Electric power pipe crack infrared detection device

Abstract

The invention relates to a nondestructive testing technology of electrical equipment, and discloses an infrared detection device for cracks of an electrical tube, which comprises a support plate, a closed detection camera obscura, a rotary moving mechanism, an infrared imaging unit and an active infrared lighting unit, and is also provided with an infrared light source intensity real-time adjusting system, the system integrates an environment state evaluation module, a system state evaluation module, an adaptation evaluation module and a motion state evaluation module, and can sense multi-dimensional parameters such as environment light intensity, air suspended matter concentration, light source working temperature, optical window transmissivity, production line operation speed and pipeline rotation angular velocity in real time; and the infrared illumination intensity is dynamically adjusted by integrating the average gray scale of the image and the target feature contrast ratio. According to the invention, intelligent self-adaptive control of the infrared light source in a complex and changeable production environment is realized, the image quality stability and the accuracy and reliability of crack detection are effectively improved, and the method is suitable for full-automatic online nondestructive detection in large-scale production of power tubes.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of nondestructive testing of electric power equipment, and particularly relates to an electric power pipe crack infrared detection device. BACKGROUND

[0002] In the process of large-scale production of electric power pipes, real-time online detection of cracks is a core link to guarantee the quality of products leaving the factory. The current mainstream detection methods face multiple bottlenecks, which seriously restrict the production efficiency and quality consistency. The traditional manual visual sampling inspection method has the problems of low efficiency and high labor intensity, and the detection results are highly dependent on the experience and immediate state of personnel, which cannot realize full detection coverage, resulting in a significant increase in the risk of missing potential quality problems. Although the automatic visible light vision detection system introduced by some production lines has improved the speed, its performance is strongly dependent on the environmental light conditions. The light environment in the factory workshop is complex and variable, and the surface of the electric power pipe (especially the black polyethylene material) is prone to local reflection or shadow interference due to its inherent glossiness and arc structure characteristics, causing unstable image quality and frequent false positives and false negatives. Such systems still require a large amount of manual re-determination intervention and cannot truly realize the automatic closed loop of the detection process.

[0003] In recent years, detection equipment using fixed infrared light sources has been gradually applied to production lines to avoid visible light interference. However, the electric power pipe production environment is essentially a dynamic system: there are inherent differences in material composition and surface color among different batches of pipes; the production line speed needs to be frequently adjusted according to order requirements; the performance of the detection equipment deteriorates due to heat accumulation during continuous operation; and the dust concentration and water vapor content in the workshop environment also fluctuate with the season and working conditions. These dynamic factors make it impossible for fixed infrared lighting parameters to adapt to the actual detection requirements, resulting in significant fluctuations in image quality (including brightness distribution and feature contrast) for different product batches or production periods. To ensure basic detectability under the worst conditions, existing equipment generally uses excessively high constant lighting intensity, which not only wastes electricity and accelerates the aging process of infrared light sources, but also loses crack detail features due to overexposure when detecting high reflectivity pipes, thereby reducing detection reliability. The production end urgently needs to break through the limitations of the existing "parameter fixation" or "manual intervention" mode and develop an adaptive infrared detection scheme that can intelligently perceive environmental disturbances, system state changes, and motion dynamics to realize stable, accurate, and efficient full-automatic quality control and meet the strict requirements of modern intelligent manufacturing for product quality assurance. SUMMARY

[0004] The purpose of the embodiment of the application is to provide an electric power pipe crack infrared detection device to solve the above problems.

[0005] The application is achieved, a power pipe crack infrared detection device, including support plate, and the closed detection dark box and rotary movement mechanism installed on the top of the support plate, the rotary movement mechanism is used to drive the power pipe to rotate and move linearly, the infrared imaging unit is installed on the top in the closed detection dark box, the active infrared illumination unit is installed on the inner wall of the closed detection dark box, further comprising: infrared light source intensity real-time adjustment system, which is electrically connected with the control end of the active infrared illumination unit, the infrared light source intensity real-time adjustment system comprises: environment state evaluation module, which outputs environment compensation coefficient based on ambient light intensity and air suspended matter concentration; system state evaluation module, which outputs system attenuation compensation coefficient based on light source working temperature and optical window transmittance; adaptive evaluation module, which outputs average gray-scale-contrast adaptation degree based on environment compensation coefficient, system attenuation compensation coefficient, image average gray-scale value and target feature contrast; motion state evaluation module, which outputs motion compensation coefficient based on line running speed and pipe rotation angular velocity; infrared light source intensity control module, which outputs target infrared light source intensity based on motion compensation coefficient and average gray-scale-contrast adaptation degree and adjusts the active infrared illumination unit to the intensity.

[0006] Further technical solutions, the infrared light source intensity control module determines the target infrared light source intensity by the following way: first, determine the basic target intensity in the preset intensity range based on the motion compensation coefficient; then, adjust the basic target intensity according to the relationship between the average gray-scale-contrast adaptation degree and the preset threshold: when the adaptation degree is lower than the lower threshold, enhance the intensity in a way negatively correlated with the adaptation degree; when the adaptation degree is higher than the upper threshold, adjust the intensity in a way positively correlated with the adaptation degree, and finally limit the result in the preset intensity range.

[0007] Further technical solutions, the motion state evaluation module running process is: the line running speed and the pipe rotation angular velocity are respectively processed by ratio with the maximum line speed and the maximum rotation angular velocity, and after limiting the ratio upper limit to 1 by using the min function, the line running speed index and the pipe rotation angular velocity index are obtained; the motion compensation coefficient is increased when any speed index is increased by performing fusion calculation based on the complements of the line running speed index and the pipe rotation angular velocity index.

[0008] Further technical solutions, the adaptive evaluation module calculates the average gray-scale-contrast adaptation degree by the following way: the deviation degree of the image average gray-scale value relative to the ideal gray-scale is calculated to obtain the gray-scale adaptation degree; the target feature contrast is processed by ratio with the minimum allowed contrast, and after limiting the ratio upper limit to 1 by using the min function, the contrast adaptation degree is obtained The gray scale adaptability and the contrast adaptability are averaged, and the larger one of the ambient compensation coefficient and the system attenuation compensation coefficient is used for attenuation adjustment to output a final average gray scale-contrast adaptability.

[0009] Further technical solutions, the system state evaluation module running process is: the maximum-minimum normalization processing is carried out to the current light source working temperature, and the light source working temperature index is obtained; the ratio processing is carried out to the current window transmittance and the initial transmittance, and the complement (i.e. one minus the ratio) of the ratio is taken as the optical window transmittance attenuation index; the larger one of the light source working temperature index and the optical window transmittance attenuation index is taken as the system attenuation compensation coefficient; the larger the value is, the more serious the system performance attenuation is.

