Digital radiographic detection system for crimping quality of strain clamp of line in alpine region

Abstract

The invention discloses a digital radiographic detection system for the crimping quality of a line strain clamp in an alpine region, and belongs to the technical field of electric power detection. The digital radiographic detection system for the crimping quality of the line strain clamp in the alpine region comprises a main body, walking mechanisms are arranged on the two sides of the main body, and icebreaking mechanisms are arranged on the two sides of the walking mechanisms; the device further comprises a ray detection module, a temperature detection module, a control execution module and a defect detection module. The problem that existing monitoring work is affected by low temperature in the alpine region is solved, internal temperature data and environment temperature data are obtained by detecting the temperature in the main body and the temperature of the surrounding environment in real time, then the internal temperature data and the environment temperature data are compared with preset safety threshold values for analysis, and the safety threshold values are obtained. And the temperature in the main body is adjusted or ice breaking work is performed according to a comparative analysis result, so that the detection work is normally performed in a low-temperature environment.

Description

Technical Field

[0001] The invention relates to the technical field of electric power detection, and in particular to a digital ray detection system for crimping quality of line tension clamps in high-cold areas. Background Art

[0002] The connections of overhead power transmission line conductors and ground wires are mostly made of crimping-type power fittings - tension clamps and straight joint pipes. They must bear all the tension of the conductors and ground wires, and are also electrical conductors. They will not be disassembled after installation. During the construction process, if the conductors and ground wires are not fully penetrated in the crimping pipe or the steel core crimping does not meet the requirements, it will bury major hidden dangers for the safe operation of the line. Across the country, there have been many accidents of disconnection and drop caused by unqualified crimping quality of tension clamps or joint pipes. X-ray nondestructive testing, as a conventional nondestructive testing method, has been used in the industrial field for nearly a hundred years. This technology uses the strong penetration ability of X-rays. The rays that penetrate the object to be tested carry information reflecting the internal structure of the object to be tested. The nature, size and distribution of various macro or micro defects in the material or workpiece are detected and judged by the change of ray intensity.

[0003] However, the existing use of X-rays to detect the quality of tension clamps or connecting pipe crimping still has the following problems: traditional detection equipment is easily affected by the local low temperature environment when conducting detection in high-altitude and cold areas. Low temperature may cause the electronic components inside the equipment to work unstably, affecting the emission and reception of rays. In addition, in low temperature environments, transmission lines are prone to ice, affecting the operation of equipment on transmission lines, making it impossible to perform detection work. Therefore, it does not meet existing needs. In this regard, we have proposed a digital radiographic detection system for the crimping quality of tension clamps in high-altitude and cold areas. Summary of the invention

[0004] The purpose of the present invention is to provide a digital radiographic detection system for the crimping quality of line tension clamps in high-cold areas. The system detects the temperature inside the main body and the surrounding environment in real time to obtain internal temperature data and ambient temperature data, and then compares and analyzes the internal temperature data and ambient temperature data with pre-set safety thresholds. The temperature inside the main body is adjusted or ice breaking is performed based on the comparison and analysis results, thereby solving the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a digital radiographic detection system for crimping quality of line tension clamps in high-cold areas, comprising a main body, both sides of which are provided with a walking mechanism for driving the walking, and both sides of the walking mechanism are provided with an ice-breaking mechanism for cleaning the surface of the transmission line;

[0006] A hook frame is arranged above the main body, an imaging plate is arranged on the frame of the main body, and an X-ray emitting device is arranged below the frame of the main body;

[0007] The ice-breaking mechanism includes a cross bar and a heating sheet, and the heating sheet is arranged on the inner wall of the cross bar;

[0008] The system further includes:

[0009] A ray detection module, configured to emit X-rays to penetrate a strain clamp in a transmission line and receive a digital image formed after the X-ray penetration;

[0010] A temperature detection module, configured to obtain the internal temperature data and ambient temperature data of the main body in real time, compare and analyze them with a pre-set safety threshold, and if the comparison and analysis result exceeds the safety threshold, generate an independent heating control signal or an ice-breaking control signal;

[0011] A control execution module, configured to perform the heating work and ice-breaking work of the main body respectively based on the independent heating control signal and the ice-breaking control signal. At the same time, perform robust scaling normalization processing on the detection data of the strain clamp, and use the objective function algorithm to perform clustering processing on the pre-processed detection data, and evaluate the crimping quality based on the clustering result;

[0012] A defect detection module, configured to detect and identify whether there are defects in the digital image based on wavelet transform and support vector machine, and if so, send out a warning message.

