Crystallizer copper pipe quality detection and maintenance method, device, equipment and medium

Abstract

The invention relates to the technical field of quality detection of crystallizer copper pipes. The crystallizer copper pipe quality detection and maintenance method comprises the steps that geometric structure information of a crystallizer copper pipe is obtained, a three-dimensional structure model is obtained, automatic defect detection is conducted on outer wall image information of the crystallizer copper pipe through a CNN model, and surface defect information is obtained. And performing nondestructive testing on the inner wall image information of the crystallizer copper pipe through an ultrasonic technology to obtain internal defect information, obtaining overall quality state information based on the surface defect information and the internal defect information, and inputting the overall quality state information into a quality evaluation model to obtain a quality score of the crystallizer copper pipe. And according to the quality score of the crystallizer copper pipe, determining the use risk grade of the crystallizer copper pipe, and based on the use risk grade, generating maintenance suggestions and prevention measure suggestions corresponding to the use risk grade. The method has the effect of improving the quality of the crystallizer copper pipe.

Description

Technical Field

[0001] The present invention relates to the technical field of quality inspection of a crystallizer copper tube, and in particular to a method, device, equipment and medium for quality inspection and maintenance of a crystallizer copper tube. Background Art

[0002] The copper tube of the crystallizer is the core component in the continuous casting process. Its performance and quality are directly related to the quality and production efficiency of the final ingot. In recent years, with the rapid development and technological progress of the metallurgical industry, higher requirements have been put forward for the quality control of the copper tube of the crystallizer. Traditional manual visual inspection and simple physical measurement methods have gradually failed to meet the needs of modern manufacturing, especially in terms of quality inspection. Summary of the invention

[0003] In order to improve the quality of a crystallizer copper tube, the present application provides a crystallizer copper tube quality detection and maintenance method, device, equipment and medium.

[0004] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A method for quality inspection and maintenance of a crystallizer copper tube, the method comprising: Acquiring geometric structure information of the copper tube of the crystallizer, and processing the geometric structure information by three-dimensional imaging technology to obtain a three-dimensional structure model; Acquire outer wall image information from the three-dimensional structure model, and perform automated defect detection on the outer wall image information of the crystallizer copper tube through a CNN model to obtain surface defect information; Acquire inner wall image information from the three-dimensional structure model, and perform nondestructive testing on the inner wall image information of the crystallizer copper tube by ultrasonic technology to obtain internal defect information; Based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain overall quality status information; The overall quality status information is input into a quality assessment model, and the quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a crystallizer copper tube quality score; According to the quality score of the crystallizer copper tube, the use risk level of the crystallizer copper tube is determined, and based on the use risk level, maintenance suggestions and preventive measures suggestions corresponding to the use risk level are generated.

[0005] By adopting the above technical scheme, the complete geometric structure information of the crystallizer copper tube can be obtained through precise three-dimensional imaging technology, which reduces the influence of traditional manual measurement errors and provides high-precision basic data for subsequent defect detection and quality assessment, thereby improving the accuracy and reliability of detection. The CNN model is used to efficiently identify various surface defects on the outer wall of the crystallizer copper tube, avoiding the subjectivity and labor intensity of manual detection, thereby improving the accuracy and speed of defect identification and reducing the risk of human error. The use of ultrasonic technology to accurately obtain internal defect information will not cause any damage to the crystallizer copper tube, thereby ensuring the integrity of the pipeline and avoiding unnecessary risks that may be caused by traditional destructive testing. The overall quality status of the crystallizer copper tube is evaluated based on comprehensive defect data, avoiding the evaluation method that relies only on a single defect type, thereby providing more accurate quality assessment results and ensuring the comprehensiveness and scientificity of the evaluation results. The overall quality of the crystallizer copper tube can be scientifically evaluated through the preset quality scoring standard. Combined with the calculation results of the quality assessment model, the quality score of the crystallizer copper tube can be quickly obtained, ensuring the objectivity and systematicness of the quality assessment process, which helps to accurately judge whether the crystallizer copper tube meets the use requirements. The risk level of use is automatically determined based on the quality score of the crystallizer copper tube, and targeted maintenance suggestions and preventive measures are generated according to different risk levels, ensuring the long-term safe operation of the equipment, reducing the risk of sudden failures, and improving the efficiency and pertinence of maintenance work.

[0006] In a preferred example, the present application can be further configured as follows: the outer wall image information is obtained from the three-dimensional structure model, and the outer wall image information of the crystallizer copper tube is automatically defect-detected by a CNN model to obtain surface defect information, including: Performing image preprocessing on the outer wall image information to obtain preprocessed outer wall image information; The CNN model is used to perform feature extraction and automatic analysis on the preprocessed outer wall image information, identify and classify surface defects in the preprocessed outer wall image information, and obtain the surface defect information.

[0007] By adopting the above technical solution, image preprocessing is performed on the outer wall image information to remove noise, enhance image contrast, improve detail clarity, etc., so as to obtain the preprocessed outer wall image information. This process ensures the quality of the original image in subsequent analysis and makes feature extraction more accurate. Then, the CNN model is used to extract features and automatically analyze the preprocessed outer wall image information to identify and classify surface defects in the crystallizer copper tube, such as cracks, pits, corrosion, etc., and finally generate surface defect information. This automated analysis method not only improves the detection efficiency, but also reduces manual misjudgment and missed judgment, ensuring the accurate identification of surface defects of the crystallizer copper tube.

[0008] In a preferred example, the present application may be further configured as follows: the inner wall image information is obtained from the three-dimensional structure model, and the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain internal defect information, including: Performing nondestructive testing on the inner wall image information of the mold copper tube by using the ultrasonic technology to obtain inner wall echo information; The inner wall echo information is analyzed based on a time-frequency domain analysis method to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating the internal defect information.

