A nondestructive ultrasonic flaw detection method and system for seamless oil casing

Abstract

The present invention relates to the field of ultrasonic measurement technology, and specifically to a nondestructive ultrasonic flaw detection method and system for seamless oil casing, comprising cleaning pretreatment, coupling agent application, automatic comprehensive scanning, signal reception and pretreatment, intelligent defect analysis, secondary verification of key areas, and result determination and recording; the beneficial effects of the present invention are: simplifying the nondestructive ultrasonic flaw detection process of seamless oil casing, comprising cleaning pretreatment, coupling agent application, automatic comprehensive scanning, signal reception and pretreatment, using intelligent algorithms to automatically analyze ultrasonic signals after pretreatment, focusing on scanning and verification of suspected defective areas, and result determination and recording, and realizing efficient and accurate defect detection through precise setting of detection parameters and intelligent analysis, and automatically generating detection reports, thereby improving detection efficiency and reliability.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic measurement, in particular to a nondestructive ultrasonic flaw detection method and system for seamless oil casing. Background Art

[0002] In the energy industry such as oil and gas, seamless oil casing is a key transportation and pressure-bearing component, and its quality and safety are directly related to the stable operation of the entire production system and the safety of personnel. Traditional seamless oil casing inspection methods often rely on manual visual inspection or destructive testing, which are not only inefficient and costly, but also difficult to fully and accurately detect tiny defects inside the material, such as cracks, inclusions, shrinkage holes, etc.

[0003] With the continuous development of non-destructive testing technology, ultrasonic flaw detection, as a non-contact, non-destructive testing method, has received more and more attention and application in the detection of seamless oil casing due to its high sensitivity, high resolution and wide range of applications. However, the existing ultrasonic flaw detection technology still faces many challenges in practical applications, such as cumbersome testing procedures, difficult to accurately control testing parameters, and data analysis relying on manual experience, which limits the efficiency and accuracy of testing.

[0004] In view of the above problems, it is necessary to develop a more efficient and accurate nondestructive ultrasonic flaw detection method and system for seamless oil casing. By optimizing the detection process, introducing intelligent analysis technology, and accurately setting detection parameters, the automation and accuracy of detection can be improved, while reducing manual intervention and errors to meet the higher requirements of modern industrial production for seamless oil casing quality inspection. Summary of the invention

[0005] The object of the present invention is to provide a nondestructive ultrasonic flaw detection method and system for seamless oil casing to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a nondestructive ultrasonic flaw detection method for seamless oil casing, comprising the following steps:

[0007] S11: Preliminary preparation, cleaning and pre-treating the surface of the seamless oil casing, and setting the detection parameters, wherein the detection parameters include gain, scanning speed and delay time;

[0008] S12: Coupling treatment: apply coupling agent on the surface of seamless oil casing to ensure close contact between the probe and the surface of the oil casing;

[0009] S13: Automated scanning, using an automated device to control the ultrasonic probe to move along a preset scanning path to conduct a comprehensive scan of the interior of the seamless oil casing;

[0010] S14: signal reception and preprocessing, receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal;

[0011] S15: Intelligent analysis, using intelligent algorithms to automatically analyze the pre-processed ultrasonic signals to identify and analyze defects;

[0012] S16: Secondary scanning, focusing on scanning and verifying suspected defect areas to ensure the accuracy of the test results;

[0013] S17: Result determination and recording: Determine whether there are defects inside the seamless oil casing and their severity based on the analysis results, record various parameters, test results and determination basis during the test process, and generate a test report.

[0014] Preferably, the following steps are included in the preliminary preparation:

[0015] S21: Equipment preparation, select an ultrasonic flaw detector suitable for seamless oil casing inspection, calibrate the ultrasonic flaw detector, including the initial setting of gain, scanning speed and delay time parameters, to ensure that the instrument is in the best working condition;

[0016] S22: Seamless oil casing preparation, cleaning the surface of seamless oil casing, removing impurities that may affect ultrasonic propagation, including paint, oxide film and dirt;

[0017] S23: Prepare the testing environment to ensure that it is quiet and free from interference to reduce the impact of external noise on the test results.