[0010] Further technical solutions, the environment state evaluation module running process is: the ratio processing is carried out to the current ambient light intensity and the air suspended matter concentration and the ambient light intensity threshold and the air suspended matter concentration respectively, the ambient light intensity index and the air suspended matter concentration index are obtained after the ratio upper limit is limited to 1 by using the min function; the square root operation fusion calculation is carried out on the ambient light intensity index and the air suspended matter concentration index, so as to highlight the contribution of the larger interference factor to the overall environmental interference degree.

[0011] Further technical solutions, the rotating moving mechanism comprises two guide plates fixed on the top of the support plate, a moving block and a moving assembly arranged on the top of the support plate, the moving assembly is used for driving the moving block to move linearly, one side of the moving block is rotationally connected with a rotating column, an inner wall clamping assembly is arranged on the rotating column, the inner wall clamping assembly is used for connecting the rotating column with the inner wall of the power pipe, and a rotating assembly for driving the rotating column to rotate is arranged on the moving block.

[0012] Further technical solutions, the moving assembly comprises two guide shafts fixed on the top of the support plate, the two guide shafts are arranged in parallel, the moving block is slidably connected on the two guide shafts, a screw rod is rotationally connected with the top of the support plate, the screw rod penetrates through the moving block and is threadedly connected with the moving block, a motor one is fixed on the top of the support plate, and the rotating end of the motor one is connected with the screw rod.

[0013] Further technical solutions, the inner wall clamping assembly comprises three mounting grooves uniformly arranged on the rotating column, a clamping rod is movably arranged in each of the three mounting grooves, a guide shaft is fixed in each of the three mounting grooves, a guide groove is arranged on the clamping rod, the guide shaft is slidably connected in the guide groove, a telescopic shaft is slidably connected at the axis of the rotating column, one end of the telescopic shaft is hinged with the clamping rod, a hollow rotary hydraulic oil cylinder is fixed on the side of the moving block away from the rotating column, and the telescopic end of the hollow rotary hydraulic oil cylinder is connected with the telescopic shaft.

[0014] Further technical solutions, the rotating assembly includes the motor two fixed on the moving block away from one side of the rotating column, the rotating end of the motor two is fixed with synchronous pulley on the rotating column, and the two synchronous pulleys are driven and connected through the synchronous belt.

[0015] Compared with the prior art, the beneficial effects of the present application are:

[0016] 1. By introducing the infrared light source intensity real-time adjustment system, the intelligent closed-loop control of the illumination intensity is realized, the image quality consistency is significantly improved, the problems of image overexposure, underexposure or insufficient contrast caused by environmental changes, system aging or motion state fluctuation are avoided, and the accuracy and reliability of crack detection are improved.

[0017] 2. The system has multi-parameter fusion evaluation capability, can adaptively respond to various interference factors such as environmental light, dust, temperature, window pollution and production line speed, realizes accurate compensation, and enhances the robustness and applicability of the device in complex industrial environments.

[0018] 3. The dynamic intensity adjustment mechanism is adopted, which avoids long-term high-power operation under the premise of ensuring image quality, helps to reduce energy consumption, prolong the service life of infrared light source and optical components, and meets the intelligent manufacturing requirements of energy saving and consumption reduction.

[0019] 4. The rotating movement mechanism can realize omnibearing scanning of the power tube, combined with adaptive illumination and high-quality imaging, support full-automatic detection, reduce manual intervention, and improve detection efficiency and overall automation level of the production line. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 A structure diagram of a power tube crack infrared detection device provided by the present application is provided.

[0021] Figure 2 The internal structure diagram of the closed detection dark box provided by the present application is provided. Figure 1

[0022] The enlarged structure diagram of A provided by the present application is provided. Figure 3 Figure 1 The structure diagram of the rotating movement mechanism provided by the present application is provided.

[0023] Figure 4 Figure 1 The internal structure diagram of the rotating column provided by the present application is provided.

[0024] Figure 5 The enlarged structure diagram of B provided by the present application is provided. Figure 4

[0025] Figure 6 The enlarged structure diagram of B provided by the present application is provided. Figure 5 ​​​​

[0026] Figure 7 The flow chart of the infrared light source intensity real-time adjustment system provided by the present application.

[0027] In the drawings: 1, support plate; 2, closed detection dark box; 3, infrared imaging unit; 4, active infrared illumination unit; 5, moving block; 6, rotating column; 7, guide shaft; 8, screw rod; 9, motor one; 10, motor two; 11, synchronous pulley; 12, synchronous belt; 13, hollow rotary hydraulic cylinder; 14, mounting groove; 15, telescopic shaft; 16, guide shaft; 17, clamping rod; 18, guide groove; 19, guide plate. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0029] In the process of on-line detection of power pipe cracks, factors such as changes in ambient light intensity, fluctuations in air suspended matter concentration, increases in light source operating temperature, decreases in optical window transmittance, production line speed adjustment, and changes in pipe rotation angular velocity work together to cause fluctuations in the quality of the acquired infrared images. Among them, the phenomenon of deviation of the average gray value of the image from the preset range and the reduction of the contrast of the target feature directly affects the accuracy of crack identification, making the detection system unable to maintain stable output performance, and thus restricting the improvement of detection efficiency and automation level.

[0030] For example, on a large-scale power pipe production line, when detecting black polyethylene material pipes, the surface high reflectivity characteristic causes visible light system reflection interference under the condition of enhanced workshop environmental light; after switching to the infrared detection mode, the fixed infrared light source intensity cannot adapt to the reflectivity difference of different batches of pipes, causing overexposure of high reflectivity pipe images and underexposure of low reflectivity pipe images. Further, when the production line speed is adjusted according to order requirements, the pipe rotation angular velocity changes synchronously, introducing motion blur effect, causing image clarity to decrease, false positives and false negatives to occur frequently, and operators being forced to perform manual rejudgment to confirm the detection results.

[0031] If the above image quality fluctuation problem is not solved, the detection system will long-term rely on manual intervention to handle false positives and false negatives, and cannot realize a fully automated detection process. As a result, the production efficiency is continuously restricted, the quality control risk is significantly increased, and long-term operation may also affect the reliability and product quality consistency of the production line due to premature equipment aging.

[0032] The specific implementation of the present application is described in detail below in combination with specific examples.

