CN118010847A - Method and system for detecting defects of internal thread pipe blank - Google Patents
Method and system for detecting defects of internal thread pipe blank Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims abstract description 51
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Abstract
The invention relates to the technical field of pipe fitting detection, in particular to a method and a system for detecting defects of an internal thread pipe blank, which can effectively improve the quality detection efficiency and reliability of the internal thread pipe blank and reduce the occurrence risk of potential safety hazards; the method comprises the following steps: based on the design size and structure of the copper pipe blank, dividing the copper pipe blank into sections to obtain a pipe blank section set, wherein the pipe blank section set comprises a first internal thread section, a first straight section, a second straight section and a second internal thread section; respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section set to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section; respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section; and performing risk assessment on the defect type characteristic data of each pipe blank section to obtain defect risk factors of the corresponding pipe blank section.
Description
Technical Field
The invention relates to the technical field of pipe fitting detection, in particular to a method and a system for detecting defects of an internal thread pipe blank.
Background
With the development of industrial production and urban construction, the internal thread copper pipe is widely applied in the fields of air conditioning and refrigeration systems, fluid transportation and the like due to the excellent heat conduction performance and mechanical strength. However, the copper pipe blank may cause internal defects such as cracks, air holes, inclusions, uneven wall thickness and the like due to various factors such as raw material quality, processing condition change and the like in the manufacturing process, and the defects not only directly affect the bearing capacity and service life of the copper pipe, but also may become potential safety hazards under specific conditions. Particularly for an internal thread pipe blank, the internal thread area is easier to generate and hide defects due to complex geometric shape and special stress distribution.
The existing internal thread pipe blank defect detection method mostly adopts ultrasonic waves to carry out integral scanning on the copper pipe blank, and judges whether the pipe blank is qualified or not according to a directly obtained scanning result and a single judgment standard, and different influence degrees of different pipe blank parts on the integral function and safety are not fully considered; for example, even a small or hidden defect, if it occurs in the internally threaded region, it may have a significant impact on the integrity and safety of the whole tubular blank due to the complex structure and stress concentrating characteristics of the region, whereas if the same defect occurs in the straight barrel portion, it may not have a significant impact on the overall performance of the tubular blank due to the laminar flow condition of the portion; therefore, the existing detection method has certain limitations in detection precision and reliability.
Disclosure of Invention
In order to solve the technical problems, the invention provides the internal thread pipe blank defect detection method and the internal thread pipe blank defect detection system which can effectively improve the quality detection efficiency and the reliability of the internal thread pipe blank and reduce the occurrence risk of potential safety hazards.
In a first aspect, the present invention provides a method for detecting defects of an internally threaded tubular blank, the method comprising:
Based on the design size and structure of the copper pipe blank, carrying out paragraph division on the copper pipe blank to obtain a pipe blank paragraph set, wherein the pipe blank paragraph set comprises a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section;
Respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section set to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
Performing risk assessment on the defect type characteristic data of each pipe blank section to obtain defect risk factors of the corresponding pipe blank section;
Traversing a pre-constructed comprehensive influence weight database of pipe blank sections by utilizing the design size and structure of the pipe blank of the copper pipe, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the pipe blank of the copper pipe;
Based on the defect risk factors of all the pipe blank sections and the comprehensive influence weight set of the pipe blank sections, calculating to obtain a defect risk evaluation index of the copper pipe blank;
and comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value, and judging whether the copper pipe blank is qualified or not according to a comparison result.
Further, the first internal thread section is a section occupied by the internal thread length of the input end, the first straight barrel section is used for providing enough distance to enable the fluid to recover the laminar flow state after passing through the internal thread section, the second straight barrel section is a stage of keeping the laminar flow state of the fluid in the copper pipe, and the second internal thread section is a section occupied by the internal thread length of the output end.