[0018] Preferably, when the ultrasonic probe is controlled by an automated device to move along a preset scanning path to conduct a comprehensive scan of the interior of the seamless oil casing, the following steps are included:

[0019] S31: preset a scanning path, and preset a series of scanning paths according to the size, shape and possible defect types of the seamless oil casing, wherein the preset scanning path is a combination of one or more of a linear scanning path, a circular scanning path and a spiral scanning path;

[0020] S32: Comprehensive scanning, controlling the ultrasonic probe to move along the preset scanning path to comprehensively scan the interior of the seamless oil casing;

[0021] S33: Analyze and record the abnormal signal in real time, determine the area where the abnormal signal is generated as a suspected defect area and record it.

[0022] Preferably, when a series of scanning paths are preset according to the size, shape and possible defect types of the seamless oil casing, the following steps are included:

[0023] S41: Geometric modeling: building a three-dimensional geometric model of seamless oil casing based on the CAD drawings of the seamless oil casing and actual measurement data;

[0024] S42: Defect prediction, based on the knowledge of material science and previous inspection experience, predicts the types of defects that may exist in seamless oil casing and their approximate locations;

[0025] S43: path planning, using an algorithm to plan an optimal scanning path on a geometric model, wherein the algorithms used include a path optimization algorithm and a genetic algorithm;

[0026] S44: Simulation verification: verify the preset scanning path through simulation software to find potential problems and optimize the scanning path to improve the accuracy and efficiency of detection.

[0027] Preferably, when using an algorithm to plan the optimal scanning path on a geometric model, an A* algorithm is used for path planning, wherein the principle formula of the A* algorithm is:

[0028] ;

[0029] Among them, g(n) is the actual cost from the starting point to the current node n, and h(n) is the estimated cost from the current node n to the end point.

[0030] Preferably, when receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal, the following steps are included:

[0031] S51: filtering processing, filtering the received electrical signal by low-pass filtering, high-pass filtering and band-pass filtering methods;

[0032] S52: amplification processing, enhancing the amplitude of the electrical signal by amplification processing to facilitate subsequent processing and analysis;

[0033] S53: An algorithm is used to accurately identify and remove noise components in the electrical signal, wherein the principle formula of the algorithm used is:

[0034] ;

[0035] in, is the wavelet coefficient, M is the signal length, is the input signal, is the wavelet function after scaling and translation, j is the scale parameter, and k is the translation parameter;

[0036] S54: Waveform display, which displays the signal waveform after filtering, amplification and noise reduction in real time, making it convenient for operators to observe.

[0037] Preferably, when using an intelligent algorithm to automatically analyze the pre-processed ultrasonic signal to identify and analyze the defects, the following steps are included:

[0038] S61: feature extraction, extracting key features from the preprocessed signal, wherein the extracted key features are used to reflect the characteristics of the internal structure of the seamless oil casing;

[0039] S62: Using machine learning and deep learning algorithms, the extracted features are compared with known defect patterns to identify the type, location, and size of the defect;

[0040] S63: Determine whether there is a defect and its severity based on the output of the algorithm and the set threshold.

[0041] As a preferred method, when using an intelligent algorithm to automatically analyze the pre-processed ultrasonic signal to identify and analyze the defects, the principle formula is:

[0042] ;

[0043] in, is the predicted output, indicating the probability of a defect, is the sigmoid function, which is used to convert linear combinations into probability values. is the weight vector, T represents the transpose operation, x is the feature vector, x contains the key features extracted from the signal, and b is the bias term.

[0044] Preferably, when judging the severity of the defect based on the output of the algorithm and the set threshold, the principle formula used is:

[0045] ;

[0046] in, Represents the severity of the defect, represents the depth of the defect, where , where v is the propagation velocity of ultrasonic waves in seamless oil casing, It is half of the time required for the ultrasonic wave to be transmitted, received and then returned to the defect. α is a constant coefficient. The value of α is determined by the physical properties of the seamless oil casing. is the length of the defect.