[0033] As Figure 2 andFigure 7 As shown, the power tube crack infrared detection device provided by one embodiment of the application comprises a support plate 1, a closed detection dark box 2 and a rotary moving mechanism installed on the top of the support plate 1, the rotary moving mechanism is used to drive the power tube to rotate and move linearly, an infrared imaging unit 3 is installed on the top inside the closed detection dark box 2, and a main active infrared illumination unit 4 is installed on the inner wall of the closed detection dark box 2. The infrared imaging unit 3 can be an infrared thermal imager or an infrared camera, which is used to capture the infrared radiation image of the surface of the power tube. The main active infrared illumination unit 4 can be composed of multiple infrared LED arrays or infrared lamp tubes, and the infrared light emitted by the main active infrared illumination unit 4 irradiates the surface of the power tube to enhance the infrared characteristics of the crack area. For example, infrared LED light sources with a wavelength of 850 nm or 940 nm can be used, and the light intensity can be changed by adjusting the driving current. When the power tube enters the closed detection dark box 2, the rotary moving mechanism drives the power tube to rotate and move linearly, so that the surface of the power tube is exposed to the light of the main active infrared illumination unit 4 and the image is captured by the infrared imaging unit 3.

[0034] The infrared light source intensity real-time adjustment system is electrically connected with the control end of the main active infrared illumination unit 4, which is designed to overcome the limitations of traditional fixed light source intensity detection and realize intelligent adaptive adjustment of light source intensity. For example, the system can be an independent embedded controller or an industrial PC, which is connected with the driving circuit of the main active infrared illumination unit 4 through a digital or analog signal interface, so as to realize accurate control of the light source intensity.

[0035] The infrared light source intensity real-time adjustment system comprises:

[0036] The environmental state evaluation module outputs an environmental compensation coefficient based on the ambient light intensity and the air suspended matter concentration. The ambient light intensity can be measured by an illuminance sensor installed outside or inside the detection dark box 2, and the air suspended matter concentration can be obtained by a laser scattering type or photoelectric type dust sensor. For example, the module can simply compare the sensor readings with a preset threshold value and output a discrete compensation coefficient (for example, three levels of low, medium and high) according to the comparison result, or calculate a continuous compensation coefficient through a linear interpolation function.

[0037] The system state evaluation module outputs a system attenuation compensation coefficient based on the light source operating temperature and the optical window transmittance. The light source operating temperature can be directly measured by a thermistor or an infrared temperature sensor to measure the surface temperature or internal junction temperature of the active infrared lighting unit 4. The optical window transmittance can be indirectly evaluated by regular calibration or by monitoring the light intensity difference before and after the optical window. For example, the module can preset a temperature-attenuation curve, and when the temperature rises, the corresponding attenuation compensation coefficient is obtained by querying the curve; for transmittance, an initial value can be set, and the attenuation compensation coefficient can be calculated according to the deviation of the actual measured value from the initial value.

[0038] The adaptation evaluation module outputs an average gray level-contrast adaptation degree based on the environmental compensation coefficient, the system attenuation compensation coefficient, the image average gray level, and the target feature contrast. The image average gray level and the target feature contrast can be calculated by the real-time image captured by the infrared imaging unit 3. For example, histogram analysis can be performed on the image to obtain the average gray level, and the target feature contrast can be calculated by an edge detection algorithm or the gray level difference of a specific region. The adaptation evaluation module can simply average these parameters, or determine the current adaptation degree through a multi-dimensional lookup table.

[0039] The motion state evaluation module outputs a motion compensation coefficient based on the line running speed and the pipe rotation angular velocity. The line running speed can be obtained by an encoder or a speed sensor on the line, and the pipe rotation angular velocity can be obtained by an encoder or a rotational speed sensor on the rotating movement mechanism. For example, the module can calculate the motion compensation coefficient through a simple proportional function according to the ratio of the current speed to the maximum speed. The faster the speed, the larger the compensation coefficient.

[0040] The infrared light source intensity regulation module outputs a target infrared light source intensity based on the motion compensation coefficient and the average gray level-contrast adaptation degree, and adjusts the active infrared lighting unit 4 to the intensity. The module can use a PID controller or a fuzzy logic controller, taking the motion compensation coefficient and the average gray level-contrast adaptation degree as inputs, to calculate the accurate driving current or voltage required by the active infrared lighting unit 4, so as to realize real-time regulation of the light source intensity. For example, when the adaptation degree is low and the motion speed is fast, the regulation module will calculate a higher target infrared light source intensity.

[0041] Traditional methods for detecting cracks in power pipes, whether manual visual inspection or automated visible light vision inspection systems, suffer from low efficiency, susceptibility to ambient light, and high false alarm and false negative rates. Even detection equipment using fixed infrared light sources cannot adapt to dynamic changes in pipe materials, production line speed, equipment aging, and workshop environments (such as dust and moisture) due to their fixed parameters, resulting in unstable image quality and difficulty in guaranteeing detection accuracy and efficiency. In contrast, this embodiment introduces a real-time infrared light source intensity adjustment system, achieving intelligent and adaptive control of the active infrared illumination unit 4. For example, in the above example, when ambient light intensity changes, airborne particulate matter concentration increases, light source operating temperature rises, or optical window transmittance decreases, the environmental state assessment module and system state assessment module can sense and quantify these external disturbances and internal attenuation factors in real time, outputting corresponding compensation coefficients. This contrasts with traditional solutions that lack awareness of environmental and system changes or only perform simple compensation; this embodiment can more accurately reflect actual working conditions.

[0042] In a preferred embodiment of the present invention, the infrared light source intensity control module determines the target infrared light source intensity in the following manner:

[0043] First, the basic target intensity is determined within a preset intensity range based on the motion compensation coefficient; the basic target intensity can be calculated as follows: [The motion compensation coefficient is then used to determine the basic target intensity]. Import formula Obtain the basic target strength ,in, This represents the maximum adjustable intensity of the light source. The minimum adjustable intensity of the light source; obtaining the basic target intensity. The steps are designed to be based on the motion state of the production line (by the motion compensation coefficient). (Reflection) Initially determine the baseline intensity of the infrared light source. The faster the movement, the higher the light source intensity is generally required to ensure image quality and avoid detail loss due to underexposure or motion blur. This step can be achieved by pre-calibrating experiments to establish a mapping table between different motion compensation coefficients and the required baseline light source intensity, which can then be looked up during runtime; alternatively, it can be achieved by real-time monitoring of the production line speed and combining empirical formulas or machine learning models to dynamically calculate the baseline target intensity that matches the current motion state. and These represent the maximum and minimum adjustable intensity of the infrared light source, respectively. These values ​​are typically determined by the physical characteristics of the light source hardware and the safe operating range, ensuring that the light source operates within a safe and effective range.

[0044] Then, based on the relationship between the average gray-scale-contrast fit and a preset threshold, the basic target intensity is adjusted: when the fit is below the lower threshold, the intensity is increased in a way that is negatively correlated with the fit; when the fit is above the upper threshold, the intensity is adjusted in a way that is positively correlated with the fit, ultimately limiting the result to the preset intensity range; the specific calculation method can be: the basic target intensity Adaptation to average grayscale-contrast Import Formula and use Limit the result to and In between, obtain ,in, The sensitivity coefficient, The larger the value, the more aggressive the system's response to image quality degradation, and the greater the increase in light source intensity. The smaller the value, the more conservative the system response and the smoother the adjustment. The lower limit threshold for fit This indicates that the image quality has just reached the lower limit of an acceptable range. This is the upper limit threshold for fit. This indicates that the image quality has entered the excellent range.