Further, the calculation formula of the defect risk evaluation index is as follows:
；
Wherein, Representing a defect risk assessment index,/>Representing a defect risk factor corresponding to the first internal thread segment,Representing a defect risk factor corresponding to the first cylinder segment,/>Representing a defect risk factor corresponding to the second straight barrel section,Representing a defect risk factor corresponding to the second internal thread segment,/>、/>、/>And/>The method comprises the steps that the method respectively shows the influence weight coefficient of the defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defect of a pipe blank, the Y function is a standardized function of the first internal thread degree and the second internal thread section, and the X function is a standardized function of the first straight barrel section and the second straight barrel section;
further, the method for acquiring the ultrasonic scanning echo signal data comprises the following steps:
selecting the type of a probe according to the material and the size of the copper pipe blank, and setting scanning parameters;
scanning all areas of each embryo section of the copper pipe according to the set parameters;
the ultrasonic probe sends ultrasonic signals and receives echo signals, and the echo signals are collected and recorded to form scanning data;
processing and analyzing the acquired scanning data, and extracting the characteristic information of the pipe blank defect;
And outputting the defect detection result of each pipe blank section according to the analysis result to obtain ultrasonic scanning echo signal data.
Further, the construction method of the copper pipe blank defect identification model comprises the following steps:
Collecting ultrasonic scanning echo signal data of a copper pipe blank, wherein the ultrasonic scanning echo signal data comprise reference data of cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth and normal defects;
labeling the collected data, and definitely marking defect types, positions and sizes of the defect types corresponding to each section of echo signals;
preprocessing the ultrasonic scanning echo signal data, including denoising, smoothing and normalizing;
selecting a machine learning model as a model basis, wherein the machine learning model comprises a convolutional neural network, a cyclic neural network and a transfer learning model;
Dividing the processed ultrasonic scanning echo signal data into a training set and a verification set;
Training the model by using a training set, and adjusting model parameters by optimizing a loss function;
Evaluating the performance of the model using the validation set;
after model training is completed, it is deployed into the actual defect detection system.
Further, the construction method of the tube embryo paragraph comprehensive influence weight database comprises the following steps:
Analyzing design characteristics of the copper pipe blank, including functions and importance of the internal thread section and the straight section;
The potential influence degree of different types of defects on the performance and the safety of each pipe blank section is obtained through expert opinion, engineering experience, experimental data and a numerical simulation method;
collecting and sorting data of various pipe blank sections affected by different types of defects; including cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth;
determining corresponding weight coefficients for different types of defects of each pipe blank section according to the evaluation result;
and (5) sorting the obtained comprehensive influence weight data of the pipe blank paragraphs and establishing a database.
Further, the set influencing factors of the preset defect risk evaluation threshold value comprise industry standard and legal regulation requirements, product use and environment requirements, design specification and performance requirements, engineering experience and history data, manufacturing cost and economic benefit, customer requirements and market positioning.
In another aspect, the present application further provides a system for detecting defects of an internally threaded pipe blank, the system comprising:
The pipe blank segmentation module is used for segmenting the copper pipe blank according to the design size and the structure of the copper pipe blank to obtain a pipe blank segment set, wherein the pipe blank segment set comprises a first internal thread segment, a first straight cylinder segment, a second straight cylinder segment and a second internal thread segment;
The ultrasonic scanning module is used for respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section collection to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
The defect identification module is used for respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
The risk assessment module is used for respectively carrying out risk assessment on the defect type characteristic data of each pipe embryo section to obtain defect risk factors of the corresponding pipe embryo section;
The influence weight calculation module is used for traversing a pre-constructed comprehensive influence weight database of pipe blank sections according to the design size and structure of the copper pipe blank, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the copper pipe blank; the comprehensive influence weight set of the pipe blank section comprises influence weight coefficients of defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defects of the pipe blank;
the defect risk evaluation module is used for calculating and obtaining a defect risk evaluation index of the copper pipe blank according to the defect risk factors of each pipe blank section and the comprehensive influence weight set of the pipe blank section;
The qualification judging module is used for comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value and judging whether the copper pipe blank is qualified or not according to the comparison result.
In a third aspect, the present application provides an electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected by the bus, the computer program when executed by the processor implementing the steps of any of the methods described above.
In a fourth aspect, the application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods described above.