[0047] A nondestructive ultrasonic flaw detection system for seamless oil casing, comprising:

[0048] Ultrasonic transmitting and receiving module, responsible for transmitting ultrasonic signals into the seamless oil casing and receiving signals reflected from the inside of the material;

[0049] The data processing and analysis module is responsible for receiving, processing and analyzing the data collected by the ultrasonic flaw detector;

[0050] The control system and operation interface module is responsible for the electrical control and automatic operation of the system, and also provides the operation interface and operation platform;

[0051] The auxiliary and monitoring module is used to monitor each link in the detection process in real time to ensure the stable operation of the system and the accuracy of the detection results.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. The present invention simplifies the nondestructive ultrasonic flaw detection process of seamless oil casing, including cleaning pretreatment, coupling agent application, automatic comprehensive scanning, signal reception and pretreatment, intelligent defect analysis, secondary verification of key areas, and result determination and recording. By accurately setting detection parameters and intelligent analysis, efficient and accurate defect detection is achieved, and detection reports are automatically generated, thereby improving detection efficiency and reliability;

[0054] 2. The present invention simplifies the preset process of scanning paths for seamless oil casing. First, a three-dimensional model of the oil casing is accurately constructed through geometric modeling; then, the defect type is predicted based on material knowledge and detection experience; then, the optimal scanning path is intelligently planned using advanced algorithms; finally, the optimized path is verified through simulation to ensure that the detection is both comprehensive and efficient, significantly improving the accuracy and efficiency of the detection;

[0055] 3. The present invention utilizes the propagation characteristics of ultrasound in seamless oil casing and combines it with precise time measurement to calculate half of the time required for ultrasound to be emitted, encounter a defect and then return to receive, and thereby infers the depth of the defect. At the same time, the length information of the defect is obtained by direct observation or by using image processing technology. Subsequently, these parameters are substituted into a specific calculation formula, in which α is used as a constant coefficient and is set according to the unique physical properties of seamless oil casing, thereby ensuring the accuracy and reliability of the calculation results. It can not only quickly identify defects in seamless oil casing, but also accurately quantify their severity, providing a more detailed and scientific basis for subsequent maintenance decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic flow chart of a nondestructive ultrasonic flaw detection method for seamless oil casing of the present invention;

[0057] Figure 2 The present invention is a schematic structural diagram of a nondestructive ultrasonic flaw detection system for seamless oil casing. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] The present invention provides a technical solution: Figure 1 A nondestructive ultrasonic flaw detection method for seamless oil casing is shown, comprising the following steps:

[0060] S11: Preliminary preparation, cleaning and pre-treating the surface of the seamless oil casing, and setting the detection parameters, wherein the detection parameters include gain, scanning speed and delay time;

[0061] S12: Coupling treatment: apply coupling agent on the surface of seamless oil casing to ensure close contact between the probe and the surface of the oil casing;

[0062] S13: Automated scanning, using an automated device to control the ultrasonic probe to move along a preset scanning path to conduct a comprehensive scan of the interior of the seamless oil casing;

[0063] S14: signal reception and preprocessing, receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal;

[0064] S15: Intelligent analysis, using intelligent algorithms to automatically analyze the pre-processed ultrasonic signals to identify and analyze defects;

[0065] S16: Secondary scanning, focusing on scanning and verifying suspected defect areas to ensure the accuracy of the test results;

[0066] S17: Result determination and recording: Determine whether there are defects inside the seamless oil casing and their severity based on the analysis results, record various parameters, test results and determination basis during the test process, and generate a test report.

[0067] As described in the above steps S11-S17, the present invention simplifies the nondestructive ultrasonic flaw detection process of seamless oil casing, including cleaning pretreatment, coupling agent application, automatic comprehensive scanning, signal reception and preprocessing, intelligent defect analysis, secondary verification of key areas, and result determination and recording. By accurately setting detection parameters and intelligent analysis, efficient and accurate defect detection is achieved, and a detection report is automatically generated, thereby improving detection efficiency and reliability.

[0068] Preferably, the following steps are included in the preliminary preparation:

[0069] S21: Equipment preparation, select an ultrasonic flaw detector suitable for seamless oil casing inspection, calibrate the ultrasonic flaw detector, including the initial setting of gain, scanning speed and delay time parameters, to ensure that the instrument is in the best working condition;

[0070] S22: Seamless oil casing preparation, cleaning the surface of seamless oil casing, removing impurities that may affect ultrasonic propagation, including paint, oxide film and dirt;

[0071] S23: Prepare the testing environment to ensure that it is quiet and free from interference to reduce the impact of external noise on the test results.