[0013] Further, the ray detection module includes:

[0014] A ray projection module, configured to cooperate between an imaging plate and an X-ray emission device, emit X-rays to penetrate a strain clamp in a transmission line, receive a digital image formed after the X-ray penetration, and obtain a digital image of the transmission line;

[0015] A data transmission module, configured to, after obtaining the digital image, transmit the digital image to the cloud server in a wireless transmission manner in the first time;

[0016] An image analysis module, configured to perform real-time processing and analysis on the digital image in the cloud server, generate an analysis result, and send and display the analysis result on the working end, wherein the processing includes temperature correction, denoising and image enhancement.

[0017] Further, the ray projection module specifically performs the following steps:

[0018] The ground workstation sends a detection instruction to the X-ray emission device;

[0019] The X-ray emission device turns on the ray according to the detection instruction;

[0020] The X-ray emission device penetrates the strain clamp in the transmission line through the turned-on ray and in cooperation with the imaging plate, and obtains a digital image formed after the penetration.

[0021] Furthermore, the image processing module is specifically:

[0022] Temperature correction: used to perform temperature correction on the digital image to eliminate image errors caused by temperature changes, including adjusting the color balance and contrast of the digital image;

[0023] Denosing: used to perform denoising processing on the digital image using a filtering algorithm to remove snow noise or thermal noise in the digital image, where the filtering algorithm includes median filtering and adaptive Wiener filtering;

[0024] Image enhancement: used to perform enhancement processing on the digital image, including increasing the contrast of the digital image and sharpening the edges.

[0025] Furthermore, the temperature detection module includes:

[0026] The body detection module is configured to deploy a temperature sensor inside the main body, and detect the internal temperature of the main body in real time through the temperature sensor to obtain the internal temperature data of the main body;

[0027] The environment detection module is configured to deploy a temperature sensor on the main body, and detect the ambient temperature around the main body in real time through the temperature sensor to obtain the ambient temperature data of the environment around the main body;

[0028] The data analysis module is configured to preset the safety thresholds for the internal temperature of the main body and the ambient temperature, and compare and analyze the obtained internal temperature data and ambient temperature data with the preset safety thresholds respectively;

[0029] Once the internal temperature data exceeds the safety threshold, an independent heating control signal is immediately generated and sent to the independent heating module;

[0030] Once the ambient temperature data exceeds the safety threshold, an ice-breaking control signal is immediately generated and sent to the independent heating module.

[0031] Furthermore, the safety threshold is specifically:

[0032] The standard for the internal temperature of the main body is 5°C - 40°C;

[0033] The standard for the ambient temperature around the main body is -5°C to 0°C.

[0034] Furthermore, the control execution module includes:

[0035] The independent heating module is configured to install a heating device inside the main body, control the heating device to start according to the received independent heating control signal, and increase the internal temperature of the main body by controlling the heating device;

[0036] The ice-breaking execution module is configured to control the heating sheet to start according to the received control signal, and break the ice layer by controlling the heating sheet to heat the transmission line.

[0037] Further, an installation frame is connected to the upper end of the cross bar. The cross bar is fixedly connected to the side surface of the main body through the installation frame. The cross bar is semicircularly arranged, and the inner wall of the cross bar is fitted with the surface of the transmission line. A heating sheet and a brush are arranged on the inner wall of the cross bar. The heating sheet is used to melt the ice layer on the transmission line, and the brush is used to clean the surface of the transmission line.

[0038] Further, the control execution module includes:

[0039] The preprocessing sub-module is used to obtain the detection data of the strain clamp, and perform robust scaling normalization processing on the detection data;

[0040] The clustering sub-module is used to perform clustering processing on the preprocessed detection data. Specifically, first determine the number of clusters, and then define the cluster centers; based on the defined cluster centers, implement clustering using the objective function algorithm;

[0041] The quality evaluation sub-module is used to evaluate the crimping quality according to the clustering result of the objective function algorithm of the clustering sub-module. Specifically, preset the target value of the calculation result obtained by the objective function algorithm as the measurement standard. If the numerical result calculated by the objective function algorithm is greater than the target value, it means that the crimping quality of the strain clamp does not meet the requirements, and a warning message is issued; otherwise, if the numerical result calculated by the objective function algorithm is not greater than the target value, it means that the crimping quality of the strain clamp meets the requirements.