Compared with the prior art, the invention has the beneficial effects that: by dividing the copper pipe blank into sections, different influence degrees of different parts on the whole function and safety are fully considered, so that the detection precision and accuracy are improved;
The method combines a plurality of technical means such as ultrasonic scanning, defect identification, risk assessment and the like to comprehensively assess the defects of each section of the pipe blank, thereby more accurately judging the quality and the safety of the pipe blank; by evaluating the defect risk factors of different paragraphs, the influence degree of defects of different parts on the quality of the whole pipe blank is considered, so that the evaluation result is more objective and careful;
The defect risk evaluation index is compared with a preset threshold value, so that the automatic judgment of the qualification of the pipe blank is realized, the interference of artificial subjective factors is reduced, and the objectivity and consistency of the judgment are improved; potential safety hazards of the pipe blank can be found in time through risk assessment, a powerful basis is provided for improvement and optimization in the manufacturing process, and the risk and loss of accidents are reduced;
in conclusion, the method can effectively improve the quality detection efficiency and reliability of the internal thread pipe blank, reduce the occurrence risk of potential safety hazards, and is beneficial to improving the safety level of industrial production and urban construction.
Drawings
FIG. 1 is a logic flow diagram of the present invention;
FIG. 2 is a logic flow diagram of a method of constructing a copper tubing embryo defect identification model;
FIG. 3 is a block diagram of an internally threaded tubular blank defect detection system;
Fig. 4 is a sectional view of the internal thread copper pipe.
Detailed Description
In the description of the present application, those skilled in the art will appreciate that the present application may be embodied as methods, apparatus, electronic devices, and computer-readable storage media. Accordingly, the present application may be embodied in the following forms: complete hardware, complete software (including firmware, resident software, micro-code, etc.), a combination of hardware and software. Furthermore, in some embodiments, the application may also be embodied in the form of a computer program product in one or more computer-readable storage media, which contain computer program code.
Any combination of one or more computer-readable storage media may be employed by the computer-readable storage media described above. The computer-readable storage medium includes: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer readable storage medium include the following: portable computer magnetic disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disk read-only memories, optical storage devices, magnetic storage devices, or any combination thereof. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, device.
The application provides a method, a device and electronic equipment through flow charts and/or block diagrams.
It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in a computer readable storage medium that can cause a computer or other programmable data processing apparatus to function in a particular manner. Thus, instructions stored in a computer-readable storage medium produce an instruction means which implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The present application will be described below with reference to the drawings in the present application.
Example 1
As shown in fig. 1 to 2, the method for detecting defects of an internally threaded pipe blank of the present invention specifically comprises the following steps;
S1, based on the design size and structure of a copper pipe blank, dividing the copper pipe blank into sections to obtain a pipe blank section set, wherein the pipe blank section set comprises a first internal thread section, a first straight cylinder section, a second straight cylinder section and a second internal thread section;
In the field of pipe fitting detection, the design size and structure of a copper pipe blank are critical to defect detection, geometric dimension measurement and analysis are carried out on the copper pipe blank according to design requirements and standards, and parameters such as the length, the diameter and the like of an internal thread and a straight barrel part of the copper pipe blank are determined; then, dividing the copper pipe blank into different sections according to the design structure of the pipe blank so as to facilitate subsequent detection and evaluation;
as shown in fig. 4, the set of tube blank sections includes:
The first internal thread section D1 is a section occupied by the length of the internal thread of the input end, the length of the first internal thread section is determined by design requirements, and the length of the first internal thread section is the distance from the beginning of the internal thread to the first straight barrel section;
A first straight barrel section D2 for providing a sufficient distance for the fluid to recover a laminar flow state after passing through the internal thread section, the length of which is determined by the design requirements and is long enough to ensure the stability of the fluid flow;
the second straight cylinder section D3 is a stage of maintaining a laminar flow state of the fluid in the copper pipe, and the length of the second straight cylinder section D3 is determined by design requirements and is long enough to ensure the stability of the fluid flow;
and the second internal thread section D4 is a section occupied by the length of the internal thread of the output end, and the length of the second internal thread section is determined by the design requirement and is the distance from the end of the internal thread to the tail end of the pipe blank.