[0045] Calculate the infrared light source intensity of the target The steps are based on the actual quality of the image (adapted from average grayscale to contrast ratio). This method fine-tunes the intensity of the base target to achieve optimal detection results. It considers both aggressive compensation when image quality deteriorates and conservative adjustment when image quality is excellent. The calculation can be implemented using conditional branching logic programmed in a microcontroller or FPGA, based on... and , Based on the comparison results, different computation paths can be selected; alternatively, different computation paths can be pre-calculated and stored. The intensity adjustment factor at the given value is quickly determined at runtime using methods such as table lookup and linear interpolation. Sensitivity coefficient This is used to control the system's response to image quality degradation. It can be a fixed value, set during system debugging based on the actual application scenario and response speed requirements. For example, for scenarios with extremely high image quality requirements, a larger value can be set. A fixed value; or it can be dynamically adjusted, for example, switching between different inspection tasks or product types based on historical data or operator input to adapt to different inspection strategies. Adaptability lower limit threshold. representing that the image quality just reaches the lower limit of the acceptable range, which can be determined by expert experience or statistical analysis of a large amount of experimental data, for example, when the average gray value of the image is lower than a certain threshold or the contrast is lower than a certain threshold, the image quality is considered unacceptable, and the corresponding threshold is set; or, it can also be dynamically adjusted according to the specific detection task and defect type, for example, for the detection of micro cracks, a higher threshold may be required. representing that the image quality has entered the excellent range, which can also be determined by expert experience or experimental data, for example, when the average gray value and contrast of the image both reach a high level, the image quality is considered to be excellent enough, and the corresponding threshold is set; or, it can also be optimized according to factors such as system energy saving or light source life, for example, under the premise of ensuring image quality, the light source intensity is as low as possible to prolong the life of the light source. The limiting amplitude processing is to ensure that the calculated target infrared light source intensity is always within the physical adjustable range of the infrared light source to , preventing the light source from being damaged or the system from being unstable due to the calculation result exceeding the range. This processing can be realized at the software level through the min() and max() functions provided by the programming language; or, it can also be realized at the hardware level through the output limiting function of the analog circuit or digital-to-analog converter (DAC) to physically limit the output voltage or current, so as to control the light source intensity within a safe range

[0046] The scheme of the present application realizes precise adaptive control of the light source intensity of the active infrared illumination unit 4 through a specific running process of the infrared light source intensity regulation module. First, the system obtains the motion compensation coefficient from the motion state evaluation module, which reflects the demand of the production line running speed and pipe rotation angular velocity on the light source intensity, so as to calculate the basic target through the formula. This step ensures that the light source intensity can preliminarily adapt to the dynamic rhythm of the production line, avoiding image blur or underexposure due to too fast motion. Subsequently, the system further combines the average gray value-contrast adaptation degree output by the adaptation evaluation module to perform fine adjustment. When is lower than the preset lower limit threshold , it indicates that the image quality is poor, and the system will aggressively increase the light source intensity according to the adaptation degree difference to quickly improve the image quality; while is higher than the preset upper limit threshold , it indicates that the image quality is in the excellent range, and the system will conservatively perform proportional adjustment to avoid overexposure and energy waste. Finally, through limiting amplitude processing, the calculated target infrared light source intensity Limited to the physical adjustable range of the light source and This protects the light source equipment. The entire process combines the movement status of the production line with real-time image quality feedback to form a closed-loop intelligent adjustment mechanism, enabling the active infrared illumination unit 4 to always provide the most suitable illumination intensity, ensuring that the infrared imaging unit 3 acquires high-quality detection images. This effectively solves the problems of inaccurate light source intensity adjustment and inability to adapt to changing working conditions in traditional solutions.

[0047] Through the above technical solution, the infrared light source intensity control module can accurately calculate and adjust the intensity of the active infrared illumination unit 4 based on the production line's motion status and real-time image quality feedback. This effectively solves the problems of inaccurate light source intensity adjustment and inability to effectively address image quality adjustment requirements under different conditions in traditional solutions. This solution achieves precise control of the infrared light source intensity through phased, conditional calculations, avoiding the inaccuracies caused by traditional fixed parameters or manual intervention. Simultaneously, when image quality deteriorates, the system can aggressively increase the light source intensity to quickly restore image quality and ensure detection stability; when image quality is excellent, it conservatively adjusts the intensity to avoid overexposure and energy waste, thereby improving detection stability and efficiency, and extending the lifespan of the light source.

[0048] In a preferred embodiment of the present invention, the operation flow of the motion state assessment module is as follows:

[0049] The system acquires the current production line operating speed and the pipe rotation angular velocity. The production line operating speed can be obtained in various ways; for example, it can be monitored in real time using an encoder or laser rangefinder installed on the production line, or the current set operating speed can be directly obtained through data interaction with the production line control system. Similarly, the pipe rotation angular velocity can be acquired in multiple ways. For instance, a rotary encoder can be installed on the rotating mechanism to directly measure the rotation angular velocity of the rotating column 6; or, the rotation angular velocity can be calculated by identifying the motion trajectory of feature points on the surface of the pipe using a vision system. This real-time data provides accurate input for subsequent compensation coefficient calculations.

[0050] The line running speed and the pipeline rotation angular velocity are respectively processed by ratio with the maximum line speed and the maximum rotation angular velocity, and the upper limit of the ratio is limited to 1 by using the min function, and then the line running speed index and the pipeline rotation angular velocity index are obtained; this step is aimed at normalizing the original speed and angular velocity data, and converting them into dimensionless indexes in the range of 0 to 1. For example, the line running speed index can be obtained by dividing the current line running speed by the preset maximum line running speed, and ensuring that the index does not exceed 1, so as to avoid abnormal values in extreme cases. Similarly, the pipeline rotation angular velocity index is obtained in a similar manner by processing it by ratio with the maximum rotation angular velocity and limiting the amplitude. This normalization processing enables the speed and angular velocity data of different dimensions to be compared and calculated on a unified scale, laying a foundation for subsequent motion compensation coefficient calculation.

[0051] The motion compensation coefficient is increased when any speed index is increased based on the fusion calculation of the line running speed index and the pipeline rotation angular velocity index. The specific calculation method can be: the line running speed index and the pipeline rotation angular velocity index are imported into the formula to obtain the motion compensation coefficient , The output range is 0-1, and the larger the value, the faster the motion, and the higher the light source intensity required. This formula ingeniously combines the requirements of line running speed and pipeline rotation angular velocity for light source intensity. When the line running speed or the pipeline rotation angular velocity increases, the corresponding index or will increase, resulting in or decrease, and then the product decreases, finally making the motion compensation coefficient increase. Conversely, when the speed or angular velocity decreases, will also decrease accordingly. The formula ensures that the output range of is between 0 and 1, and the larger the value, the faster the motion of the power pipe, and the higher the requirement for infrared light source intensity. This nonlinear combination method can more accurately reflect the comprehensive demand for light source intensity in the actual detection process.