[0042] Further, the digital radiography detection system for the crimping quality of strain clamps in high-cold areas also includes a defect detection module. The defect detection module includes:

[0043] The wavelet transform decomposition sub-module is used to obtain the digital image obtained by the ray detection module, and decompose the digital image using the following wavelet transform formula:

[0044]

[0045] Among them, W(,1) is the digital image output after wavelet transform decomposition, x(t) is the input signal based on the digital image, is the wavelet function based on time t, a is the scale parameter, and 1 is the translation parameter;

[0046] The feature extraction sub-module is used to perform feature extraction on the digital image output after wavelet transform decomposition to obtain a feature vector;

[0047] The decision classification sub-module is used to classify the feature vector according to the support vector machine (SVM) using the following decision function:

[0048]

[0049] Among them, () is the decision function, sign() is the sign function, is the number of decomposed digital images, and α j is the Lagrange multiplier, and y j is the feature vector corresponding to the j-th digital image output after decomposition, K(x, x j ) is the kernel function, and b2 is the bias term;

[0050] The defect recognition sub-module is used to judge whether there is a defect according to the classification result of the feature vector by the decision function. If so, a warning message is sent.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] Through the temperature detection module, the present invention can detect the ambient temperature inside and around the main body in real time, so as to obtain the internal temperature data and the ambient temperature data. Then, the obtained internal temperature data and ambient temperature data are respectively compared and analyzed with the pre-set safety thresholds. Once the internal temperature data and the ambient temperature data exceed the safety thresholds, corresponding control signals are immediately generated to implement corresponding measures. If the comparison and analysis result of the internal temperature data exceeds the safety threshold, an independent heating control signal is generated and sent to the independent heating module, so that the temperature inside the main body can be increased by controlling the heating device, avoiding the problem that low temperature affects the detection work. By controlling the heating sheet to heat the transmission line and cooperating with the brush, the ice layer on the transmission line can be effectively broken, ensuring that the main body can walk smoothly on the transmission line. Description of the Drawings

[0053] Figure 1 is a schematic structural diagram of the digital ray detection system for the crimping quality of strain clamps on lines in alpine regions of the present invention;

[0054] Figure 2 is a schematic structural diagram of the ice-breaking mechanism of the present invention;

[0055] Figure 3 is a schematic module diagram of the digital ray detection system for the crimping quality of strain clamps on lines in alpine regions of the present invention;

[0056] Figure 4 is a schematic flow diagram of the temperature detection module of the present invention.

[0057] In the figure: 1. Main body; 11. Hook frame; 12. Imaging plate; 13. X-ray emission device; 2. Traveling mechanism; 3. Ice-breaking mechanism; 31. Mounting frame; 32. Cross bar; 33. Heating sheet; 34. Brush. Detailed Embodiments

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0059] In order to solve the problems that when existing detection equipment conducts detection in alpine regions, it is vulnerable to the local low-temperature environment. The low temperature may cause the electronic components inside the equipment to work unstably, affecting the emission and reception effects of rays, and in a low-temperature environment, the transmission line is prone to icing, affecting the movement of the equipment on the transmission line, and thus the detection work cannot be carried out. Please refer to Figures 1 - 4 , the following technical solutions are provided in this embodiment:

[0060] A digital ray detection system for the compression quality of strain clamps on transmission lines in alpine regions includes a main body 1. Walking mechanisms 2 are arranged on both sides of the main body 1. The walking mechanisms 2 are used to drive the main body 1 to move on the transmission line. Ice-breaking mechanisms 3 are arranged on both sides of the walking mechanisms 3. The ice-breaking mechanisms 3 are used for cleaning the surface of the transmission line;

[0061] A hanging hook frame 11 is arranged above the main body 1. An imaging plate 12 is arranged on the frame of the main body 1. An X-ray emission device 13 is arranged below the frame of the main body 1;

[0062] The ice-breaking mechanism 3 includes a cross bar 32 and a heating sheet 33. The heating sheet 33 is arranged on the inner wall of the cross bar 32;

[0063] The system further includes:

[0064] A ray detection module configured to, based on X-ray fluoroscopy imaging technology, emit X-rays to penetrate the strain clamps in the transmission line and receive the digital images formed after the X-ray penetration;

[0065] A temperature detection module configured to detect the ambient temperature inside and around the main body 1 in real time, obtain the internal temperature data and the ambient temperature data, and respectively compare and analyze the obtained internal temperature data and ambient temperature data with the pre-set safety thresholds;

[0066] If the comparison and analysis result of the internal temperature data exceeds the safety threshold, an independent heating control signal is generated and sent to the independent heating module;

[0067] If the comparison and analysis result of the ambient temperature data exceeds the safety threshold, an ice-breaking control signal is generated and sent to the ice-breaking execution module;

[0068] The control execution module is configured to receive the independent heating control signal and the ice-breaking control signal sent by the temperature detection module, and respectively execute the heating work and ice-breaking work of the main body 1 through the independent heating control signal and the ice-breaking control signal. At the same time, the detection data of the strain clamp is subjected to robust scaling normalization processing, and the target function algorithm is used to cluster the preprocessed detection data, and the crimping quality is evaluated based on the clustering result;

[0069] The defect detection module is configured to detect and identify whether there are defects in the digital image based on wavelet transform and support vector machine, and send a warning message if so.