[0009] By adopting the above technical solution, ultrasonic technology is used to scan the image information of the inner wall of the crystallizer copper tube, and the ultrasonic beam penetrates the inner wall of the crystallizer copper tube to obtain the reflected echo information. These echo information contains the characteristics of the inner wall structure and can be used to identify potential defects such as cracks, pores, corrosion, etc. Time domain analysis can help extract the delay and amplitude changes of the echo, and frequency domain analysis can reveal the frequency characteristics and energy changes in the echo information. It can effectively determine whether there are defects on the inner wall of the crystallizer copper tube. If the change in the echo information exceeds the set threshold, it is judged to be defective, otherwise it is normal.

[0010] In a preferred example, the present application may be further configured as follows: the inner wall echo information is analyzed based on the time-frequency domain analysis method to determine whether there is a defect on the inner wall of the crystallizer copper tube, thereby generating the internal defect information, including: performing time domain analysis on the inner wall echo information, extracting the time delay change and amplitude change of the inner wall echo information, and obtaining a time domain analysis result; Performing frequency domain analysis on the inner wall echo information, extracting frequency characteristic changes and energy changes of the inner wall echo information, and obtaining frequency domain analysis results; The time domain analysis result and the frequency domain analysis result are respectively compared with a preset internal defect threshold value to determine whether there is a defect on the inner wall of the crystallizer copper tube, thereby generating the internal defect information.

[0011] By adopting the above technical solution, the inner wall echo information is analyzed in the time domain, and the time domain analysis results are obtained by extracting the delay change and amplitude change of the echo signal. These time domain features help to reveal the propagation characteristics of the echo signal and reflect the structural anomalies or defects of the inner wall of the crystallizer copper tube, such as the echo signal changes caused by cracks or corrosion. The inner wall echo information is analyzed in the frequency domain, and the frequency feature changes and energy changes in the echo information are extracted to obtain the frequency domain analysis results. The frequency domain features can reveal the abnormal changes in the frequency distribution in the echo signal and the offset of the signal energy, which further helps to identify the subtle defects of the inner wall of the crystallizer copper tube. These frequency domain features can indicate the type and severity of the defects in different frequency ranges. Finally, the time domain analysis results and the frequency domain analysis results are compared with the preset internal defect thresholds. By setting a reasonable threshold, it is possible to determine whether there are defects on the inner wall of the crystallizer copper tube.

[0012] In a preferred example, the present application may be further configured as follows: based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain overall quality status information, including: According to the surface defect information and the internal defect information, combined with the preset quality assessment standard, the overall quality status of the crystallizer copper tube is assessed to confirm the overall quality status information.

[0013] By adopting the above technical solution, based on the surface defect information and internal defect information, combined with the preset quality assessment standards, it is possible to accurately judge whether the crystallizer copper tube meets the use requirements and obtain the overall quality status information. This quality assessment result can clearly reflect the risks that may exist in the actual application of the crystallizer copper tube, which is convenient for subsequent decision-making and maintenance. Through the comprehensive analysis of surface and internal defects, possible hidden dangers can be identified in the quality status assessment of the crystallizer copper tube, and a scientific basis can be provided for subsequent use and maintenance, ensuring the long-term stability and safety of the crystallizer copper tube.

[0014] In a preferred example, the present application may be further configured as follows: the overall quality status information is input into a quality assessment model, and the quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a crystallizer copper tube quality score, including: The quality score of the mold copper tube is obtained by the following formula: Wherein, Q is the quality score of the mold copper tube, n is the number of defect types evaluated, and W is i is the weight coefficient of the i-th defect type, the F i is the influencing factor corresponding to the i-th defect type, the α iis the dynamic adjustment coefficient of the defect type, m is the number of additional influencing factors, and P j is the potential influence coefficient of the jth environmental factor on the crystallizer copper tube, and β is the adjustment coefficient of the environmental factor.

[0015] By adopting the above technical solution, the quality score of the mold copper tube can be accurately calculated according to the defect type, defect influencing factors and environmental factors of the mold copper tube. i 、Influencing factors F i , Dynamic adjustment coefficient α i The scoring system not only takes into account the impact of different defect types, but also can be dynamically adjusted according to actual environmental conditions, thus providing a more scientific and accurate basis for the risk assessment and subsequent maintenance of the mold copper tube. In addition, the adjustment coefficient β of environmental factors and the additional influencing factor P j The introduction of further improves the comprehensiveness and reliability of quality assessment and ensures the long-term stability and safety of the crystallizer copper tube in the actual working environment.

[0016] In a preferred example, the present application can be further configured as follows: determining the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and generating maintenance suggestions and preventive measures suggestions corresponding to the use risk level based on the use risk level, including: The quality score of the crystallizer copper tube is compared with the preset risk level standard score. If the quality score of the crystallizer copper tube is greater than or equal to the preset risk level standard score, the use risk level is marked as a low risk level; if the quality score of the crystallizer copper tube is less than the preset risk level standard score, the use risk level is marked as a high risk level; According to the usage risk level, the maintenance suggestion and the preventive measure suggestion corresponding to the usage risk level are generated.

[0017] By adopting the above technical solution, the quality score of the crystallizer copper tube can be compared with the preset risk level standard to accurately determine the use risk level of the crystallizer copper tube, so as to avoid potential safety hazards caused by inaccurate quality assessment. Secondly, by comparing the quality score of the crystallizer copper tube with the risk level standard and setting low-risk and high-risk levels, not only the accuracy of the quality assessment is improved, but also the high-risk crystallizer copper tube can be identified and handled preferentially, and timely measures can be taken to avoid failures; in addition, based on the use risk level of the crystallizer copper tube, matching maintenance suggestions and preventive measures are generated, which can help maintenance personnel accurately formulate targeted maintenance plans.