[0072] As described in the above steps S21-S23, the present invention carefully selects and calibrates the ultrasonic flaw detector through the equipment preparation in step S21 to ensure that key parameters such as gain, scanning speed and delay time are in the optimal settings, thereby laying a solid foundation for the detection work; in step S22, the surface of the seamless oil casing is thoroughly cleaned to effectively remove impurities such as paint, oxide film and dirt, which may seriously interfere with the propagation of ultrasonic waves and thus affect the detection results; in addition, step S23 emphasizes the preparation of the detection environment to ensure that the environment is quiet and free of external interference, so as to reduce the interference of noise factors on the ultrasonic signal and further improve the detection accuracy; this series of meticulous preliminary preparations together constitute a solid foundation for an efficient and accurate non-destructive ultrasonic flaw detection technical solution.

[0073] Preferably, when the ultrasonic probe is controlled by an automated device to move along a preset scanning path to conduct a comprehensive scan of the interior of the seamless oil casing, the following steps are included:

[0074] S31: preset a scanning path, and preset a series of scanning paths according to the size, shape and possible defect types of the seamless oil casing, wherein the preset scanning path is a combination of one or more of a linear scanning path, a circular scanning path and a spiral scanning path;

[0075] S32: Comprehensive scanning, controlling the ultrasonic probe to move along the preset scanning path to comprehensively scan the interior of the seamless oil casing;

[0076] S33: Analyze and record the abnormal signal in real time, determine the area where the abnormal signal is generated as a suspected defect area and record it.

[0077] As described in the above steps S31-S33, the present invention adopts a refined path planning and real-time signal analysis strategy in the automated scanning stage. First, the scanning path is preset through step S31. According to the unique size, shape and potential defect characteristics of the seamless oil casing, a variety of scanning paths such as straight lines, circles and spirals are flexibly combined to ensure a comprehensive and detailed detection of the interior of the oil casing. Subsequently, in step S32, advanced automation devices are used to accurately control the movement of the ultrasonic probe along the preset path to achieve a complete scanning of the internal structure of the seamless oil casing. The most critical step is step S33, which introduces a real-time signal analysis mechanism to instantly identify and record abnormal signals generated during the scanning process, and quickly lock and mark suspected defect areas. This technical solution not only improves the detection efficiency, but also enhances the accuracy and timeliness of defect identification, providing strong technical support for quality assessment and safety assurance of seamless oil casing.

[0078] Preferably, when a series of scanning paths are preset according to the size, shape and possible defect types of the seamless oil casing, the following steps are included:

[0079] S41: Geometric modeling: building a three-dimensional geometric model of seamless oil casing based on the CAD drawings of the seamless oil casing and actual measurement data;

[0080] S42: Defect prediction, based on the knowledge of material science and previous inspection experience, predicts the types of defects that may exist in seamless oil casing and their approximate locations;

[0081] S43: path planning, using an algorithm to plan an optimal scanning path on a geometric model, wherein the algorithms used include a path optimization algorithm and a genetic algorithm;

[0082] S44: Simulation verification: verify the preset scanning path through simulation software to find potential problems and optimize the scanning path to improve the accuracy and efficiency of detection.

[0083] As described in the above steps S41-S44, the present invention simplifies the preset process of the scanning path of seamless oil casing. First, the three-dimensional model of the oil casing is accurately constructed through geometric modeling; then, the defect type is predicted based on material knowledge and detection experience; then, advanced algorithms are used to intelligently plan the optimal scanning path; finally, the optimized path is verified through simulation to ensure that the detection is both comprehensive and efficient, thereby significantly improving the accuracy and efficiency of the detection.

[0084] Preferably, when using an algorithm to plan the optimal scanning path on a geometric model, an A* algorithm is used for path planning, wherein the principle formula of the A* algorithm is:

[0085] ;

[0086] Among them, g(n) is the actual cost from the starting point to the current node n, and h(n) is the estimated cost from the current node n to the end point.