[0052] The scheme of the present application realizes accurate calculation of the motion compensation coefficient through the above operation process, to dynamically adapt to the changes of the production line speed and the pipe rotation. Specifically, by obtaining the current production line running speed and the pipe rotation angular velocity in real time, it is ensured that the calculation is based on the latest working condition data. Then, the speed and angular velocity are respectively processed by ratio with the maximum value, and the upper limit is limited to 1 by using the min function. This normalization processing effectively prevents extreme value interference, ensures the comparability and stability of the input data, so as to obtain the production line running speed index and the pipe rotation angular velocity index. Finally, these indexes are introduced into a specific mathematical formula to calculate the motion compensation coefficient . The formula comprehensively considers the joint effect of speed and angular velocity. When both are high, the coefficient is close to 1, indicating that the light source intensity needs to be enhanced; when any factor is low, the coefficient is correspondingly reduced, avoiding excessive adjustment. The output range of the motion compensation coefficient is limited to 0-1, ensuring that the coefficient is within a reasonable range and avoiding invalid adjustment. Overall, this method solves the problem of inaccurate motion compensation coefficient by standardizing the input and designing an intelligent formula, so that the infrared light source intensity can efficiently respond to the dynamic changes of the production line. In the power pipe crack infrared detection device, the motion compensation coefficient will be further introduced into the infrared light source intensity regulation module, together with the average gray-scale-contrast adaptation degree to determine the final target infrared light source intensity. This linkage mechanism enables the light source intensity to not only adapt to environmental and system attenuation, but also to be finely adjusted according to the actual motion state of the power pipe, so that high-quality infrared images can be obtained at different production tempos, ensuring the stability and accuracy of crack detection.

[0053] Through the above technical scheme, the present application can accurately evaluate the influence of the motion state of the power pipe on the infrared imaging quality and generate a reasonable motion compensation coefficient accordingly. This enables the infrared light source intensity regulation module to dynamically adjust the output intensity of the active infrared illumination unit 4 according to the real-time changes of the production line running speed and the pipe rotation angular velocity. Therefore, even in the case of frequent adjustment of the production line tempo or large changes in the power pipe rotation speed, the images obtained by the infrared imaging unit 3 can have stable brightness and contrast, avoiding image quality degradation due to motion blur or underexposure / overexposure, thereby significantly improving the accuracy and reliability of power pipe crack detection and reducing the risk of false positives and false negatives.

[0054] As a preferred embodiment of the present application, the adaptation evaluation module calculates the average gray-scale-contrast adaptation degree by the following method:

[0055] Obtain the environmental compensation coefficient, the system attenuation compensation coefficient, the image average gray value and the target feature contrast; these parameters are the key inputs for comprehensive evaluation of the current detection environment, device state and the quality of the infrared image itself. The environmental compensation coefficient and the system attenuation compensation coefficient can be obtained by collecting data in real time through various sensors integrated in the detection device (for example, a photosensitive sensor for ambient light intensity, a particle sensor for air suspended matter concentration, a temperature sensor for light source working temperature), and combined with a preset model or lookup table. The image average gray value and the target feature contrast are analyzed and extracted in real time by the image data captured by the infrared imaging unit 3 through the image processing module (for example, an image processor based on FPGA or DSP). In addition, the environmental compensation coefficient and the system attenuation compensation coefficient can also be obtained through the data interface with the factory central control system, which may have integrated environmental monitoring and device state monitoring functions. The image average gray value and the target feature contrast can be calculated preliminarily before the image is transmitted to the main control unit by embedding a special image analysis algorithm in the image acquisition path of the infrared imaging unit 3.

[0056] Calculate the deviation of the image average gray value from the ideal gray value to obtain the gray adaptation degree; the specific calculation method of the gray adaptation degree can be: the image average gray value Import the formula , and use Limit the result in the range of 0-1 to obtain the gray adaptation degree , wherein is the ideal gray value, The average value of the maximum and minimum values of the ideal gray value can be taken; this step aims to quantify the matching degree between the overall brightness (average gray value) of the current infrared image and the expected optimal brightness, and standardize it to a value between 0 and 1, so as to facilitate subsequent comprehensive evaluation. The ideal gray value can be preset to a specific value according to the characteristics of different power pipe materials (such as PE, PVC) and colors (such as black, white) through experimental calibration or expert experience. For example, for black PE pipes, a moderately low gray value can be set as the ideal value to ensure the visibility of crack details. The ideal gray value can also be dynamically calculated by statistically analyzing a large number of infrared images of qualified power pipes to obtain the average or median of the gray value distribution, and fine-tuned according to the detection requirements to adapt to production batch differences.

[0057] Process the target feature contrast and the minimum allowed contrast by ratio, and obtain the contrast adaptation degree ; this step is used to evaluate the clarity and recognizability of the key detection target (such as cracks) in the infrared image, i.e. its degree of differentiation from the background, and convert it into a standardized fitness. The minimum allowable contrast can be pre-set by the system integrator or user according to the performance indicators of the infrared imaging unit 3, the minimum detectable size of the crack, and the false positive rate requirement. For example, a threshold is set below which the contrast will result in cracks being difficult to be reliably identified. The minimum allowable contrast can also be dynamically analyzed by an image processing algorithm in combination with edge detection or feature extraction techniques, and the threshold is adaptively adjusted according to the difficulty of the detection task.

[0058] The gray scale fitness and the contrast fitness are averaged, and the larger value of the ambient compensation coefficient and the system attenuation compensation coefficient is adjusted for attenuation to output the final average gray scale-contrast fitness; the specific calculation method can be: the gray scale fitness , the contrast fitness , the ambient compensation coefficient , and the system attenuation compensation coefficient Import the formula to obtain the average gray scale-contrast fitness , The output range is 0-1, the closer the value is to 1, the more suitable the image quality is for the current detection requirement. This step is the core of the adaptation evaluation, which comprehensively considers the internal image quality (gray scale and contrast) and the influence of external environmental interference and system performance decay to obtain a comprehensive image quality evaluation index. The calculation of this formula can be performed on a dedicated processor (such as a microcontroller or an embedded system) in the infrared light source intensity real-time adjustment system. The processor receives input parameters from various modules and performs calculations according to pre-set algorithm logic to finally output . The calculation logic can also be implemented in the host computer software, which receives all necessary coefficients and values through a communication interface (such as Ethernet or serial port), performs calculations, and feeds back the results to the infrared light source intensity control module. This way is convenient for algorithm updating and maintenance.

