches the preset alarm threshold, verify the function of generating metal heating alarms. If corresponding alarms can be generated, it is judged as qualified; otherwise, it is unqualified.

[0024] Specifically, based on the present invention, the manufacturer can automatically inspect the catenary components of the catenary thermal defect detection system, including insulation and metal heating defects. The specific technical solutions are as follows: Using the present invention to test the nine-grid temperature measurement function of the catenary thermal defect detection system 1.1 Verification process of nine-grid temperature measurement consistency The inspection process of nine-grid temperature measurement is as Figure 1 shown. The detailed operation steps are as follows: 1) Start the intelligent platform; 2) Control the trolley to move in front of the nine-grid display platform through the intelligent platform, ensuring that the collected image can completely capture the nine-grid area; 3) Manually adjust the blackbody temperature to 100 °C, and the intelligent platform sends instructions to control the horizontal / vertical sliding table to move and place the blackbody in squares 1...9 in sequence, and record the blackbody temperatures C1...C9 collected 9 times.

[0025] According to the obtained blackbody temperatures C1...C9, calculate T = |Ct - C5| (t = 1, 2, 3, 4, 6, 7, 8, 9). If T is less than 2, it meets the factory requirements.

[0026] 2. Using the present invention to test the temperature measurement accuracy function of the central area of the catenary thermal defect detection system Verification process of temperature measurement accuracy in the central area The inspection process of temperature measurement accuracy in the central area is as Figure 2 shown. The detailed operation steps are as follows: 1) Start the intelligent platform; 2) Control the trolley to move in front of the nine-grid display platform through the intelligent platform, ensuring that the collected image can completely capture the nine-grid area; 3) Adjust the blackbody temperature to 50 °C, 100 °C, 150 °C, and 200 °C in sequence; 4) The intelligent platform sends instructions to control the horizontal / vertical sliding table to move and place the blackbody in square 5 in sequence; 5) Output the collected blackbody temperatures C1, C2, C3, and C4 in sequence.

[0027] Based on the obtained blackbody temperatures C1, C2, C3, and C4, calculate T1=|C1-50|, T2=|C2-100|, T3=|C3-150|, and T4=|C4-200| respectively. If T1, T2, T3, and T4 are all less than or equal to 2, the factory requirements are met.

[0028] Heterogeneous image fusion registration verification process The heterogeneous image fusion verification process is designed to verify the accuracy and reliability of the contact line thermal defect detection system when fusing images from different sources (such as infrared thermal imagers and visible light cameras). The following are the detailed steps of this verification process: 1. Start the smart platform: First, start the intelligent control system of the performance test platform to ensure that all components (infrared thermal imager, visible light camera, image acquisition system, etc.) are in standby mode and ready to receive instructions.

[0029] 2. Configure the test environment: A test area was set up on the catenary system, ensuring that it encompassed a variety of catenary components (such as insulators, dropper clamps, and disconnectors) to comprehensively test image fusion and registration capabilities. The parameters of the infrared and visible light cameras were adjusted to ensure that the image clarity captured during the test met the required standards for identifying key catenary components. Image clarity was measured using Laplacian variance, with a standard of ≥ 100 (adjustable) to eliminate blurry images.

[0030] 3. Move the car to the test position: The intelligent platform controls the trolley, which moves along a track to the front of the test area. To ensure coverage of all critical component areas, the fields of view of the infrared thermal imager and visible light camera are calibrated. The mobile platform also fine-tunes the test position several times along the track to ensure that key components (such as heating string clamps and heating insulators) are fully within the field of view. During this process, the boundaries and viewing angles of the captured image are monitored in real time, and the docking position is dynamically adjusted when necessary using an image ROI detection algorithm. 4. Start image acquisition: The image acquisition function is activated on the intelligent platform, controlling both the infrared thermal imager and the visible light camera to simultaneously capture images of the test area. Before image acquisition, the camera system calibration parameters (including exposure, gamma correction, and infrared thermal imaging pseudo-color range) must be loaded through the intelligent platform. Once acquisition begins, the infrared thermal imager captures the thermal distribution of each contacting component, while the visible light image provides the component's structural outline and identifying features. The two are aligned using timestamps to form synchronized image data pairs. All images are cached in the intelligent platform's task processing module and enter the registration process.