[0070] The technical effects of the above content are as follows: The main body 1 is mainly responsible for the detection work. An imaging plate 12 and an X-ray emission device 13 are equipped on the main body 1, which can be used for X-ray fluoroscopy imaging of the strain clamp. The hook frame 11 arranged above can be mounted on the unmanned aerial vehicle, so that the main body 1 can be placed on the transmission line to be detected through the unmanned aerial vehicle. The traveling mechanism 2 is installed on both sides of the main body 1 and can be used to drive the main body 1 to travel on the transmission line to realize detection at different positions. The ice-breaking mechanism 3 is located on both sides of the traveling mechanism 2. The ice-breaking mechanism 3 can generate heat through the heating sheet 33 to melt the ice layer on the surface of the transmission line, not only ensuring the accuracy of the detection, but also ensuring that the traveling mechanism 2 is not affected by the ice layer during the traveling process. The ray detection module uses X-ray fluoroscopy imaging technology to irradiate the strain clamp in the transmission line, and the digital image formed after the irradiation can be used for subsequent quality analysis. The temperature detection module real-time detects the ambient temperature inside and around the main body 1 and conducts a comparative analysis to understand the current temperature situation, so that the control execution module can determine whether to execute the heating work and ice-breaking work according to the current temperature situation.

[0071] In summary, when the main body 1 travels on the transmission line, the ray detection module starts to work, emits X-rays to irradiate the strain clamp, and receives the formed digital image. At the same time, the temperature detection module real-time detects the internal and ambient temperature data. If the internal temperature data exceeds the safety threshold, the control execution module executes the heating work and ice-breaking work according to the received signal, avoiding the influence of the low-temperature environment on the detection work and ensuring the accuracy of the detection.

[0072] The upper end of the cross bar 32 is connected with a mounting frame 31. The cross bar 32 is fixedly connected to the side surface of the main body 1 through the mounting frame 31. The cross bar 32 is semicircularly arranged, and the inner wall of the cross bar 32 is fitted to the surface of the transmission line. A heating sheet 33 and a brush 34 are arranged on the inner wall of the cross bar 32. The heating sheet 33 is used to melt the ice layer on the transmission line, and the brush 34 is used to clean the surface of the transmission line.

[0073] The technical effects of the above content are as follows: The upper end of the crossbar 32 is connected to the mounting bracket 31. Through the mounting bracket 31, the crossbar 32 is fixedly connected to the side of the main body 1, ensuring the stability and reliability of the crossbar 32 during the detection process. The crossbar 32 is designed in a semi-circular shape, and its inner wall is in close contact with the surface of the transmission line, not only increasing the contact area between the crossbar 32 and the transmission line, improving the ice melting and cleaning effects, but also ensuring the stability of the crossbar 32 on the transmission line. The heating element 33 is arranged on the inner wall of the crossbar 32 and is used to melt the ice layer on the transmission line. In alpine regions, the surface of the transmission line is prone to icing. The heating element 33 effectively melts the ice layer by generating heat, providing convenience for the subsequent cleaning work. The brush 34 is also arranged on the inner wall of the crossbar 32. The brush 34 is used to clean the surface of the transmission line, removing the impurities and dirt remaining after ice melting, ensuring the cleanliness of the transmission line and the normal movement of the traveling mechanism 2.

[0074] The ray detection module includes:

[0075] The ray projection module is configured to cooperate between the imaging plate 12 and the X-ray emitting device 13, emit X-rays to irradiate the strain clamp in the transmission line, and receive the digital image formed after the X-ray irradiation to obtain the digital image of the transmission line. Specifically, the following steps are executed:

[0076] The ground workstation sends a detection instruction to the X-ray emitting device 13;

[0077] The X-ray emitting device 13 turns on the ray according to the detection instruction;

[0078] The X-ray emitting device 13 irradiates the strain clamp in the transmission line through the turned-on ray in cooperation with the imaging plate 12, and obtains the digital image formed after the irradiation;

[0079] The data transmission module is configured to, after obtaining the digital image, transmit the digital image to the cloud server in a wireless transmission manner in the first time;

[0080] The image analysis module is configured to perform real-time processing and analysis on the digital image in the cloud server, generate an analysis result, and send and display the analysis result on the working end. Among them, the processing includes temperature correction, denoising, and image enhancement.