[0087] As described in the above algorithm, the present invention adopts the A* algorithm, which is famous for its efficient path search capability. Its principle is to evaluate and select the optimal path by comprehensively considering the actual cost g(n) from the starting point to the current node and the estimated cost h(n) from the current node to the end point. The application of this algorithm not only ensures that the scanning path can accurately cover the key areas of the seamless oil casing, but also greatly reduces unnecessary path redundancy, thereby improving the detection efficiency. Through the intelligent planning of the A* algorithm, we can quickly and accurately find the optimal scanning path on a complex geometric model, providing strong technical support for the non-destructive detection of seamless oil casing.

[0088] Preferably, when receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal, the following steps are included:

[0089] S51: filtering processing, filtering the received electrical signal by low-pass filtering, high-pass filtering and band-pass filtering methods;

[0090] S52: amplification processing, enhancing the amplitude of the electrical signal by amplification processing to facilitate subsequent processing and analysis;

[0091] S53: An algorithm is used to accurately identify and remove noise components in the electrical signal, wherein the principle formula of the algorithm used is:

[0092] ;

[0093] in, is the wavelet coefficient, M is the signal length, is the input signal, is the wavelet function after scaling and translation, j is the scale parameter, and k is the translation parameter;

[0094] S54: Waveform display, which displays the signal waveform after filtering, amplification and noise reduction in real time, making it convenient for operators to observe.

[0095] As described in the above steps S51-S54, in the ultrasonic signal preprocessing stage, the present invention adopts steps such as filtering, amplification, denoising and real-time waveform display. We use filtering technology to remove interference, amplify the signal to enhance the signal, use advanced algorithms to accurately denoise, and display the processed waveform in real time to ensure signal quality and improve detection accuracy and efficiency.

[0096] Preferably, when using an intelligent algorithm to automatically analyze the pre-processed ultrasonic signal to identify and analyze the defects, the following steps are included:

[0097] S61: feature extraction, extracting key features from the preprocessed signal, wherein the extracted key features are used to reflect the characteristics of the internal structure of the seamless oil casing;

[0098] S62: Using machine learning and deep learning algorithms, the extracted features are compared with known defect patterns to identify the type, location, and size of the defect;

[0099] S63: Determine whether there is a defect and its severity based on the output of the algorithm and the set threshold.

[0100] As described in the above steps S61-S63, the present invention adopts a set of efficient intelligent algorithm processes in the automated analysis stage of ultrasonic signals. First, through the feature extraction technology in step S61, the key features reflecting the internal structural characteristics of the seamless oil casing are accurately captured from the preprocessed signals. Then, in step S62, advanced machine learning and deep learning algorithms are used to intelligently compare the extracted features with the pre-stored defect pattern library to achieve rapid and accurate identification of the defect type, location and size. Finally, in step S63, based on the output results of the algorithm and the preset threshold standards, a comprehensive judgment is made on whether there are defects inside the seamless oil casing and their severity, providing a reliable basis for subsequent maintenance decisions. This technical solution significantly improves the intelligence level and detection efficiency of defect identification.

[0101] As a preferred method, when using an intelligent algorithm to automatically analyze the pre-processed ultrasonic signal to identify and analyze the defects, the principle formula is:

[0102] ;

[0103] in, is the predicted output, indicating the probability of a defect, is the sigmoid function, which is used to convert linear combinations into probability values. is the weight vector, T represents the transpose operation, x is the feature vector, x contains the key features extracted from the signal, and b is the bias term.

[0104] As described in the above algorithm, the present invention adopts an advanced intelligent algorithm, and its core principle is based on a carefully designed mathematical model. The model achieves accurate evaluation of the internal condition of seamless oil casing by calculating the predicted output, that is, the probability of defects. Among them, the sigmoid function is used as a key conversion tool to cleverly map the linear combination of the feature vector x and the weight vector w into a probability value. This process not only retains the nonlinear characteristics of the data, but also ensures the intuitiveness and interpretability of the output results. The feature vector x brings together various key features extracted from the preprocessed signal. These features comprehensively reflect the subtle changes in the internal structure of the seamless oil casing. The introduction of the bias term b further enhances the flexibility and adaptability of the model, enabling it to more accurately capture different types of defect modes.