[0031] 5. Image registration and fusion processing: The captured infrared and visible light images are uploaded to the intelligent platform for processing. The system first normalizes the infrared and visible light images to unify their resolution and align their scales. Key feature points (such as SIFT, ORB, and SURF) are then extracted for initial matching. The matching results are then filtered using the RANSAC method to remove mismatched points and estimate the homography matrix, which is then used to perform affine or perspective transformation registration. For scenes with complex backgrounds or low-texture images, a joint calibration model is also supported to directly perform coordinate mapping based on camera parameters.

[0032] In the fusion process, the infrared and visible light images are first fed into the convolutional encoding module for feature extraction. The fusion module then assigns weights for the thermal and texture signals using a channel-by-channel attention mechanism. Finally, the upsampling and reconstruction phase produces the fused image. This fused image not only preserves edge structure and color texture but also enhances the contrast and expressiveness of target areas (such as heat-generating components) in the thermal dimension. This fusion result is then used as input to the target recognition model to improve detection accuracy.

[0033] 6. Verify the fusion results: The system automatically compares the fused image with the original image based on template matching and keypoint (SIFT / ORB) descriptors and assesses registration accuracy (e.g., average keypoint matching offset <3 pixels). Manual verification is also available to confirm that key components (such as heating cables and insulators) are positioned consistently in both images and have good edge alignment.

[0034] The quality of the fusion effect can be judged by the following quantitative indicators: Structural Similarity Index (SSIM) ≥ 0.85: used to measure the consistency of image structure, brightness, and texture; Mutual Information (MI) ≥ threshold (e.g., 1.0): indicates the degree of effective information sharing between the fused image and the source image; Edge-Based Similarity (EBS) ≥ 0.9: used to determine whether the outline clarity is preserved. Chi-square distance χ² (such as for histogram difference) ≤ threshold (such as 0.3): measures the difference in overall distribution between the fused image and the original image.

[0035] If more than two of the above indicators meet the set threshold, the fusion quality is judged to be good.

[0036] 7. Record and analyze data: Record key indicators such as acquisition time, temperature value, image registration offset, and signal-to-noise ratio after fusion; and generate an inspection report to determine whether the fusion registration effect meets factory requirements.

[0037] 8. Adjustment and optimization: To improve the stability and generalization of the fusion registration algorithm, the system automatically summarizes the fusion image's registration offset and fusion performance metrics (such as SSIM, MI, and the number of keypoint matches) after testing and generates an analysis report. The platform offers a variety of built-in image fusion algorithms (such as multi-scale wavelet fusion, CNN feature splicing, and attention-guided fusion).

[0038] Based on the evaluation results, testers can adjust parameters such as image resolution scaling, feature extraction thresholds, and fusion weight coefficients, or switch to different algorithm modules and re-execute the registration and fusion process. For image pairs with large errors, advanced registration strategies (such as sparse feature registration combined with dense flow field correction) can be used to improve registration accuracy.

[0039] All optimization iterations record configuration parameters and evaluation data through the intelligent platform, and support comparison of multiple version fusion results to ultimately determine the optimal model configuration to meet factory consistency requirements.

[0040] 9. End of measurement: When all test steps are completed and the results meet the requirements, the measurement is terminated and the test data and report are saved. Through the above steps, the performance of the contact network thermal defect detection system in heterogeneous image fusion and registration can be fully verified, ensuring that it can accurately and reliably detect thermal defects in contact network components in practical applications.

[0041] Absolute high temperature alarm inspection process is as follows Figure 3 The detailed steps are as follows: 1) Launch the smart platform; 2) Use the intelligent platform to control the trolley to move in front of the overhead contact network device to ensure that the disconnector is within the image acquisition range; 3) Set the temperature of the heating plate to 80°C through the intelligent platform and check whether the intelligent platform generates a third-level absolute high temperature alarm file; set the temperature of the heating plate to 120°C and check whether a second-level absolute high temperature alarm file is generated; set the temperature of the heating plate to 160°C and check whether a first-level absolute high temperature alarm file is generated; 4) Set different thresholds for the heater temperature to simulate the high-temperature alarm of the isolation switch. If the alarm file is generated normally, the factory requirements are met; 5) End measurement.