[0081] The technical effects of the above content are as follows: The ray projection module uses the cooperation between the imaging plate 12 and the X-ray emission device 13 to emit X-rays to penetrate the strain clamp in the transmission line. X-rays can penetrate objects and form digital images. After the data transmission module obtains the digital images, it immediately transmits the digital images to the cloud server in a timely manner for subsequent processing and analysis. Transmitting the digital images immediately can transfer them to other environments, avoiding the degradation of digital image quality caused by long-term exposure to low temperatures. The transmission method adopts wireless transmission methods such as Wi-Fi, 4G / 5G networks, etc., ensuring that the image data can be transmitted to the cloud quickly and reliably. The image analysis module performs real-time processing and analysis on the received digital images in the cloud server, generates analysis results on the crimping quality of the strain clamp, and sends the analysis results to the working end (such as the mobile device or computer of the inspector), and displays them in an intuitive way, facilitating the inspector to timely understand and evaluate the crimping quality of the strain clamp.

[0082] In summary, the ray detection module realizes the accurate detection and analysis of the crimping quality of the strain clamp in the transmission line in alpine regions by integrating functions such as ray projection, data transmission, and image analysis. It not only has efficient and real-time detection capabilities but also can perform remote processing and analysis through the cloud server, greatly improving the efficiency and accuracy of the detection work.

[0083] The image processing module is specifically as follows:

[0084] Temperature correction: used to perform temperature correction on the digital image to eliminate image errors caused by temperature changes, including adjusting the color balance and contrast of the digital image;

[0085] Noise reduction: used to perform noise reduction processing on the digital image using a filtering algorithm to remove snow noise or thermal noise in the digital image. Among them, the filtering algorithm includes median filtering and adaptive Wiener filtering;

[0086] Image enhancement: used to perform enhancement processing on the digital image, including increasing the contrast and sharpening the edges of the digital image.

[0087] The technical effects of the above content are as follows: Since the temperature in alpine regions is extremely low, it may affect the performance of image acquisition devices (such as detectors), resulting in image distortion or noise. Therefore, during the processing stage, temperature correction should be performed on digital images to eliminate image errors caused by temperature changes. This usually involves adjusting parameters such as color balance and contrast of the image to restore the true color and details of the digital image. Secondly, in a low-temperature environment, additional noise may be introduced during the image acquisition process, such as snow noise or thermal noise. These noises will reduce the quality of the digital image and affect subsequent analysis and evaluation. Therefore, a filtering algorithm should be used to denoise the digital image to improve the clarity and readability of the digital image. In order to more clearly display the internal structure of the strain clamp, enhancement processing needs to be performed on the digital image, including increasing the contrast of the image, sharpening the edges, etc., in order to better identify and analyze defects and abnormalities in the digital image.

[0088] The temperature detection module includes:

[0089] The body detection module is configured to deploy a temperature sensor inside the main body 1, and detect the internal temperature of the main body 1 in real time through the temperature sensor to obtain the internal temperature data of the main body 1;

[0090] The environment detection module is configured to deploy a temperature sensor on the main body 1, and detect the ambient temperature around the main body 1 in real time through the temperature sensor to obtain the ambient temperature data of the environment around the main body 1;

[0091] The data analysis module is configured to pre-set the safety thresholds for the internal temperature of the main body 1 and the ambient temperature, and compare and analyze the obtained internal temperature data and ambient temperature data with the pre-set safety thresholds respectively. Among them, the safety thresholds are specifically:

[0092] The standard for the internal temperature of the main body 1 is 5°C - 40°C;

[0093] The standard for the ambient temperature around the main body 1 is -5°C to 0°C;

[0094] Once the internal temperature data exceeds the safety threshold, an independent heating control signal will be generated immediately and sent to the independent heating module;

[0095] Once the ambient temperature data exceeds the safety threshold, an ice-breaking control signal will be generated immediately and sent to the independent heating module.

[0096] The technical effects of the above are as follows: The body detection module uses a temperature sensor to detect the internal temperature of the main body 1 in real time and obtains the corresponding internal temperature data. The environmental detection module uses a temperature sensor to detect the ambient temperature around the main body 1 in real time and obtains the corresponding ambient temperature data. The data analysis module compares and analyzes the obtained internal temperature data and ambient temperature data with the pre-set safety thresholds respectively. Once the internal temperature data exceeds the safety threshold range of 5°C - 40°C, an independent heating control signal is immediately generated and sent to the independent heating module. Once the ambient temperature data exceeds the safety threshold range of -5°C to 0°C, an ice-breaking control signal is immediately generated and sent to the independent heating module, thereby taking corresponding measures to cope with the low-temperature environment.