[0059] The scheme of the present application obtains the key parameters affecting image quality from multiple dimensions through the above process, including environmental interference, system decay, and image gray scale and contrast. Then, the gray scale fitness and the contrast fitness are calculated to quantify the performance of the image in terms of brightness and feature clarity. The gray scale fitness evaluates whether the overall brightness of the image is moderate by comparing the current average gray scale value with the ideal gray scale value, avoiding over-brightness or over-darkness. The contrast fitness The recognizability of the key defect feature is ensured by comparing the target feature contrast with the minimum allowable contrast. Finally, these intrinsic image quality indicators are integrated with the environmental compensation coefficient and the system attenuation compensation coefficient to calculate the average gray-scale-contrast adaptation degree by formula . This formula ingeniously takes the average of gray-scale and contrast as a representative of the intrinsic quality of the image, and multiplies it by a penalty factor that takes into account external disturbances and system attenuation. Among them, the embodies the "short board effect", that is, when any of the environmental interference or system attenuation is more serious, it will have a significant impact on the overall adaptation degree, thus prompting the system to preferentially compensate for the most serious deficiency. This comprehensive adaptation degree is then passed to the infrared light source intensity regulation module as the key basis for adjusting the intensity of the active infrared illumination unit 4. In this way, the infrared light source intensity real-time adjustment system can dynamically and accurately assess the quality of the current infrared image, and comprehensively consider the external environment and internal system state, providing reliable input for subsequent light source intensity adjustment, so as to ensure that in the process of power pipe crack infrared detection, no matter how the production line speed, environmental conditions or equipment state change, the best image quality can be maintained, significantly improving the stability and accuracy of detection.

[0060] Through the above technical solution, the adaptation evaluation module can dynamically and accurately evaluate the quality of the infrared image, and comprehensively consider the gray-scale, contrast of the image itself, and various factors such as external environmental interference and internal system attenuation. This makes the infrared light source intensity regulation module receive more comprehensive and accurate image quality feedback, so as to realize fine adjustment of the intensity of the active infrared illumination unit 4. This adjustment not only effectively avoids the overexposure or underexposure problem caused by traditional fixed light source intensity, ensures that clear and high-contrast infrared images can be obtained under various complex working conditions, and significantly improves the accuracy and reliability of power pipe crack detection. At the same time, by optimizing the light source intensity, it is also helpful to prolong the service life of the light source and reduce energy consumption.

[0061] As a preferred embodiment of the present application, the system state evaluation module running process is:

[0062] Obtain the current light source operating temperature and optical window transmittance; the light source operating temperature directly reflects the heat dissipation condition and aging degree of the light source, and too high temperature will accelerate the decay of the light source and reduce the luminous efficiency. The optical window transmittance indicates the cleanliness of the optical path inside the closed detection dark box 2, for example, the attachment of dust, water vapor or oil stains will reduce the transmittance of infrared light, thereby weakening the illumination effect. Obtaining these parameters is the basis for accurate system performance evaluation, ensuring the timeliness and accuracy of subsequent compensation. This can be achieved by integrating temperature sensors near the active infrared illumination unit 4 to measure the surface temperature or internal junction temperature of the light source in real time. At the same time, the optical window transmittance can be measured by setting photoelectric sensors before and after the optical window to measure the transmittance of specific wavelength infrared light, or by periodic calibration and image analysis to indirectly evaluate its decay degree.

[0063] Max-min normalization of the current light source operating temperature to obtain the light source operating temperature index; the purpose is to convert light source operating temperature data of different dimensions and ranges into a unified, dimensionless index, so that it can be effectively compared and integrated with other evaluation indicators. Normalization processing can eliminate the absolute value difference of the original temperature data, linearly map it between 0 and 1 (or a specific range), so as to more intuitively reflect the relative degree of temperature influence on system performance. For example, a minimum safe operating temperature and a maximum allowed operating temperature of a light source can be set to map the real-time measured temperature value to this interval.

[0064] Take the complement of the ratio of the current window transmittance to the initial transmittance (i.e. one minus the ratio) as the optical window transmittance decay index, which is used to quantify the degree of transmittance performance decline of the optical window due to pollution or aging. By comparing the currently measured transmittance with the ideal transmittance in the initial state of the system, a ratio can be obtained, and the smaller the ratio, the more serious the transmittance decay. Taking its complement will convert the decay degree into a positive index, i.e. the decay index, and the larger the index value, the more serious the decay, and the more compensation is needed. This processing method is intuitive and easy to understand, and can accurately reflect the contribution of the optical window to the loss of infrared light energy.

[0065] Take the larger value of the light source operating temperature index and the optical window transmittance decay index as the system decay compensation coefficient; the larger the value, the more serious the system performance decay, and more compensation is needed. The maximum value is used to reflect the "short board effect" of system performance, and when either the temperature is too high or the window is seriously polluted, the system needs significant compensation.

[0066] By the technical solution, the system performance attenuation can be accurately quantified, and the most serious attenuation factor can be responded preferentially. By monitoring the light source working temperature and the optical window transmittance in real time and converting them into standardized indexes, the system can comprehensively and accurately evaluate the system state. Especially importantly, the system attenuation compensation coefficient is determined by taking the larger value, which effectively avoids the problem that the serious attenuation of a single factor is averaged by other non-serious factors in the traditional method, and ensures that the infrared light source intensity can be adjusted in time and significantly when any "short board" such as light source overheating or optical window pollution occurs. This makes the infrared light source intensity regulation module obtain more accurate system attenuation information, so as to more accurately adjust the output of the active infrared illumination unit 4, maintain the stability and high quality of the detection image, and significantly improve the adaptability and reliability of the electric power pipe crack infrared detection device under long-term operation and complex working conditions.

[0067] As a preferred embodiment of the present application, the environmental state evaluation module running process is as follows:

[0068] The current environmental light intensity and the air suspended matter concentration are obtained; the environmental light intensity directly affects the background noise of infrared imaging, and the air suspended matter concentration scatters or absorbs infrared light, reducing the image definition. This can be realized by setting an environmental light sensor (such as a photoresistor, a photodiode or a special illuminometer) outside or inside the closed detection dark box 2 to measure the environmental light intensity in real time. At the same time, a particulate matter sensor (such as a PM2.5 / PM10 sensor based on the laser scattering principle) can be deployed to detect the suspended matter concentration in the air. In addition, a multifunctional environmental sensor module can also be integrated, which can output the environmental light intensity and the air suspended matter concentration data at the same time, and transmit the data to the processing unit through wired or wireless mode.