[0018] The second object of the invention is achieved by the following technical solutions: A crystallizer copper tube quality detection and maintenance device, the crystallizer copper tube quality detection and maintenance device comprising: A geometric structure information acquisition and three-dimensional modeling module is used to acquire geometric structure information of the copper tube of the crystallizer, and process the geometric structure information through three-dimensional imaging technology to obtain a three-dimensional structure model; An outer wall defect automatic detection module is used to obtain outer wall image information from the three-dimensional structure model, and perform automatic defect detection on the outer wall image information of the crystallizer copper tube through a CNN model to obtain surface defect information; An inner wall nondestructive testing module is used to obtain inner wall image information from the three-dimensional structure model, and perform nondestructive testing on the inner wall image information of the crystallizer copper tube by ultrasonic technology to obtain internal defect information; A quality status assessment module, used to assess the quality status of the mold copper tube based on the surface defect information and the internal defect information to obtain overall quality status information; A quality scoring and assessment module, used for inputting the overall quality status information into a quality assessment model, wherein the quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a crystallizer copper tube quality score; The use risk level and maintenance suggestion generation module is used to determine the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and based on the use risk level, generate maintenance suggestions and preventive measures suggestions corresponding to the use risk level.

[0019] By adopting the above technical scheme, the complete geometric structure information of the crystallizer copper tube can be obtained through precise three-dimensional imaging technology, which reduces the influence of traditional manual measurement errors and provides high-precision basic data for subsequent defect detection and quality assessment, thereby improving the accuracy and reliability of detection. The CNN model is used to efficiently identify various surface defects on the outer wall of the crystallizer copper tube, avoiding the subjectivity and labor intensity of manual detection, thereby improving the accuracy and speed of defect identification and reducing the risk of human error. The use of ultrasonic technology to accurately obtain internal defect information will not cause any damage to the crystallizer copper tube, thereby ensuring the integrity of the pipeline and avoiding unnecessary risks that may be caused by traditional destructive testing. The overall quality status of the crystallizer copper tube is evaluated based on comprehensive defect data, avoiding the evaluation method that relies only on a single defect type, thereby providing more accurate quality assessment results and ensuring the comprehensiveness and scientificity of the evaluation results. The overall quality of the crystallizer copper tube can be scientifically evaluated through the preset quality scoring standard. Combined with the calculation results of the quality assessment model, the quality score of the crystallizer copper tube can be quickly obtained, ensuring the objectivity and systematicness of the quality assessment process, which helps to accurately judge whether the crystallizer copper tube meets the use requirements. The risk level of the crystallizer copper tube is automatically determined according to the quality score of the crystallizer copper tube, and targeted maintenance suggestions and preventive measures are generated according to different risk levels, ensuring the long-term safe operation of the equipment, reducing the risk of sudden failures, and improving the efficiency and pertinence of maintenance work.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned crystallizer copper tube quality detection and maintenance method when executing the computer program.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned crystallizer copper tube quality detection and maintenance method.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. The complete geometric structure information of the mold copper tube can be obtained through precise three-dimensional imaging technology, which reduces the influence of traditional manual measurement errors and provides high-precision basic data for subsequent defect detection and quality assessment, thereby improving the accuracy and reliability of detection. The CNN model is used to efficiently identify various surface defects on the outer wall of the mold copper tube, avoiding the subjectivity and labor intensity of manual detection, thereby improving the accuracy and speed of defect identification and reducing the risk of human error. The use of ultrasonic technology to accurately obtain internal defect information will not cause any damage to the mold copper tube, thereby ensuring the integrity of the pipeline and avoiding unnecessary risks that may be caused by traditional destructive testing. The overall quality status of the mold copper tube is evaluated based on comprehensive defect data, avoiding the evaluation method that relies only on a single defect type, thereby providing more accurate quality assessment results and ensuring the comprehensiveness and scientificity of the evaluation results. The overall quality of the mold copper tube can be scientifically evaluated through the preset quality scoring standard. Combined with the calculation results of the quality assessment model, the quality score of the mold copper tube can be quickly obtained, ensuring the objectivity and systematicness of the quality assessment process, which helps to accurately judge whether the mold copper tube meets the use requirements. Automatically determine the risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and generate targeted maintenance suggestions and preventive measures according to different risk levels, ensuring the long-term safe operation of the equipment, reducing the risk of sudden failures, and improving the efficiency and pertinence of maintenance work; 2. It can accurately calculate the quality score of the mold copper tube according to the defect type, defect influencing factors and environmental factors of the mold copper tube. The various parameters in the formula (such as defect weight coefficient Wi, influencing factor Fi, dynamic adjustment coefficient αi, etc.) can fully reflect the severity of surface and internal defects of the mold copper tube, and accurately assess the quality level of the mold copper tube in combination with the external environmental influence. This scoring system not only takes into account the impact of different defect types, but also can be dynamically adjusted according to actual environmental conditions, thereby providing a more scientific and accurate basis for the use risk assessment and subsequent maintenance of the mold copper tube. In addition, the introduction of the adjustment coefficient β of environmental factors and the additional influencing factor Pj further enhances the comprehensiveness and reliability of the quality assessment, ensuring the long-term stability and safety of the mold copper tube in the actual working environment; 3. Based on the comparison between the quality score of the crystallizer copper tube and the preset risk level standard, the use risk level of the crystallizer copper tube can be accurately determined, so as to avoid potential safety hazards caused by inaccurate quality assessment. Secondly, by comparing the quality score of the crystallizer copper tube with the risk level standard and setting low-risk and high-risk levels, not only the accuracy of the quality assessment is improved, but also the high-risk crystallizer copper tube can be identified and handled preferentially, and timely measures can be taken to avoid failures; in addition, based on the use risk level of the crystallizer copper tube, matching maintenance recommendations and preventive measures are generated, which can help maintenance personnel accurately formulate targeted maintenance plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a method for quality inspection and maintenance of a crystallizer copper tube in one embodiment of the present application; Figure 2 It is a flowchart for implementing step S20 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 3 It is a flowchart for implementing step S30 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 4 It is a flowchart for implementing step S302 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 5 It is a flowchart for implementing step S40 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 6 It is a flowchart for implementing step S50 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 7 It is a flowchart for implementing step S60 in the method for quality inspection and maintenance of the crystallizer copper tube in one embodiment of the present application; Figure 8 This is a principle block diagram of a crystallizer copper tube quality detection and maintenance device in one embodiment of the present application; Fig. 9 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a method for quality inspection and maintenance of a crystallizer copper tube, which specifically includes the following steps: S10: obtaining geometric structure information of the copper tube of the crystallizer, processing the geometric structure information by three-dimensional imaging technology, and obtaining a three-dimensional structure model.