[0097] In summary, the design of the temperature detection module can ensure that when the main body 1 is working in alpine regions, the temperatures of its interior and the surrounding environment are within a safe and appropriate range, thus guaranteeing the smooth progress of the detection work and the accuracy of the detection results.

[0098] The control execution module includes:

[0099] The independent heating module is configured to install a heating device inside the main body 1 and control the start of the heating device according to the received independent heating control signal, and increase the temperature inside the main body 1 by controlling the heating device;

[0100] The ice-breaking execution module is configured to control the start of the heating element 33 according to the received control signal, and heat the transmission line to break the ice layer by controlling the heating element 33.

[0101] The technical effects of the above are as follows: When the data analysis module detects that the internal temperature of the main body 1 is lower than the safety threshold, it will generate an independent heating control signal. After receiving the independent heating control signal, the independent heating module will control the start of the heating device. The heating device generates heat to increase the temperature inside the main body 1, ensuring that its working environment is within an appropriate range and preventing the low-temperature environment from affecting the internal electronic components. When the data analysis module detects that the ambient temperature around the main body 1 is lower than the safety threshold, it indicates that the transmission line may be frozen. At this time, an ice-breaking control signal is generated. After receiving the ice-breaking control signal, the ice-breaking execution module will control the start of the heating element 33. The heating element 33 generates heat to directly heat the surface of the transmission line, thereby melting and breaking the ice layer, preventing the ice layer from affecting the movement of the traveling mechanism 2 and the normal operation of the transmission line.

[0102] In summary, through the independent heating module and the ice-breaking execution module, the control execution module effectively controls the temperature inside the main body 1 and the ice layer on the surface of the transmission line. When abnormal temperature is detected, it can respond quickly and ensure the normal operation of the main body 1 and the unobstructed transmission line by controlling the operation of the heating device or the heating sheet 33. This design not only improves the efficiency and accuracy of the detection work, but also enhances the adaptability and reliability of the system in alpine regions.

[0103] Working principle: When the main body 1 moves on the transmission line, the ray detection module starts to work, emits X-rays to penetrate the strain clamp, and receives the formed digital image. At the same time, the temperature detection module real-time detects the internal and environmental temperature data. If the internal temperature data exceeds the safety threshold, the control execution module performs heating work and ice-breaking work according to the received signal, effectively controlling the temperature inside the main body 1 and the ice layer on the transmission line, and enhancing the adaptability and reliability of the system in alpine regions.

[0104] Based on the foregoing embodiments, the control execution module includes:

[0105] A preprocessing sub-module, which is used to obtain the detection data of the strain clamp and perform RobustScaler normalization processing on the detection data;

[0106] A clustering sub-module, which is used to perform clustering processing on the preprocessed detection data. Specifically, first determine the number of clusters, and then define the cluster centers. The definition formula of the i-th cluster center is as follows:

[0107]

[0108] Based on the defined cluster centers, perform clustering using the objective function algorithm, where the objective function algorithm is as follows:

[0109]

[0110] where k is the number of clusters, C i is the i-th cluster, μ i is the i-th cluster center, and x is the data point of the detection data;

[0111] A quality evaluation sub-module, which is used to evaluate the crimping quality according to the clustering result of the objective function algorithm of the clustering sub-module. Specifically, preset the target value of the calculation result obtained by the objective function algorithm as the measurement standard. If the numerical result calculated by the objective function algorithm is greater than the target value, it means that the crimping quality of the strain clamp does not meet the requirements, and a warning message is issued; otherwise, if the numerical result calculated by the objective function algorithm is not greater than the target value, it means that the crimping quality of the strain clamp meets the requirements.

[0112] In summary, for the detection of strain clamps, robust scaling normalization is performed on the inspection data. Robust scaling normalization is better suited for processing data with noise or outliers, which helps to exclude noise interference. By normalizing, data with different dimensions and value ranges are converted to the same scale, laying the foundation for subsequent clustering analysis. After normalization, the above objective function algorithm is used to perform clustering analysis. Through clustering analysis, the system can classify the detection data of strain clamps into different quality grades, facilitating quality control. Among them, the larger the numerical result of the objective function algorithm, the greater the fluctuation of the crimping quality and the worse the quality stability. On the contrary, the smaller the numerical result of the objective function algorithm, the smaller the fluctuation of the crimping quality and the better the quality stability. Therefore, a target value of the calculation result of the objective function algorithm can be set as a measurement standard. If the calculation result of the objective function algorithm exceeds the target value, a warning message is sent to remind the staff to take corresponding measures for adjustment. In addition, the clustering algorithm has no strict assumptions about the data distribution and can adapt to different detection data. Therefore, the data adaptability of this solution is strong. Moreover, the clustering algorithm is simple and easy to implement, with high computational efficiency and is suitable for processing large-scale data.