[0069] The current ambient light intensity and the air suspended matter concentration are respectively processed by ratio with the ambient light intensity threshold and the air suspended matter concentration, and the ratio is limited to 1 by using the min function, and then the ambient light intensity index and the air suspended matter concentration index are obtained; the purpose is to standardize the original ambient light intensity and the air suspended matter concentration data, and convert them into dimensionless indexes, so as to facilitate subsequent unified calculation and comparison. The ratio processing can reflect the degree of current environmental disturbance relative to the preset threshold, and the min function limiting the ratio to 1 ensures that the index will not increase infinitely due to extreme conditions, thereby avoiding excessive adjustment of the compensation coefficient and maintaining the stability of the system. This step can be performed by a digital signal processor (DSP) or a microcontroller (MCU) executing a preset algorithm. First, the real-time ambient light intensity value obtained by the sensor is divided by the preset ambient light intensity threshold to obtain a ratio; similarly, the real-time air suspended matter concentration value is divided by the preset air suspended matter concentration threshold to obtain another ratio. Then, the min(value, 1) function is applied to limit the two ratios, thereby obtaining the ambient light intensity index and the air suspended matter concentration index. Alternatively, it can also be realized in the upper computer software, and a data processing module is written by programming language to receive sensor data and perform ratio calculation and limiting operation according to the preset threshold.

[0070] The ambient light intensity index and the air suspended matter concentration index are subjected to square root mean operation fusion calculation to highlight the contribution of the larger interference factor to the overall environmental disturbance; the specific calculation method can be: the ambient light intensity index and the air suspended matter concentration index are imported into the formula to obtain the environmental compensation coefficient , The output range is 0-1, the larger the value, the stronger the environmental disturbance, and the formula adopts the square root mean form to emphasize the dominant role of the larger interference factor (ambient light or suspended matter). The formula is the core of calculating the environmental compensation coefficient, which adopts the square root mean (RMS) form, can effectively consider the two interference factors of ambient light and air suspended matter, and especially emphasizes the dominant factor with greater impact. When one interference factor is significantly higher than the other, the formula will make it occupy a larger weight in the final compensation coefficient, so that the system can more accurately respond to the main disturbance source. The output range of the environmental compensation coefficient is 0-1, which directly represents the degree of environmental disturbance and provides a quantitative basis for subsequent adjustment of the infrared light source intensity. This mathematical operation can be realized in an embedded controller (such as FPGA or high-performance MCU), which receives the ambient light intensity index and the air suspended matter concentration index , the square, sum, divide by 2, and square root operations are performed, and finally the . Alternatively, it can also be implemented in the control software running on an industrial PC or server, where the software module receives the two indices, calls a mathematical library function to perform the square root of the mean calculation, and passes the result as output to the infrared light source intensity regulation module.

[0071] The environmental state evaluation module detects the interference in the environment by obtaining the current ambient light intensity and the concentration of airborne particulate matter. These raw data are then standardized by being divided by the preset threshold and limited in amplitude, generating the ambient light intensity index and the airborne particulate matter concentration index . This standardization ensures the comparability of different types of interference factors and avoids the influence of extreme values on system stability. Then, these two indices are imported into the square root of the mean formula to calculate the environmental compensation coefficient . The cleverness of this formula is that it can highlight the effect of the dominant interference factor in the environment. For example, when the ambient light intensity is significantly higher than the airborne particulate matter concentration, the ambient light intensity index will have a greater weight in the formula, making more inclined to reflect the influence of ambient light; vice versa. This ensures that the system can effectively compensate for the current main interference source, avoiding the "one-size-fits-all" compensation strategy. The environmental compensation coefficient (range 0-1) obtained finally quantifies the severity of environmental interference. This environmental compensation coefficient is then passed to the adaptation evaluation module, along with the system attenuation compensation coefficient, the average image gray value, and the target feature contrast, to calculate the average gray value-contrast adaptation degree . By including in the calculation of , this scheme can ensure that the adaptation degree will decrease accordingly when the environmental interference is strong, prompting the infrared light source intensity regulation module to output higher target infrared light source intensity. This linkage mechanism enables the entire power pipe crack infrared detection device to intelligently adapt to changing environmental conditions, even in complex ambient light or high airborne particulate matter conditions, maintaining stable image quality and detection performance through dynamic adjustment of infrared light source intensity, effectively solving the problem of unstable image quality in traditional fixed light source or manual intervention modes.

[0072] By the above technical solution, the application can effectively solve the problem of unstable image quality caused by changes in ambient light intensity and air suspended matter concentration during the infrared detection of power pipe cracks. The scheme converts the real-time acquisition of ambient light intensity and air suspended matter concentration into standardized ambient light intensity index and air suspended matter concentration index, providing a reliable basis for the quantification of environmental interference. Importantly, the formula in the form of square root mean is used to calculate the environmental compensation coefficient , enabling the system to intelligently identify and emphasize the dominant interference factors in the environment. This means that when ambient light intensity is the main interference, the system will focus more on compensating for the effects of ambient light; when air suspended matter concentration is the main interference, the system will focus more on compensating for the effects of suspended matter. This adaptive compensation mechanism avoids the conservative strategy of "one-size-fits-all" or "worst-case scenario" in traditional schemes, making the environmental compensation coefficient more accurately reflect the actual environmental interference level. Since the environmental compensation coefficient is included in the calculation of the adaptive evaluation module, it directly affects the evaluation results of the average gray-scale-contrast adaptation degree . When environmental interference increases, , the increase will lead to the decrease of , thus prompting the infrared light source intensity regulation module to correspondingly increase the output intensity of the active infrared illumination unit 4. This linked adjustment mechanism ensures that even in harsh or variable environmental conditions, the infrared imaging unit 3 can capture images with stable average gray-scale values and target feature contrasts, ensuring the accuracy and reliability of crack detection, significantly improving the robustness and automation level of the detection device.

[0073] As Figures 1-6As shown, as a preferred embodiment of the present application, the rotating movement mechanism comprises two guide plates 19 fixed on the top of the support plate 1, and a moving block 5 and a moving assembly arranged on the top of the support plate 1, the moving assembly is used to drive the moving block 5 to move linearly, one side of the moving block 5 is rotationally connected with a rotating column 6, an inner wall clamping assembly is arranged on the rotating column 6, the inner wall clamping assembly is used to connect the rotating column 6 with the inner wall of the power pipe, a rotating assembly is arranged on the moving block 5 and used to drive the rotating column 6 to rotate.