[0026] Specifically, the crystallizer copper tube is scanned by laser scanning or optical three-dimensional imaging technology to obtain geometric structure information of the crystallizer copper tube, and the acquired data includes but is not limited to the three-dimensional space coordinate information of the crystallizer copper tube, such as the outer dimensions, surface contour, and curvature change. These three-dimensional space coordinate information are processed and calculated by dedicated three-dimensional modeling software to generate a highly accurate three-dimensional structure model, which includes detailed geometric features of the surface and inner wall of the crystallizer copper tube.

[0027] S20: Obtain outer wall image information from the three-dimensional structure model, perform automatic defect detection on the outer wall image information of the crystallizer copper tube through the CNN model, and obtain surface defect information.

[0028] Specifically, the outer wall image of the crystallizer copper tube is first preprocessed. The preprocessing includes steps such as grayscale, denoising, brightness and contrast enhancement of the image. The purpose is to improve the quality of the image and make the defects more obvious. Then, the preprocessed image is input into the convolutional neural network (CNN). CNN automatically extracts low-level features (such as edges, textures, color changes, etc.) and high-level features (such as shape, surface irregularities, etc.) in the image through multi-layer convolution operations. These features are the key to identifying defects. After the convolution layer, the network performs feature dimensionality reduction through the pooling layer, retains the most recognizable information, reduces the amount of calculation, and improves the model's sensitivity to details. Then, the fully connected layer is used to map the extracted features to the defect category space, and the defects are classified into different types (such as cracks, dents, corrosion, etc.) through the Softmax or Sigmoid function, thereby generating specific surface defect information.

[0029] S30: Acquire inner wall image information from the three-dimensional structure model, perform nondestructive testing on the inner wall image information of the crystallizer copper tube by ultrasonic technology, and obtain internal defect information.

[0030] Specifically, ultrasonic detection technology is used to transmit high-frequency sound wave signals to the inner wall of the copper tube of the crystallizer through an ultrasonic probe. During the propagation of the sound wave on the inner wall, it will be reflected or scattered by internal defects, generating echo signals. These echo signals are received by sensors and converted into electronic signals, and then further processed using time-frequency domain analysis methods. First, the echo signal is preprocessed to remove noise, and the time delay and frequency characteristics of the signal are extracted by time-frequency analysis methods, and then the inner wall of the copper tube of the crystallizer is analyzed to see if there are defects such as cracks, cavities, corrosion, etc., and finally internal defect information is generated.

[0031] S40: Based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain the overall quality status information.

[0032] Specifically, the defect information obtained from surface defect detection and inner wall non-destructive testing is comprehensively analyzed, and a multi-dimensional evaluation method is used to compare the defect type, size, distribution and other information with the preset quality standards, and the overall quality score is calculated through a weighted algorithm. Combined with the working conditions of the crystallizer copper tube, such as working pressure, temperature and other factors, these data are used as evaluation parameters for comprehensive judgment, and the overall quality status of the crystallizer copper tube is finally obtained.

[0033] S50: The overall quality status information is input into the quality assessment model. The quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a quality score of the crystallizer copper tube.

[0034] Specifically, by inputting various types of data extracted from surface defect information, internal defect information and quality assessment standards into the quality assessment model, the model quantitatively evaluates the quality of the crystallizer copper tube according to the preset scoring standards. The quality scoring standard takes into account factors such as the severity of various defects, the geometric dimensions of the crystallizer copper tube, and historical usage. On this basis, a weighted scoring method is used to calculate the comprehensive quality score of the crystallizer copper tube. Each defect type corresponds to a weight coefficient, and the size and location of the defect affect the score. By calculating the weighted sum of all defects, the quality score of the crystallizer copper tube is finally obtained. S60: Determine the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and generate maintenance suggestions and preventive measures suggestions corresponding to the use risk level based on the use risk level.

[0035] Specifically, the quality score of the crystallizer copper tube is compared with the preset risk level standard. If the quality score is higher than or equal to the risk level standard score, the crystallizer copper tube is judged to be at a low risk level, otherwise it is judged to be at a high risk level. According to different risk levels, corresponding maintenance and preventive measures are automatically generated. For example, if it is assessed as a high risk level, it is recommended to carry out maintenance measures such as regular inspection, replacement or reinforcement, and provide targeted preventive measures such as reducing operating pressure and increasing external support according to the use environment and potential risk factors of the crystallizer copper tube. If it is assessed as a low risk level, it may be recommended to extend the use cycle or implement routine maintenance inspections to ensure the long-term stable operation of the crystallizer copper tube.

[0036] In one embodiment, if Figure 2 As shown, in step S20, the outer wall image information is obtained from the three-dimensional structure model, and the outer wall image information of the crystallizer copper tube is automatically inspected by the CNN model to obtain surface defect information, including: S201: Perform image preprocessing on the outer wall image information to obtain preprocessed outer wall image information.

[0037] Specifically, after obtaining the outer wall image information, the image is first denoised, and common image processing algorithms such as Gaussian filtering or median filtering are used to remove the noise generated during the imaging process. Then the image is grayed, and the color image is converted into a grayscale image to facilitate subsequent feature extraction and analysis. Subsequently, image enhancement is performed, and methods such as histogram equalization are used to improve the image contrast to ensure that the defects in the image are more visually obvious. In addition, edge detection may also be performed, such as using the Canny edge detection algorithm to highlight the details and contours in the image to improve the accuracy of subsequent defect detection. After these processes, the pre-processed outer wall image information is obtained.

[0038] S202: Perform feature extraction and automatic analysis on the preprocessed outer wall image information through the CNN model, identify and classify surface defects in the preprocessed outer wall image information, and obtain surface defect information.