[0113] Based on the foregoing embodiments, the digital radiographic inspection system for the crimping quality of strain clamps in high-cold regions further includes a defect detection module, and the defect detection module includes:

[0114] A wavelet transform decomposition sub-module, configured to obtain the digital image obtained by the radiographic detection module, and decompose the digital image by using the following wavelet transform formula:

[0115]

[0116] wherein, W(a, b1) is the digital image output after wavelet transform decomposition, x(t) is the input signal based on the digital image, is the wavelet function based on time t, a is the scale parameter, and 1 is the translation parameter;

[0117] A feature extraction sub-module, configured to perform feature extraction on the digital image output after wavelet transform decomposition to obtain a feature vector;

[0118] A decision classification sub-module, configured to classify the feature vector according to the support vector machine (SVM) by using the following decision function:

[0119]

[0120] wherein, () is the decision function, sign() is the sign function, is the number of decomposed digital images, α j is the Lagrange multiplier, y jis the feature vector corresponding to the j-th digital image output after decomposition, K(x, x j ) is the kernel function, and 2 is the bias term;

[0121] The defect recognition sub-module is used to judge whether there is a defect according to the classification result of the feature vector by the decision function. If so, a warning message is sent.

[0122] In summary, this solution uses wavelet transform to perform multi-resolution analysis on the X-ray images of strain clamps, and processes them through the above algorithm to detect potential defects of strain clamps; among them, the sign function operation is used in the decision function to obtain the vector label of the feature vector (the vector labels obtained after the operation of the feature vectors corresponding to the defective strain clamps and the non-defective strain clamps are different). The vector label reflects whether there is a defect in the strain clamp, and classification is carried out based on this to separate the defective strain clamps from the non-defective strain clamps. If there is a defective strain clamp in the classification, a warning message is sent; combining wavelet transform and support vector machine, the system can accurately identify the defects of strain clamps; wavelet transform can provide multi-resolution image analysis and effectively detect defects of different scales; wavelet transform has good robustness to noise and can stably detect defects under complex backgrounds.

[0123] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0124] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

Claims

1. Digital ray detection system for compression quality of strain clamps on lines in alpine regions, comprising a main body (1), characterized in that, Walking mechanisms (2) are provided on both sides of the main body (1), and ice-breaking mechanisms (3) are provided on both sides of the walking mechanisms (2); the system further includes: A ray detection module configured to emit X-rays to penetrate the strain clamp in the transmission line and obtain a digital image. A temperature detection module configured to obtain the internal temperature data and ambient temperature data of the main body (1), and compare and analyze them with a pre-set safety threshold. If the comparison and analysis result exceeds the safety threshold, an independent heating control signal or an ice-breaking control signal is generated. A control execution module configured to perform the heating work and ice-breaking work of the main body (1) respectively based on the independent heating control signal and the ice-breaking control signal. At the same time, the detection data of the strain clamp is subjected to robust scaling normalization processing, and the target function algorithm is used to cluster the pre-processed detection data, and the crimping quality is evaluated based on the clustering result. A defect detection module configured to detect and identify whether there are defects in the digital image based on wavelet transform and support vector machine, and issue a warning message if so.

2. The digital ray detection system for the compression quality of strain clamps on overhead lines in alpine regions according to claim 1, wherein: The ray detection module includes: A ray projection module configured to emit X-rays from the main body (1) to penetrate the strain clamp in the transmission line, receive the digital image formed after the X-ray penetration, and obtain the digital image of the transmission line. A data transmission module configured to, after obtaining the digital image, transmit the digital image to the cloud server in real time by means of wireless transmission. An image analysis module configured to perform real-time processing and analysis on the digital image in the cloud server, generate an analysis result, and send and display the analysis result on the working end, where the processing includes temperature correction, denoising, and image enhancement.

3. The digital radiographic inspection system for the compression quality of strain clamps on overhead lines in alpine regions according to claim 2, wherein: The ray projection module specifically performs the following steps: Receive the detection instruction sent by the ground workstation and send it to the main body (1). The main body (1) turns on the ray according to the sent detection instruction. The main body (1) penetrates the strain clamp in the transmission line through the turned-on ray and obtains the digital image formed after the penetration.

4. The digital radiographic inspection system for the compression quality of strain clamps of overhead lines in alpine regions according to claim 2, wherein: The image processing module is specifically: Temperature correction: used to perform temperature correction on the digital image to eliminate the image error caused by temperature change, including adjusting the color balance and contrast of the digital image. Denoising: used to perform denoising processing on the digital image using a filtering algorithm to remove snow noise or thermal noise in the digital image, where the filtering algorithm includes median filtering and adaptive Wiener filtering. Image enhancement: used to perform enhancement processing on the digital image, including increasing the contrast of the digital image and sharpening the edges.