[0074] In the embodiment of the present application, when the power pipe crack infrared detection is performed, the power pipe is placed on the guide plates 19, the two guide plates 19 support the left and right sides of the power pipe, the motor 9 drives the screw rod 8 to rotate, under the guidance of the two guide shafts 7, the screw rod 8 drives the moving block 5 to move through the threaded transmission, the moving block 5 drives the rotating column 6 to extend into one end of the power pipe, the hollow rotary hydraulic oil cylinder 13 drives the telescopic shaft 15 to move towards the power pipe, the telescopic shaft 15 drives one end of the clamping rod 17 to move horizontally, under the guidance of the guide shaft 16 and the guide groove 18, the clamping rod 17 moves towards the inner wall of the power pipe, until the three clamping rods 17 are in contact with the inner wall of the power pipe, at this time, the rotating column 6 is connected with the power pipe, the motor 10 drives the rotating column 6 to rotate through the synchronous pulley 11 and the synchronous belt 12, the rotating column 6 drives the power pipe to rotate, the motor 9 continues to rotate, thereby driving the moving block 5 to drive the rotating column 6 to move linearly, the rotating column 6 drives the power pipe to move linearly, and the power pipe is detected in a rotating manner by the infrared imaging unit 3.

[0075] The above merely describes preferred embodiments of the present application, and is not used to limit the present application, any modification, equivalent replacement and improvement within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. An infrared detection device for cracks in power pipes, comprising a support plate, a closed detection chamber and a rotating moving mechanism mounted on the top of the support plate, the rotating moving mechanism being used to drive the power pipe to rotate and move linearly, an infrared imaging unit being mounted on the top of the closed detection chamber, and an active infrared illumination unit being mounted on the inner wall of the closed detection chamber, characterized in that... Also includes: An infrared light source intensity real-time adjustment system is electrically connected to the control terminal of the active infrared illumination unit. The infrared light source intensity real-time adjustment system includes: The environmental status assessment module outputs an environmental compensation coefficient based on ambient light intensity and airborne particulate matter concentration. The system status assessment module outputs the system attenuation compensation coefficient based on the light source operating temperature and the optical window transmittance. The adaptation evaluation module outputs the average gray-contrast adaptation degree based on the environmental compensation coefficient, the system attenuation compensation coefficient, the average gray value of the image and the contrast of the target features. The motion status assessment module outputs motion compensation coefficients based on the production line operating speed and the pipeline rotation angular velocity. The infrared light source intensity control module outputs the target infrared light source intensity based on the motion compensation coefficient and the average gray-scale-contrast adaptation, and adjusts the active infrared illumination unit to that intensity.

2. The infrared detection device for cracks in power pipes according to claim 1, characterized in that, The infrared light source intensity control module determines the target infrared light source intensity in the following way: First, the basic target intensity is determined within a preset intensity range based on the motion compensation coefficient; Then, based on the relationship between the average gray-scale-contrast fit and the preset threshold, the intensity of the basic target is adjusted: when the fit is lower than the lower threshold, the intensity is increased in a way that is negatively correlated with the fit. When the fit is higher than the upper limit threshold, the intensity is adjusted in a way that is positively correlated with the fit, and the result is ultimately limited to the preset intensity range.

3. The infrared detection device for cracks in power pipes according to claim 2, characterized in that, The operation process of the motion state assessment module is as follows: The production line operating speed and pipeline rotational angular velocity are compared with the maximum production line speed and maximum rotational angular velocity, respectively. After using the min function to limit the upper limit of the ratio to 1, the production line operating speed index and pipeline rotational angular velocity index are obtained. The motion compensation coefficient is calculated by combining the complements of the production line operating speed index and the pipeline rotation angular velocity index, so that the motion compensation coefficient increases when either speed index increases.

4. The infrared detection device for cracks in power pipes according to claim 2, characterized in that, The adaptation evaluation module calculates the average grayscale-contrast adaptation score in the following manner: The grayscale fit is obtained by calculating the deviation of the average grayscale value of the image from the ideal grayscale value. The target feature contrast is compared with the minimum allowable contrast, and then the ratio is limited to 1 using a min function to obtain the contrast fit. ; The grayscale adaptation and contrast adaptation are averaged, and then attenuation adjustment is performed based on the larger value between the environmental compensation coefficient and the system attenuation compensation coefficient to output the final average grayscale-contrast adaptation.

5. The infrared detection device for cracks in power pipes according to claim 4, characterized in that, The system status assessment module operates as follows: The current operating temperature of the light source is normalized by the maximum and minimum to obtain the operating temperature index of the light source. The current window transmittance is compared with the initial transmittance, and the complement of the ratio (i.e., the ratio minus one) is taken as the optical window transmittance attenuation index. The larger of the light source operating temperature index and the optical window transmittance attenuation index is taken as the system attenuation compensation coefficient; the larger the value, the more severe the system performance attenuation.

6. The infrared detection device for cracks in power pipes according to claim 4, characterized in that, The operation process of the environmental status assessment module is as follows: The current ambient light intensity and airborne particulate matter concentration are compared with the ambient light intensity threshold and airborne particulate matter concentration, respectively. After the ratio is limited to 1 by the min function, the ambient light intensity index and airborne particulate matter concentration index are obtained. The ambient light intensity index and the airborne particulate matter concentration index are calculated by merging the square root average to highlight the contribution of larger interfering factors to the overall environmental disturbance level.

7. The infrared detection device for cracks in power pipes according to claim 1, characterized in that, The rotating moving mechanism includes two guide plates fixed to the top of the support plate, and a moving block and a moving component set on the top of the support plate. The moving component is used to drive the moving block to move linearly. A rotating column is rotatably connected to one side of the moving block. An inner wall clamping component is set on the rotating column. The inner wall clamping component is used to connect the rotating column to the inner wall of the power pipe. A rotating component is set on the moving block to drive the rotating column to rotate.

8. The infrared detection device for cracks in power pipes according to claim 7, characterized in that, The moving component includes two guide shafts fixed to the top of a support plate, the two guide shafts being arranged in parallel, the moving block being slidably connected to the two guide shafts, a lead screw being rotatably connected to the top of the support plate, the lead screw passing through the moving block and being threadedly connected to the moving block, and a motor being fixed to the top of the support plate, the rotating end of the motor being connected to the lead screw.

9. The infrared detection device for cracks in power pipes according to claim 7, characterized in that, The inner wall clamping assembly includes three mounting slots evenly arranged on the rotating column, each mounting slot containing a clamping rod, and each mounting slot containing a guide shaft. Each clamping rod has a guide groove, and the guide shaft is slidably connected within the guide groove. A telescopic shaft is slidably connected to the axis of the rotating column, and the telescopic shaft is hinged to one end of the clamping rod. A hollow rotary hydraulic cylinder is fixed to the side of the moving block away from the rotating column, and the telescopic end of the hollow rotary hydraulic cylinder is connected to the telescopic shaft.

10. The infrared detection device for cracks in power pipes according to claim 7, characterized in that, The rotating assembly includes a second motor fixed on the side of the moving block away from the rotating column. Both the rotating end of the second motor and the rotating column are fixed with synchronous pulleys, and the two synchronous pulleys are connected by a synchronous belt drive.

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