[0039] Specifically, the preprocessed outer wall image is input into the convolutional neural network (CNN) model. The CNN model first extracts features from the image through multiple convolutional layers, extracts low-level features such as texture, shape, edge, corner points, etc., and further reduces the size of the image through the pooling layer, thereby reducing the computational complexity and extracting more abstract high-level features. Then, these features are integrated through the fully connected layer, and the features are nonlinearly transformed through the activation function to achieve automatic analysis of the image. The CNN model can automatically identify surface defects in the image, such as cracks, scratches, dents, corrosion, etc., based on the defect features learned during training, and classify these defects. Finally, the model outputs the type, location, and severity of the surface defects as surface defect information.

[0040] In one embodiment, if Figure 3 As shown, in step S30, the inner wall image information is obtained from the three-dimensional structure model, and the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain internal defect information, including: S301: the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain inner wall echo information.

[0041] Specifically, an ultrasonic probe is first used to scan the inner wall of the crystallizer copper tube, emitting an ultrasonic signal to the inner wall, and receiving an echo signal reflected from the inner wall. This process is implemented through the principle of non-destructive detection, and can effectively detect potential defects in the inner wall of the crystallizer copper tube without disassembling or damaging the crystallizer copper tube. The time delay and intensity of the echo signal can reflect the density, structure and whether there are defects in the inner wall. For example, if there are cracks or holes in the inner wall, the echo signal will change, and the reflection time and intensity will be abnormal. During the detection process, ultrasonic waves of different frequencies are used to adapt to different types of defects and improve the detection accuracy. High-frequency ultrasonic waves can detect small defects more carefully, while low frequencies are suitable for detecting larger-scale defects. Through this process, echo information reflecting the state of the inner wall of the crystallizer copper tube is finally obtained.

[0042] S302: Analyze the inner wall echo information based on the time-frequency domain analysis method to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating internal defect information.

[0043] Specifically, first, the echo information is analyzed in the time domain to extract the time delay information of the echo signal, so as to obtain the propagation time and reflection intensity of the echo. By analyzing the change in time delay, the uniformity of the inner wall material and whether there are defects such as cracks and voids can be inferred. For example, if the time delay of the echo is long, it may indicate that there are large defects in the inner wall, such as pores or cracks. Subsequently, the echo signal is Fourier transformed using frequency domain analysis to extract the frequency characteristics of the echo signal, such as the frequency response and amplitude characteristics of the signal. Frequency domain characteristics can help determine the type and size of inner wall defects. For example, different types of defects will produce different characteristic peaks in the spectrum. Combining the analysis results of the time domain and frequency domain, it is possible to more accurately identify and determine whether there are defects on the inner wall of the crystallizer copper tube. Finally, based on these analysis results, the corresponding internal defect information is generated, including the location and size of the defects.

[0044] In one embodiment, if Figure 4 As shown, in step S302, the inner wall echo information is analyzed based on the time-frequency domain analysis method to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating internal defect information, including: S3021: Perform time domain analysis on the inner wall echo information, extract the delay change and amplitude change of the inner wall echo information, and obtain the time domain analysis result.

[0045] Specifically, firstly, the acquired inner wall echo information is collected and preprocessed in the time domain to ensure the clarity and accuracy of the echo signal. In the time domain analysis process, the time delay of the echo signal (i.e., the time from the emission signal to the reception of the echo) and the change in amplitude are analyzed. The time delay reflects the distance that the sound wave propagates in the copper tube of the crystallizer, while the amplitude change reflects the intensity of the reflected echo. Usually, an echo with lower intensity may indicate a defective area. By calculating the time delay change of the echo signal, the depth and nature of the obstacles or defects encountered by the reflected signal can be inferred. For the amplitude change, different types of defects such as cracks, holes or foreign body inclusions can be detected by calculating the difference in echo intensity.

[0046] S3022: Perform frequency domain analysis on the inner wall echo information, extract the frequency characteristic changes and energy changes of the inner wall echo information, and obtain the frequency domain analysis results.

[0047] Specifically, the echo signal is analyzed in the frequency domain using Fourier transform, and the time domain signal is converted into the frequency domain signal to extract the frequency characteristics and energy distribution in the echo information. In the frequency domain analysis process, the main focus is on the frequency components and change patterns of the signal, especially the peak value and bandwidth in the spectrum. The defect location usually appears as a specific frequency change or energy concentration area in the spectrum. For example, a crack may cause the echo signal to concentrate energy at a certain frequency. By comparing the frequency characteristics and energy fluctuations of different signals, the type and characteristics of the defect can be further identified. For example, the change in the frequency component can be used to determine whether the defect affects the integrity of the inner wall.

[0048] S3023: The time domain analysis results and the frequency domain analysis results are respectively compared with the preset internal defect thresholds to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating internal defect information.

[0049] In this embodiment, the preset internal defect threshold refers to the preset time domain threshold and Specifically, the time delay change and amplitude change of the inner wall echo information are obtained through time domain analysis. The time delay change reflects the propagation time of the sound wave on the inner wall of the crystallizer copper tube, while the amplitude change reflects the change in the intensity of the echo signal. The frequency characteristic change and energy change of the inner wall echo information are extracted through frequency domain analysis. The frequency change may reflect the surface or structural change of the inner wall, while the energy change can indicate whether there are defects such as cracks or corrosion. Next, the time delay change in the time domain analysis result is compared with the set threshold. If the time delay change is greater than the preset internal defect threshold, it may indicate that there is an abnormality in the inner wall, such as pores or cracks. Similarly, if the amplitude change exceeds the threshold, it may indicate that the echo signal reflection is abnormal, usually due to the change in signal intensity caused by the inner wall defect. Next, the frequency domain analysis is compared to compare the change in frequency characteristics with the preset threshold range. If the frequency exceeds the normal range, it may indicate that the inner wall surface or structure has changed. If the energy change also exceeds the set threshold, it means that there may be a large defect, such as a penetrating crack or severe corrosion. In addition, the thresholds are set based on empirical values ​​obtained through experimental data or standard literature. These thresholds reflect the characteristics of the echo signal under normal circumstances. Any changes beyond these thresholds may mean the presence of defects. By comparing the time domain and frequency domain analysis results one by one, if both show anomalies exceeding the threshold, it is determined that there is a defect on the inner wall of the crystallizer copper tube. If only one analysis result exceeds the threshold, combined with the specific situation, it may mean that the defect is not obvious or has a small impact. Finally, based on the comparison results, internal defect information is generated, recording the type, location, size and possible impact area of ​​the defect, and providing it to subsequent quality assessment and risk determination for further processing.