5. The digital radiographic inspection system for the compression quality of strain clamps of overhead lines in alpine regions according to claim 1, characterized in that: The temperature detection module includes: A body detection module configured to deploy temperature sensors inside the main body (1), and detect the internal temperature of the main body (1) in real time through the temperature sensors to obtain the internal temperature data of the main body (1). An environment detection module configured to deploy temperature sensors on the main body (1), and detect the ambient temperature around the main body (1) in real time through the temperature sensors to obtain the ambient temperature data of the environment around the main body (1). The data analysis module is configured to preset the safety thresholds for the internal temperature of the main body (1) and the ambient temperature, and compare and analyze the acquired internal temperature data and ambient temperature data with the preset safety thresholds respectively; Once the internal temperature data exceeds the safety threshold, an independent heating control signal is immediately generated and sent to the independent heating module; Once the ambient temperature data exceeds the safety threshold, an ice-breaking control signal is immediately generated and sent to the independent heating module.

6. The digital radiographic inspection system for the compression quality of strain clamps on lines in alpine regions according to claim 5, characterized in that: The safety thresholds are specifically: The standard for the internal temperature of the main body (1) is 5°C - 40°C; The standard for the ambient temperature around the main body (1) is -5°C to 0°C.

7. The digital ray detection system for the compression quality of strain clamps on lines in alpine regions according to claim 1, wherein: The control execution module includes: The independent heating module is configured to install a heating device inside the main body (1), and control the start of the heating device according to the received independent heating control signal, and increase the internal temperature of the main body (1) by controlling the heating device; The ice-breaking execution module is configured to control the start of the ice-breaking mechanism (3) according to the received control signal, and break the ice layer by heating the transmission line through controlling the ice-breaking mechanism (3).

8. The digital radiographic inspection system for the crimping quality of strain clamps on overhead lines in alpine regions according to claim 1, wherein: The ice-breaking mechanism (3) includes a cross bar (32) and a heating sheet (33). The upper end of the cross bar (32) is connected with a mounting bracket (31). The cross bar (32) is fixedly connected to the side surface of the main body (1) through the mounting bracket (31). The cross bar (32) is semicircularly arranged. The inner wall of the cross bar (32) is attached to the surface of the transmission line. A heating sheet (33) and a brush (34) are arranged on the inner wall of the cross bar (32). The heating sheet (33) is used to melt the ice layer on the transmission line, and the brush (34) is used to clean the surface of the transmission line.

9. The digital radiographic inspection system for the compression quality of strain clamps on transmission lines in alpine regions according to claim 1, wherein: The control execution module includes: The preprocessing sub-module is used to obtain the detection data of the strain clamp and perform robust scaling normalization processing on the detection data; The clustering sub-module is used to perform clustering processing on the preprocessed detection data. Specifically, first determine the number of clusters, and then define the cluster centers; based on the defined cluster centers, implement clustering using the objective function algorithm; The quality assessment sub-module is used to evaluate the crimping quality according to the clustering result of the objective function algorithm of the clustering sub-module. Specifically, preset the target value of the calculation result obtained by the objective function algorithm as the measurement standard. If the numerical result calculated by the objective function algorithm is greater than the target value, it means that the crimping quality of the strain clamp does not meet the requirements, and a warning message is issued; otherwise, if the numerical result calculated by the objective function algorithm is not greater than the target value, it means that the crimping quality of the strain clamp meets the requirements.

10. The digital radiographic inspection system for the compression quality of strain clamps on lines in alpine regions according to claim 1, characterized in that: It further includes a defect detection module, and the defect detection module includes: The wavelet transform decomposition sub-module is used to obtain the digital image obtained by the ray detection module and decompose the digital image using the following wavelet transform formula: Among them, W(a, b1) is the digital image output after wavelet transform decomposition, x(t) is the input signal based on the digital image, is the wavelet function based on time t, a is the scale parameter, and b1 is the translation parameter; The feature extraction sub-module is used to perform feature extraction on the digital image output after wavelet transform decomposition to obtain a feature vector; The decision classification sub-module is used to classify the feature vector according to the support vector machine (SVM) using the following decision function: Among them, f(x) is the decision function, sign() is the sign function, n is the number of decomposed digital images, α j is the Lagrange multiplier, y j is the feature vector corresponding to the j-th digital image output after decomposition, K(x, x j ) is the kernel function, and b2 is the bias term; The defect identification sub-module is used to judge whether there is a defect according to the classification result of the feature vector by the decision function. If so, a warning message is issued.

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