[0042] 5. Using the present invention to test the temperature difference alarm detection of the contact network thermal defect detection system The detailed steps of the suspected insulator heating inspection process are as follows: 1) Launch the smart platform; 2) Use the intelligent platform controller to move the trolley to the front of the contact network device to ensure that the insulator is within the image acquisition range; 3) Set the heating plate to different temperatures through the intelligent platform; 4) The intelligent platform receives images collected by infrared thermal imagers and visible light; 5) Identify contact network components based on the image, obtain the maximum and average temperatures of the components, and if the component is an insulator, calculate whether the temperature difference reaches the alarm threshold; 6) If the component is not an insulator or metal, proceed to step 4 to calculate other components; 7) If the component is an insulator and the calculated temperature difference does not reach the alarm threshold, continue to step 4 to calculate other components; 8) The intelligent platform receives the alarm, displays the suspected hot insulator heating image and alarm details, and sets the heating plate temperature to 40°C, 32°C, and 28°C (the ambient temperature is 25°C) through the intelligent platform. The intelligent platform generates the first, second, and third level alarm files for the suspected insulator heating defect in turn.

[0043] 9) Set different threshold heater temperature to simulate suspected insulator heating defects. If the alarm file is generated normally, the factory requirements are met. 10) End the measurement.

[0044] The detailed steps of the suspected metal fever inspection process are as follows: 1) Launch the smart platform; 2) Use the intelligent platform controller to move the trolley to the front of the contact network device to ensure that the insulator is within the image acquisition range; 3) Set the heating plate to different temperatures through the intelligent platform; 4) The intelligent platform receives images collected by infrared thermal imagers and visible light; 5) Identify the contact network components based on the image and obtain the maximum and average temperatures of the components. If the components are metal, calculate whether the relative temperature difference reaches the alarm threshold; 6) If the component is not an insulator or metal, proceed to step 4 to calculate other components; 7) If the component is metal and the calculated relative temperature difference does not reach the alarm threshold, proceed to step 4 to calculate other components; 8) The intelligent platform receives the alarm and displays the suspected hot metal heating image and alarm details.

[0045] 9) Set different threshold heater temperature to simulate suspected metal heating defects. If the alarm file is generated normally, the factory requirements are met. 10) End the measurement.

Claims

1. A performance test platform for a contact network thermal defect detection device, comprising a track, characterized in that: Including thermal defect detection module, contact network simulation device, nine-square temperature measurement test module, and intelligent control platform; The thermal defect detection module, the contact network simulation device, and the nine-square test module are respectively connected to the intelligent control platform; The thermal defect detection module includes a mobile trolley and a thermal defect detection device, which is used to collect images of thermal defects in the contact network to be tested; The catenary simulation device is used to simulate thermal defects of catenary components; The nine-square temperature measurement test module includes a nine-square test module and a linear module, which is used to calibrate the thermal defect detection module; The intelligent control platform is used to control the temperature of the heating plate in the contact network simulation device to simulate different heating defects, and control the thermal defect detection module to perform thermal defect detection.

2. A performance test platform for a contact network thermal defect detection device according to claim 1, characterized in that: The nine-grid temperature measurement test module includes a nine-grid test module and a linear module, which is used to calibrate the thermal defect detection module, including: a blackbody radiation source driven by the linear module, verifying the temperature measurement consistency of the thermal defect detection module in the nine-grid test module.

3. A performance test platform for a contact network thermal defect detection device according to claim 2, characterized in that: The verification of the temperature measurement consistency of the thermal defect detection module includes: The linear module drives the blackbody radiation source to the center of each of the nine squares of the nine-square grid, and calculates the temperature difference between the temperature value Ct at each position and the temperature of the center square C5 |Ct-C5|. If all temperature differences are less than the temperature difference, the test is passed; otherwise, it fails. In the temperature measurement accuracy verification of the central area, the blackbody is controlled to be positioned at the center square C5 of the nine-square grid. The temperature of the blackbody radiation source is set to different temperature values ​​in sequence to verify whether the temperature measurement error between the temperature collected by the thermal defect detection module and the set temperature is less than the temperature difference. If all temperature differences are less than the temperature difference, it is judged to pass; otherwise, it is failed.