[0050] In one embodiment, if Figure 5 As shown, in step S40, the quality status of the mold copper tube is evaluated based on the surface defect information and the internal defect information to obtain the overall quality status information, including: S401: Based on the surface defect information and the internal defect information, combined with the preset quality assessment standard, the overall quality status of the crystallizer copper tube is assessed to confirm the overall quality status information.

[0051] Specifically, first, the surface defect information and internal defect information are combined to obtain the overall defect status of the crystallizer copper tube. Combined with the preset quality assessment criteria, the impact of the defects is weighted or comprehensively determined. The quality assessment criteria involve factors such as the type, size, quantity, and location of the defects, where each factor is weighted according to its impact on the overall quality. Finally, based on the combined defect information, a quality assessment result is generated, which can be used to determine whether the crystallizer copper tube meets the preset quality requirements, thereby confirming the overall quality status information.

[0052] In one embodiment, if Figure 6As shown, in step S50, the overall quality status information is input into the quality assessment model. The quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on the preset quality scoring standard to obtain the crystallizer copper tube quality score, including: The quality score of the mold copper tube is obtained by the following formula: Where Q is the quality score of the mold copper tube, n is the number of defect types evaluated, and W i is the weight coefficient of the i-th defect type, F i is the influencing factor corresponding to the i-th defect type, α i is the dynamic adjustment coefficient of the defect type, m is the number of additional influencing factors, P j is the potential influence coefficient of the jth environmental factor on the crystallizer copper tube, and β is the adjustment coefficient of the environmental factor.

[0053] Specifically, first, for each defect type i (such as cracks, corrosion, deformation, etc.), the influencing factor Fi is calculated. This is usually done by analyzing the area, depth, location, and other factors of the defect to quantify the degree of influence of the defect on the overall structure of the crystallizer copper tube. Then, a weight coefficient W is assigned according to the influence of the defect type. i , which indicates the importance of the defect type in quality assessment. For example, if the appearance of a crack may lead to more serious structural failure, a higher weight will be given to the crack. Then, in order to improve the accuracy of the assessment, the impact of each defect type will be adjusted by a dynamic adjustment coefficient α i Correction. This adjustment factor reflects the changing impact of defects on the quality score under specific environmental, usage conditions or time factors. For example, if the crystallizer copper tube works at a higher temperature, some types of defects may expand faster, so it is necessary to appropriately increase the impact coefficient of the corresponding defect type. At the same time, it is also necessary to consider external environmental factors such as temperature, humidity, pressure, etc. These factors will have a potential impact on the corrosion and wear of the crystallizer copper tube. These environmental factors are expressed through the potential impact coefficient P j To quantify, and further correct by the environmental adjustment factor β. For example, in a high humidity environment, corrosion defects may become more serious, so the adjustment factor for environmental factors needs to be appropriately adjusted according to the specific conditions of the environment. Finally, through a comprehensive analysis of all defect types, additional influencing factors and environmental factors, the quality score Q of the crystallizer copper tube is obtained.

[0054] In one embodiment, if Figure 7 As shown, in step S60, the use risk level of the crystallizer copper tube is determined according to the quality score of the crystallizer copper tube, and based on the use risk level, maintenance suggestions and preventive measures suggestions corresponding to the use risk level are generated, including: S601: Compare the quality score of the crystallizer copper tube with the preset risk level standard score. If the quality score of the crystallizer copper tube is greater than or equal to the preset risk level standard score, the risk level used will be marked as a low risk level. If the quality score of the crystallizer copper tube is less than the preset risk level standard score, the risk level used will be marked as a high risk level.

[0055] Specifically, the quality score of the crystallizer copper tube is first compared with the preset risk level standard score, which is usually formulated based on industry standards, empirical data or the use requirements of the crystallizer copper tube. If the quality score of the crystallizer copper tube is greater than or equal to the preset standard score, it indicates that the quality of the crystallizer copper tube is within an acceptable range and is therefore marked as a low risk level. If the quality score of the crystallizer copper tube is less than the preset standard score, it indicates that the crystallizer copper tube has major defects or damage and the quality does not meet the standard requirements, so the crystallizer copper tube is marked as a high risk level. For example, if the preset risk level standard score is 7.0 and the quality score of the crystallizer copper tube is 6.5, the risk level is a high risk level. Conversely, if the quality score of the crystallizer copper tube is 7.2, the risk level is a low risk level.

[0056] S602: Generate maintenance suggestions and preventive measures suggestions corresponding to the use risk level according to the use risk level.

[0057] Specifically, if the crystallizer copper tube is marked as a low-risk level, maintenance recommendations may include regular inspections and routine maintenance to ensure the long-term and stable operation of the crystallizer copper tube, such as checking for surface defects every 6 months and making necessary environmental adaptability adjustments when the working environment conditions change. For crystallizer copper tubes with high-risk levels, maintenance recommendations need to be more stringent, and may include recommendations for repair or replacement as soon as possible to prevent serious failure or damage to the crystallizer copper tube during use. In addition, preventive measures recommendations will also be adjusted accordingly. For example, if the crystallizer copper tube is affected by corrosion due to environmental factors (such as high temperature and humidity), it is recommended to increase anti-corrosion protection measures, install temperature and humidity control equipment, or perform special coating treatment on the crystallizer copper tube, etc., to ensure the safety and reliability of the crystallizer copper tube in actual use.