The copper pipe blank is divided into different sections, so that the detection of each section is more refined; different paragraphs may be affected by different mechanical environments and stress states, so that each paragraph is detected independently, which is helpful for more accurately evaluating the defect condition; the copper pipe blank is divided into different parts such as an internal thread section, a straight barrel section and the like, so that the specific position of the defect can be positioned more easily; the defect can be accurately identified and positioned in the detection process, so that the repair or treatment can be better performed;
the design function of each paragraph is different, so the tolerance to defects is also different; by independently detecting and evaluating each paragraph, the influence of defects on the performance and safety of the whole pipe blank can be better comprehensively considered, so that the whole quality of the pipe blank can be more accurately evaluated; the pipe blank is divided into different sections, so that the detection focus is concentrated on a position possibly with a defect, and the detection efficiency is improved; by purposefully detecting each paragraph, potential problems can be found and identified more quickly, and time and cost are saved;
in summary, the step S1 can improve the detection accuracy, locate the defect position, comprehensively evaluate the defect effect, and improve the detection efficiency, thereby providing a reliable basis for the subsequent defect detection and evaluation.
S2, respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section collection to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
s2, an important link in the internal thread pipe blank defect detection method, which involves carrying out ultrasonic scanning on each pipe blank section in a pipe blank section set so as to acquire ultrasonic scanning echo signal data corresponding to the pipe blank section;
ultrasonic waves are high-frequency mechanical waves, can propagate in a medium, and generate phenomena such as reflection, refraction and the like in the medium; when the ultrasonic wave propagates between the inside and the surface of the material, the ultrasonic wave is influenced by factors such as the structure and defects of the material, so that different echo signals are generated, and the defect condition in the material can be detected by analyzing the echo signals by utilizing an ultrasonic scanning technology;
the method for acquiring the ultrasonic scanning echo signal data comprises the following steps:
s21, selecting an ultrasonic probe type according to the material and the size of a copper pipe blank, and setting scanning parameters including ultrasonic frequency, pulse repetition frequency, beam angle, scanning speed and gain parameters;
S22, moving the ultrasonic probe along the surface of the copper pipe blank, and scanning the copper pipe according to the set parameters; during the scanning process, the probe is kept in good contact with the surface of the tube blank, and scanning coverage is ensured to all areas of each tube blank section;
S23, an ultrasonic probe sends ultrasonic signals and receives echo signals, and the echo signals are collected and recorded to form scanning data; the data record includes echo amplitude and time delay information for subsequent analysis and processing;
S24, processing and analyzing the acquired scanning data, and extracting characteristic information related to the pipe blank defect; analyzing the scanning data by utilizing a signal processing algorithm and a pattern recognition technology, and recognizing possible defect characteristics of cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth;
S25, outputting a defect detection result of each pipe blank section according to the analysis result so as to facilitate subsequent risk assessment and judgment; the output results include defect location, type and size information and corresponding signal image reports.
In the step, the detailed information in the pipe embryo section can be obtained through ultrasonic scanning, and the nondestructive detection method can provide high-resolution data, so that various defects of the pipe embryo can be accurately identified;
Each pipe embryo paragraph in the pipe embryo paragraph set is subjected to ultrasonic scanning, so that the surface and the inside of the whole pipe embryo can be covered, and all areas possibly with defects are ensured to be comprehensively detected, so that missing detection and false detection are avoided;
The ultrasonic scanning has the characteristics of rapidness and real time, can finish the detection of the pipe embryo in a shorter time, and improves the detection efficiency; meanwhile, the recording and processing of the scanning data can be automated by means of equipment such as a computer, so that the detection efficiency is further improved;
By recording and storing the scanning data, the detection process can be traced and repeated, and the reliability and the credibility of the detection result are ensured; the method is beneficial to reference and analysis in subsequent quality control and product tracing;
In summary, the beneficial effects of the step S2 include improving the accuracy, comprehensiveness and high efficiency of detection, and enhancing the traceability of the detection result, so as to provide reliable basic data support for subsequent defect identification, risk assessment and judgment.