[0105] Preferably, when judging the severity of the defect based on the output of the algorithm and the set threshold, the principle formula used is:

[0106] ;

[0107] in, Represents the severity of the defect, represents the depth of the defect, where , where v is the propagation velocity of ultrasonic waves in seamless oil casing, It is half of the time required for the ultrasonic wave to be transmitted, received and then returned to the defect. α is a constant coefficient. The value of α is determined by the physical properties of the seamless oil casing. is the length of the defect.

[0108] As described in the above algorithm, the present invention utilizes the propagation characteristics of ultrasound in seamless oil casing and combines it with precise time measurement to calculate half of the time required for ultrasound to be emitted, encounter a defect and then return to be received, and thereby infers the depth of the defect. At the same time, the length information of the defect is obtained by direct observation or by using image processing technology. Subsequently, these parameters are substituted into a specific calculation formula, in which α is used as a constant coefficient and is set according to the unique physical properties of seamless oil casing, thereby ensuring the accuracy and reliability of the calculation results. It is not only possible to quickly identify defects in seamless oil casing, but also to accurately quantify their severity, providing a more detailed and scientific basis for subsequent maintenance decisions.

[0109] The present invention provides a technical solution: Figure 2 A nondestructive ultrasonic flaw detection system for seamless oil casing is shown, comprising:

[0110] Ultrasonic transmitting and receiving module, responsible for transmitting ultrasonic signals into the seamless oil casing and receiving signals reflected from the inside of the material;

[0111] The data processing and analysis module is responsible for receiving, processing and analyzing the data collected by the ultrasonic flaw detector;

[0112] The control system and operation interface module is responsible for the electrical control and automatic operation of the system, and also provides the operation interface and operation platform;

[0113] The auxiliary and monitoring module is used to monitor each link in the detection process in real time to ensure the stable operation of the system and the accuracy of the detection results.

[0114] Specifically, the system integrates four modules: ultrasonic emission and reception, data processing, automatic control and real-time monitoring. The front end of the system emits ultrasonic waves and receives reflected signals, while the back end intelligently analyzes data and automatically identifies defects. At the same time, the system supports automated operation and real-time monitoring to ensure efficient and accurate detection, providing reliable guarantee for the quality inspection of seamless oil casing.

[0115] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0116] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A nondestructive ultrasonic flaw detection method for seamless oil casing; characterized by: The following steps are involved: S11: Preliminary preparation, cleaning and pre-treating the surface of the seamless oil casing, and setting the detection parameters, wherein the detection parameters include gain, scanning speed and delay time; S12: Coupling treatment: apply coupling agent on the surface of seamless oil casing to ensure close contact between the probe and the surface of the oil casing; S13: Automated scanning, using an automated device to control the ultrasonic probe to move along a preset scanning path to conduct a comprehensive scan of the interior of the seamless oil casing; S14: signal reception and preprocessing, receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal; S15: Intelligent analysis, using intelligent algorithms to automatically analyze the pre-processed ultrasonic signals to identify and analyze defects; S16: Secondary scanning, focusing on scanning and verifying suspected defect areas to ensure the accuracy of the test results; S17: Result determination and recording: determine whether there are defects inside the seamless oil casing and their severity according to the analysis results, record various parameters, test results and determination basis during the test process, and generate a test report; When the ultrasonic probe is controlled by an automated device to move along a preset scanning path to conduct a comprehensive scan of the interior of a seamless oil casing, the following steps are included: S31: preset a scanning path, and preset a series of scanning paths according to the size, shape and possible defect types of the seamless oil casing, wherein the preset scanning path is a combination of one or more of a linear scanning path, a circular scanning path and a spiral scanning path; S32: Comprehensive scanning, controlling the ultrasonic probe to move along the preset scanning path to comprehensively scan the interior of the seamless oil casing; S33: Analyze and record the abnormal signal in real time, determine the area where the abnormal signal is generated as a suspected defect area and record it; When a series of scanning paths are preset according to the size, shape and possible defect types of seamless oil casing, the following steps are included: S41: Geometric modeling: building a three-dimensional geometric model of seamless oil casing based on the CAD drawings of the seamless oil casing and actual measurement data; S42: Defect prediction, based on the knowledge of material science and previous inspection experience, predicts the types of defects that may exist in seamless oil casing and their approximate locations; S43: path planning, using an algorithm to plan an optimal scanning path on a geometric model, wherein the algorithms used include a path optimization algorithm and a genetic algorithm; S44: Simulation verification: verify the preset scanning path through simulation software to find potential problems and optimize the scanning path to improve the accuracy and efficiency of detection.

2. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 1, characterized in that: The following steps are included in the preliminary preparation: S21: Equipment preparation, select an ultrasonic flaw detector suitable for seamless oil casing inspection, calibrate the ultrasonic flaw detector, including the initial setting of gain, scanning speed and delay time parameters, to ensure that the instrument is in the best working condition; S22: Seamless oil casing preparation, cleaning the surface of seamless oil casing, removing impurities that may affect ultrasonic propagation, including paint, oxide film and dirt; S23: Prepare the testing environment to ensure that it is quiet and free from interference to reduce the impact of external noise on the test results.

3. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 2, characterized in that: When using the algorithm to plan the optimal scanning path on the geometric model, the A* algorithm is used for path planning, wherein the principle formula of the A* algorithm is: Among them, g(n) is the actual cost from the starting point to the current node n, and h(n) is the estimated cost from the current node n to the end point.

4. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 3, characterized in that: When receiving the reflected ultrasonic signal and preprocessing the received ultrasonic signal, the following steps are included: S51: filtering processing, filtering the received electrical signal by low-pass filtering, high-pass filtering and band-pass filtering methods; S52: amplification processing, enhancing the amplitude of the electrical signal by amplification processing to facilitate subsequent processing and analysis; S53: An algorithm is used to accurately identify and remove noise components in the electrical signal, wherein the principle formula of the algorithm used is: in, is the wavelet coefficient, M is the signal length, is the input signal, is the wavelet function after scaling and translation, j is the scale parameter, and k is the translation parameter; S54: Waveform display, which displays the signal waveform after filtering, amplification and noise reduction in real time, making it convenient for operators to observe.

5. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 4, characterized in that: When using intelligent algorithms to automatically analyze the pre-processed ultrasonic signals and identify and analyze defects, the following steps are included: S61: feature extraction, extracting key features from the preprocessed signal, wherein the extracted key features are used to reflect the characteristics of the internal structure of the seamless oil casing; S62: Using machine learning and deep learning algorithms, the extracted features are compared with known defect patterns to identify the type, location, and size of the defect; S63: Determine whether there is a defect and its severity based on the output of the algorithm and the set threshold.

6. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 5, characterized in that: When using intelligent algorithms to automatically analyze the pre-processed ultrasonic signals and identify and analyze defects, the principle formula is: in, is the predicted output, indicating the probability of a defect, is the sigmoid function, which is used to convert linear combinations into probability values. is the weight vector, T represents the transpose operation, x is the feature vector, x contains the key features extracted from the signal, and b is the bias term.

7. A nondestructive ultrasonic flaw detection method for seamless oil casing according to claim 6, characterized in that: When judging the severity of a defect based on the output of the algorithm and the set threshold, the principle formula used is: ； in, Represents the severity of the defect, represents the depth of the defect, where , where v is the propagation velocity of ultrasonic waves in seamless oil casing, It is half of the time required for the ultrasonic wave to be transmitted, received and then returned to the defect. α is a constant coefficient. The value of α is determined by the physical properties of the seamless oil casing. is the length of the defect.

8. A nondestructive ultrasonic flaw detection system for seamless oil casing according to claim 7, characterized in that: Ultrasonic transmitting and receiving module, responsible for transmitting ultrasonic signals into the seamless oil casing and receiving signals reflected from the inside of the material; The data processing and analysis module is responsible for receiving, processing and analyzing the data collected by the ultrasonic flaw detector; The control system and operation interface module is responsible for the electrical control and automatic operation of the system, and also provides the operation interface and operation platform; The auxiliary and monitoring module is used to monitor each link in the detection process in real time to ensure the stable operation of the system and the accuracy of the detection results.

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