[0058] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0059] In one embodiment, a crystallizer copper tube quality detection and maintenance device is provided, and the crystallizer copper tube quality detection and maintenance device corresponds to the crystallizer copper tube quality detection and maintenance method in the above embodiment. Figure 8As shown, the crystallizer copper tube quality inspection and maintenance device includes a geometric structure information acquisition and three-dimensional modeling module, an outer wall defect automatic detection module, an inner wall non-destructive detection module, a quality status assessment module, a quality scoring and evaluation module, and a use risk level and maintenance suggestion generation module. The functional modules are described in detail as follows: The geometric structure information acquisition and three-dimensional modeling module is used to obtain the geometric structure information of the crystallizer copper tube, process the geometric structure information through three-dimensional imaging technology, and obtain a three-dimensional structure model; The outer wall defect automatic detection module is used to obtain the outer wall image information from the three-dimensional structure model, and perform automatic defect detection on the outer wall image information of the crystallizer copper tube through the CNN model to obtain surface defect information; The inner wall nondestructive testing module is used to obtain the inner wall image information from the three-dimensional structure model, and perform nondestructive testing on the inner wall image information of the crystallizer copper tube through ultrasonic technology to obtain internal defect information; The quality status assessment module is used to assess the quality status of the mold copper tube based on surface defect information and internal defect information to obtain overall quality status information; The quality scoring and assessment module is used to input the overall quality status information into the quality assessment model. The quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on the preset quality scoring standard to obtain the crystallizer copper tube quality score; The use risk level and maintenance suggestion generation module is used to determine the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and based on the use risk level, generate maintenance suggestions and preventive measures suggestions corresponding to the use risk level.

[0060] Optional, automatic detection module for outer wall defects includes: The outer wall image preprocessing submodule is used to perform image preprocessing on the outer wall image information to obtain the preprocessed outer wall image information; The outer wall defect recognition and classification submodule is used to extract features and automatically analyze the preprocessed outer wall image information through the CNN model, recognize and classify surface defects in the preprocessed outer wall image information, and obtain surface defect information.

[0061] Optional, internal wall non-destructive testing module includes: The inner wall nondestructive detection submodule is used to perform nondestructive detection on the inner wall image information of the crystallizer copper tube through ultrasonic technology to obtain the inner wall echo information; The echo analysis and defect judgment submodule is used to analyze the inner wall echo information based on the time-frequency domain analysis method to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating internal defect information.

[0062] Optional echo analysis and defect judgment submodules include: A time domain analysis unit is used to perform time domain analysis on the inner wall echo information, extract the time delay change and amplitude change of the inner wall echo information, and obtain the time domain analysis result; A frequency domain analysis unit is used to perform frequency domain analysis on the inner wall echo information, extract the frequency characteristic change and energy change of the inner wall echo information, and obtain the frequency domain analysis result; The defect determination and comparison unit is used to compare the time domain analysis results and the frequency domain analysis results with the preset internal defect thresholds respectively to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating internal defect information.

[0063] Optional, quality status assessment modules include: The quality assessment submodule is used to assess the overall quality status of the mold copper tube and confirm the overall quality status information based on the surface defect information and internal defect information combined with the preset quality assessment standards.

[0064] Optional quality scoring and rating modules include: The scoring confirmation submodule is used to obtain the quality score of the mold copper tube through the following formula: Where Q is the quality score of the mold copper tube, n is the number of defect types evaluated, and W i is the weight coefficient of the i-th defect type, F i is the influencing factor corresponding to the i-th defect type, αi is the dynamic adjustment coefficient of the defect type, m is the number of additional influencing factors, Pj is the potential influence coefficient of the j-th environmental factor on the crystallizer copper tube, and β is the adjustment coefficient of the environmental factor.

[0065] Optionally, use the risk level and maintenance suggestion generation module including: The risk level determination submodule is used to compare the quality score of the mold copper tube with the preset risk level standard score. If the quality score of the mold copper tube is greater than or equal to the preset risk level standard score, the risk level used is marked as a low risk level; if the quality score of the mold copper tube is less than the preset risk level standard score, the risk level used is marked as a high risk level; The maintenance and prevention suggestion generation submodule is used to generate maintenance suggestions and prevention measures suggestions corresponding to the use risk level according to the use risk level.

[0066] The specific definition of the crystallizer copper tube quality detection and maintenance device can be found in the above definition of the crystallizer copper tube quality detection and maintenance method, which will not be repeated here. Each module in the above-mentioned crystallizer copper tube quality detection and maintenance device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0067] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for quality detection and maintenance of a crystallizer copper tube is implemented.

[0068] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Obtaining geometric structure information of the copper tube of the crystallizer, processing the geometric structure information through three-dimensional imaging technology, and obtaining a three-dimensional structure model; The outer wall image information is obtained from the three-dimensional structure model, and the outer wall image information of the crystallizer copper tube is automatically inspected through the CNN model to obtain the surface defect information; The inner wall image information is obtained from the three-dimensional structure model, and the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain the internal defect information; Based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain the overall quality status information; the overall quality status information is input into the quality assessment model, and the quality assessment model evaluates the comprehensive quality of the crystallizer copper tube based on the preset quality scoring standard to obtain the crystallizer copper tube quality score; According to the quality score of the crystallizer copper tube, the use risk level of the crystallizer copper tube is determined, and based on the use risk level, maintenance suggestions and preventive measures suggestions corresponding to the use risk level are generated.

[0069] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtaining geometric structure information of the copper tube of the crystallizer, processing the geometric structure information through three-dimensional imaging technology, and obtaining a three-dimensional structure model; The outer wall image information is obtained from the three-dimensional structure model, and the outer wall image information of the crystallizer copper tube is automatically inspected through the CNN model to obtain the surface defect information; The inner wall image information is obtained from the three-dimensional structure model, and the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain the internal defect information; Based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain the overall quality status information; the overall quality status information is input into the quality assessment model, and the quality assessment model evaluates the comprehensive quality of the crystallizer copper tube based on the preset quality scoring standard to obtain the crystallizer copper tube quality score; According to the quality score of the crystallizer copper tube, the use risk level of the crystallizer copper tube is determined, and based on the use risk level, maintenance suggestions and preventive measures suggestions corresponding to the use risk level are generated.