S3, respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
Aiming at the ultrasonic scanning echo signal data corresponding to the pipe blank section obtained through ultrasonic scanning in the step S2, the ultrasonic scanning echo signal data is used as input data to be imported into a pre-trained and constructed copper pipe blank defect recognition model; the model is trained based on a large amount of sample data, and can effectively analyze various defect characteristic information contained in ultrasonic scanning echo signals;
the construction method of the copper pipe blank defect identification model comprises the following steps:
s31, collecting a large amount of ultrasonic scanning echo signal data of copper pipe blanks, wherein the ultrasonic scanning echo signal data of the copper pipe blanks cover various existing defect types, including cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth and normal and defect-free reference data;
S32, marking the collected data, and definitely marking the defect type corresponding to each section of echo signal and the position and size information thereof;
S33, preprocessing the ultrasonic scanning echo signal data, including denoising, smoothing and normalization; extracting characteristic parameters reflecting defect characteristics, including echo amplitude, frequency components, attenuation characteristics, and statistical characteristics on time domain and frequency domain;
S34, selecting a machine learning model as a model basis, wherein the machine learning model comprises a convolutional neural network, a cyclic neural network and a transfer learning model;
s35, dividing the processed ultrasonic scanning echo signal data into a training set and a verification set;
s36, training the model by using a training set, and adjusting model parameters by optimizing a loss function so that the model parameters can accurately identify corresponding defect characteristics from input ultrasonic scanning echo signals;
S37, evaluating the performance of the model by using the verification set, and optimizing the recognition rate and accuracy of the model by means of adjusting the model structure, optimizing algorithm parameters and the like;
S38, after model training is completed, the model is deployed into an actual defect detection system and used for processing newly acquired ultrasonic scanning data of the copper pipe blank, so that defect type characteristic data of each section of the pipe blank can be accurately identified.
In the step, through inputting the ultrasonic scanning echo signal data into the trained defect identification model, various defects possibly existing in the pipe blank section can be identified more accurately, and the defect detection accuracy is improved;
the pre-constructed defect identification model can effectively analyze defect characteristics in ultrasonic wave scanning echo signals, can help reduce the occurrence of missed detection, and improves the comprehensiveness of tube blank defect detection;
The ultrasonic scanning echo signal data are input into the defect identification model for automatic processing, so that the detection efficiency can be greatly improved, the manpower resource cost is saved, and the production flow is accelerated; by more accurately identifying possible defects in the internal thread pipe blank, the potential safety hazard of the product in the use process can be effectively reduced, and the production safety is improved;
After the defects are detected, unqualified pipe blanks can be treated in time, unqualified products are prevented from entering a subsequent production link, and the production efficiency is improved;
In summary, the application of the defect identification model in the step S3 is helpful to improve the accuracy and efficiency of defect detection, reduce the omission factor, and enhance the production safety and efficiency, thereby providing a more reliable quality control means for the manufacturing process of the female thread pipe blank.
S4, performing risk assessment on the defect type characteristic data of each pipe blank section respectively to obtain defect risk factors of the corresponding pipe blank section;
In the step S4, detailed risk assessment is carried out on the defect type characteristic data of each pipe blank section obtained through ultrasonic scanning so as to quantify the influence degree of the defects in each section on the overall performance and safety of the pipe blank section; the process includes the following aspects:
according to characteristic data of different defect types, including cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth, evaluating potential damage degree of the copper pipe on the aspects of pressure bearing capacity, corrosion resistance, fatigue life and the like;
Considering the differences of mechanical properties and working environments of the internal thread region and the straight barrel region, the risk assessment results of defects of the same type at different positions are also different; the internal thread segments present a much higher risk here than the straight segments due to the concentration of stresses and the complex hydrodynamic characteristics, of the same size and type of defects;
based on factors such as defect type, size and position, and combining related engineering experience and a mechanical model, calculating defect risk factors of each pipe blank section; the risk factor is a numerical quantity reflecting the size of the risk that a defect in that paragraph brings to the functioning and safety of that paragraph and even the whole copper tube.