4. A performance test platform for a contact network thermal defect detection device according to claim 3, characterized in that: The catenary simulation device is used to simulate thermal defects of catenary components, and includes an insulator simulation module, a dropper wire clamp simulation module, and an isolating switch simulation module; The insulator simulation module, the dropper wire clamp simulation module and the disconnector simulation module are respectively connected to the intelligent control platform; The insulator simulation module includes a heating insulator module and a normal insulator module; the dropper string clamp simulation module includes a heating dropper string clamp module and a normal dropper string clamp module; the heating insulator module, normal insulator module, heating dropper string clamp module, and normal dropper string clamp module are respectively connected to the intelligent control platform; the intelligent control platform controls the heating insulator module, heating dropper string clamp module, and disconnector simulation module to perform heating simulation.

5. The performance test platform for a contact network thermal defect detection device according to claim 1, characterized in that: The controlling thermal defect detection module to perform thermal defect detection includes: The mobile cart is controlled by an intelligent platform to enable the thermal defect detection module to synchronously collect infrared and visible light images of the contact network simulation device; feature point matching and transformation registration are performed on the dual-mode images to generate a fused image; quantitative indicators of the fused image and the source image are calculated. If the quantitative indicators meet the standards, the fusion and registration function is judged to be qualified.

6. A performance test platform for a contact network thermal defect detection device according to claim 5, characterized in that: Also included are the absolute high temperature alarm verification steps: Control the temperature of the isolating switch module to rise to the set temperature in sequence, and verify whether the third-level, second-level, and first-level absolute high temperature alarm files are generated in sequence. If the corresponding high temperature alarm files are generated, the absolute high temperature alarm verification is qualified, otherwise, it is unqualified.

7. A performance test platform for a contact network thermal defect detection device according to claim 6, characterized in that: It also includes a temperature difference alarm verification step: a. Set stepped temperatures T1, T2, T3 for the heated insulator module, where T1 < T2 < T3, and calculate the temperature difference ΔT from the environment; b. If ΔT reaches the preset alarm threshold, verify that the device under test generates an insulator heating alarm at the corresponding level; c. Execute the same process for the heated suspension clamp module to verify the function of generating metal heating alarms.

8. A performance test method for a contact network thermal defect detection device, characterized in that: Applied to the performance test platform of a catenary thermal defect detection device according to any one of claims 1-7, it includes: S1, Start the performance test platform S2, Calibrate the thermal defect detection module S21, Verification of temperature measurement consistency: Drive the blackbody radiation source through the linear module to locate to the centers of the 9 squares of the nine-square grid in sequence, record the temperature measurement values Ct at each position, and calculate the temperature difference |Ct - C5| from the central square C5; if all temperature differences are less than the preset temperature difference value, it is judged as passed, otherwise it is not passed; S22, Verification of temperature measurement accuracy in the central area: Control the blackbody radiation source to locate to the central square C5 of the nine-square grid, set different temperature values in sequence, and verify the error between the temperature collected by the device under test and the set temperature; if all errors are less than the preset temperature difference value, it is judged as passed, otherwise it is not passed; S3, Image acquisition and fusion registration function test The intelligent control platform controls the movement of the mobile trolley to enable the device under test to synchronously acquire infrared images and visible light images of the catenary simulation device; perform feature point matching and transformation registration on the infrared images and visible light images to generate a fused image; calculate the quantization index of the fused image and the source image, and if the index meets the standard, it is judged that the fusion registration function is qualified; S4, Absolute high temperature alarm verification Control the temperature of the disconnector module in the catenary simulation device to rise to the set temperature in sequence, and verify whether the device under test generates three-level, two-level, and one-level absolute high temperature alarm files in sequence; if the corresponding alarm files are generated, it is judged as qualified, otherwise it is not qualified; S5 Temperature difference alarm verification S51, Set stepped temperatures T1, T2, T3 (T1 < T2 < T3) for the heated insulator module, and calculate the temperature difference ΔT from the environment; when ΔT reaches the preset alarm threshold, verify whether an insulator heating alarm at the corresponding level is generated; S52, Set stepped temperatures T1, T2, T3 (T1 < T2 < T3) for the heated suspension clamp module, and calculate the temperature difference ΔT from the environment; when ΔT reaches the preset alarm threshold, verify the function of generating metal heating alarms; if corresponding alarms can be generated in both cases, it is judged as qualified, otherwise it is not qualified.

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