[0070] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0071] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0072] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for quality inspection and maintenance of a crystallizer copper tube, characterized in that: The crystallizer copper tube quality detection and maintenance method comprises: Acquiring geometric structure information of the copper tube of the crystallizer, and processing the geometric structure information by three-dimensional imaging technology to obtain a three-dimensional structure model; Acquire outer wall image information from the three-dimensional structure model, and perform automated defect detection on the outer wall image information of the crystallizer copper tube through a CNN model to obtain surface defect information; Acquire inner wall image information from the three-dimensional structure model, and perform nondestructive testing on the inner wall image information of the crystallizer copper tube by ultrasonic technology to obtain internal defect information; Based on the surface defect information and the internal defect information, the quality status of the crystallizer copper tube is evaluated to obtain overall quality status information; The overall quality status information is input into a quality assessment model, and the quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a crystallizer copper tube quality score; According to the quality score of the crystallizer copper tube, the use risk level of the crystallizer copper tube is determined, and based on the use risk level, maintenance suggestions and preventive measures suggestions corresponding to the use risk level are generated.

2. The method for quality inspection and maintenance of the mold copper tube according to claim 1, characterized in that: The outer wall image information is obtained from the three-dimensional structure model, and the outer wall image information of the crystallizer copper tube is automatically defect-detected by a CNN model to obtain surface defect information, including: Performing image preprocessing on the outer wall image information to obtain preprocessed outer wall image information; The CNN model is used to perform feature extraction and automatic analysis on the preprocessed outer wall image information, identify and classify surface defects in the preprocessed outer wall image information, and obtain the surface defect information.

3. The method for quality inspection and maintenance of the crystallizer copper tube according to claim 1, characterized in that: The inner wall image information is obtained from the three-dimensional structure model, and the inner wall image information of the crystallizer copper tube is non-destructively tested by ultrasonic technology to obtain internal defect information, including: Performing nondestructive testing on the inner wall image information of the mold copper tube by using the ultrasonic technology to obtain inner wall echo information; The inner wall echo information is analyzed based on a time-frequency domain analysis method to determine whether there are defects on the inner wall of the crystallizer copper tube, thereby generating the internal defect information.

4. The method for quality inspection and maintenance of the crystallizer copper tube according to claim 3, characterized in that: The method of analyzing the inner wall echo information based on the time-frequency domain analysis method to determine whether there is a defect on the inner wall of the crystallizer copper tube, thereby generating the internal defect information, includes: Performing time domain analysis on the inner wall echo information, extracting the time delay change and amplitude change of the inner wall echo information, and obtaining a time domain analysis result; Performing frequency domain analysis on the inner wall echo information, extracting frequency characteristic changes and energy changes of the inner wall echo information, and obtaining frequency domain analysis results; The time domain analysis result and the frequency domain analysis result are respectively compared with a preset internal defect threshold value to determine whether there is a defect on the inner wall of the crystallizer copper tube, thereby generating the internal defect information.

5. The method for quality inspection and maintenance of the crystallizer copper tube according to claim 1, characterized in that: The method of evaluating the quality status of the mold copper tube based on the surface defect information and the internal defect information to obtain overall quality status information includes: According to the surface defect information and the internal defect information, combined with the preset quality assessment standard, the overall quality status of the crystallizer copper tube is assessed to confirm the overall quality status information.

6. The method for quality inspection and maintenance of the crystallizer copper tube according to claim 1, characterized in that: The overall quality status information is input into a quality assessment model, and the quality assessment model assesses the comprehensive quality of the mold copper tube based on a preset quality scoring standard to obtain a quality score of the mold copper tube, including: The quality score of the mold copper tube is obtained by the following formula: Wherein, Q is the quality score of the mold copper tube, n is the number of defect types evaluated, and W is i is the weight coefficient of the i-th defect type, the F i is the influencing factor corresponding to the i-th defect type, the α i is the dynamic adjustment coefficient of the defect type, m is the number of additional influencing factors, and P j is the potential influence coefficient of the jth environmental factor on the crystallizer copper tube, and β is the adjustment coefficient of the environmental factor.

7. The method for quality inspection and maintenance of the crystallizer copper tube according to claim 1, characterized in that: The method of determining the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and generating maintenance suggestions and preventive measures suggestions corresponding to the use risk level based on the use risk level, includes: The quality score of the crystallizer copper tube is compared with the preset risk level standard score. If the quality score of the crystallizer copper tube is greater than or equal to the preset risk level standard score, the use risk level is marked as a low risk level; if the quality score of the crystallizer copper tube is less than the preset risk level standard score, the use risk level is marked as a high risk level; According to the usage risk level, the maintenance suggestion and the preventive measure suggestion corresponding to the usage risk level are generated.

8. A crystallizer copper tube quality detection and maintenance device, characterized in that: The crystallizer copper tube quality detection and maintenance device comprises: A geometric structure information acquisition and three-dimensional modeling module is used to acquire geometric structure information of the copper tube of the crystallizer, and process the geometric structure information through three-dimensional imaging technology to obtain a three-dimensional structure model; An outer wall defect automatic detection module is used to obtain outer wall image information from the three-dimensional structure model, and perform automatic defect detection on the outer wall image information of the crystallizer copper tube through a CNN model to obtain surface defect information; An inner wall nondestructive testing module is used to obtain inner wall image information from the three-dimensional structure model, and perform nondestructive testing on the inner wall image information of the crystallizer copper tube by ultrasonic technology to obtain internal defect information; A quality status assessment module, used to assess the quality status of the mold copper tube based on the surface defect information and the internal defect information to obtain overall quality status information; A quality scoring and assessment module, used for inputting the overall quality status information into a quality assessment model, wherein the quality assessment model assesses the comprehensive quality of the crystallizer copper tube based on a preset quality scoring standard to obtain a crystallizer copper tube quality score; The use risk level and maintenance suggestion generation module is used to determine the use risk level of the crystallizer copper tube according to the quality score of the crystallizer copper tube, and based on the use risk level, generate maintenance suggestions and preventive measures suggestions corresponding to the use risk level.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the crystallizer copper tube quality detection and maintenance method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for quality inspection and maintenance of the crystallizer copper tube according to any one of claims 1 to 7 are implemented.

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