In the step, by carrying out detailed evaluation on the defect type characteristic data of each pipe blank section, various defects in each section can be accurately identified, and the method is beneficial to early finding potential risks which can influence the performance and safety of the pipe blank in the production process;
The risk assessment process not only considers the type and the position of the defect, but also comprehensively considers factors such as the size, the shape and the like of the defect, so that the influence degree of the defect in each paragraph on the overall performance and the safety of the defect can be quantified; the risk condition of each pipe blank section is better known by production managers and engineers, and targeted measures are adopted for management and repair;
considering the mechanical property and working environment difference of the internal thread area and the straight barrel area, the risk difference of the defects of the same type in different positions can be distinguished by the evaluation in the step; this helps the production manager to allocate resources and take measures with pertinence to minimize the risk of the pipe blank being in different locations;
Based on the comprehensive evaluation results of factors such as defect type, size, position and the like, production managers and engineers can more scientifically make decisions and take actions, and repair, replacement or other improvement measures can be purposefully carried out according to defect risk factors of each pipe blank section so as to ensure the quality and safety of the final product;
In summary, the beneficial effects of step S4 include improving the accuracy of risk identification, quantifying the risk influence degree, distinguishing the risk differences at different positions, and providing support for scientific decisions, so as to effectively improve the quality and safety of the production process of the pipe blank.
S5, traversing a pre-constructed comprehensive influence weight database of pipe blank sections by utilizing the design size and structure of the copper pipe blank, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the copper pipe blank;
In order to more accurately measure the influence of defects at different positions on the overall performance and safety of the copper pipe blank, a comprehensive influence weight database of pipe blank sections based on the design size and structure of the copper pipe blank is designed; the database is pre-constructed with a series of mapping relations between the defect risk indexes of the different pipe blank sections and the overall defect influence weight coefficients of the pipe blank, and the influence weight coefficients of the defect risk indexes of the corresponding sections on the overall defects can be rapidly inquired according to the specific structural information of the pipe blank of the copper pipe;
According to the actual design specification and application scene of the copper pipe, the mechanical property, the hydrodynamic property and the importance under the actual operation condition of each paragraph are researched and analyzed; for example, the internal thread segments are generally higher in risk due to defects relative to the straight barrel segments due to the special geometric shape and stress concentration characteristics, so that the corresponding defect risk indexes have larger influence weight coefficients on the overall defects of the pipe blanks;
The construction method of the comprehensive influence weight database of the pipe embryo section comprises the following steps:
s51, analyzing design characteristics of the copper pipe blank, including functions and importance of the internal thread section and the straight section; the research and analysis of engineering design files, product specifications and industry standard information are involved;
S52, obtaining potential influence degrees of different types of defects on the performance and the safety of each pipe blank section through expert opinion, engineering experience, experimental data and a numerical simulation method;
S53, collecting and sorting data of various pipe blank sections affected by different types of defects; including cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth;
S54, determining corresponding weight coefficients for different types of defects of each pipe blank section according to the evaluation result;
S55, the obtained comprehensive influence weight data of the pipe blank paragraphs are arranged and built into a database so as to facilitate subsequent application and inquiry;
The content of the comprehensive influence weight database of the pipe embryo paragraph comprises:
A list of tube embryo sections, wherein the database contains all the sections of the tube embryo, and each section has a corresponding unique identifier and name;
Different types of defects influence weights, and for each pipe blank paragraph, a database records weight coefficients of influence of different types of defects on the pipe blank paragraph, wherein the weight coefficients reflect the influence degree of the different types of defects on the performance and the safety of the pipe blank paragraph;
A defect type list, wherein various defect types which can affect the pipe blank, such as cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth, are listed in a database, and each defect has corresponding description and influence degree evaluation;
The weight calculation method comprises a specific method and a formula for weight calculation, wherein the database is used for evaluating and determining the comprehensive influence weight of the pipe embryo paragraph according to the defect type and the influence degree;
The database also comprises records for updating and maintaining the data, including data updating date, updating content and updating personnel information, so that the accuracy and timeliness of the database are ensured.
In the step, a pipe embryo section comprehensive influence weight database constructed based on the design size and the structure of the copper pipe embryo can evaluate the influence of defects at different positions on the overall performance and the safety of the pipe embryo more accurately, and the accuracy of an evaluation result is improved;
The database can quickly inquire the influence weight coefficient of the defect risk index of the corresponding paragraph on the overall defect according to the specific structural information of the copper pipe blank, so that the evaluation process is more efficient;
according to the actual design specification and application scene of the copper pipe, the mechanical property, the hydrodynamic property and the importance of each paragraph under the actual operation condition are researched and analyzed, the personalized defect influence weight can be determined for each pipe blank paragraph, and the pertinence and the applicability of the evaluation are improved;
The database contains information such as a pipe blank paragraph list, different types of defect influence weights, defect type lists and the like, so that unified management and arrangement of evaluation data are realized, and subsequent application and inquiry are facilitated; the database also comprises an update record, so that the accuracy and timeliness of the data are ensured, and reliable data support is provided for subsequent evaluation work;
In summary, the beneficial effects of the present step include improving the evaluation accuracy, improving the efficiency, personalized evaluation, unified management of data, and ensuring the accuracy and timeliness of the data.
S6, calculating to obtain a defect risk evaluation index of the copper pipe blank based on the defect risk factors of all pipe blank sections and the comprehensive influence weight set of the pipe blank sections;
In the S6 step, comprehensively evaluating the defect risk of the copper pipe blank by combining the data and the information obtained in the previous steps;
S6, calculating defect risk factors of all pipe blank sections and corresponding section comprehensive influence weight coefficients, and summarizing and calculating an overall defect risk evaluation index of the pipe blank; the index is a numerical value comprehensively considering all paragraph defect risks and the influence degree of the paragraph defect risks on the whole performance, and can more accurately reflect the defect condition of the copper pipe blank and the potential threat of the copper pipe blank to the quality and the safety performance of the product;
the calculation formula of the defect risk evaluation index is as follows:
；
Wherein, Representing a defect risk assessment index,/>Representing a defect risk factor corresponding to the first internal thread segment,Representing a defect risk factor corresponding to the first cylinder segment,/>Representing a defect risk factor corresponding to the second straight barrel section,Representing a defect risk factor corresponding to the second internal thread segment,/>、/>、/>And/>The method comprises the steps of respectively representing the influence weight coefficient of the defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defect of a pipe blank, wherein a Y function is a standardized function of the first internal thread degree and the second internal thread section, and an X function is a standardized function of the first straight barrel section and the second straight barrel section.
In the step, the comprehensive defect risk evaluation index of the copper pipe blank can be obtained by calculating the defect risk factors of all pipe blank sections and the corresponding section comprehensive influence weight coefficients; the index comprehensively considers the defect risk of each paragraph and the influence degree of the defect risk on the whole performance, so that the defect condition of the copper pipe blank can be reflected more accurately;
Because the defect types and positions of different sections have different influence on the overall performance of the pipe blank, the comprehensive influence weight coefficient is adopted for calculation, so that the fine assessment of the defect risks of different parts can be realized; such an assessment can help manufacturers to better understand the defect distribution of the pipe blanks, and to purposefully improve and repair the pipe blanks;
The defect risk evaluation index is used as an objective value, and an important basis is provided for subsequent decision; the manufacturer can determine whether to repair or replace the pipe blank according to the index, so that the quality risk of the product is reduced, and the production efficiency and the product safety are improved;
The defect risk of the pipe blank is identified and evaluated in time, so that the rejection rate caused by defects can be effectively reduced, and the production efficiency and the yield are improved; meanwhile, the high-risk pipe blank can be repaired or replaced preferentially, so that the quality and the safety performance of the product are ensured;
in summary, the beneficial effects of the step S6 include comprehensive evaluation, fine evaluation, objective decision basis provision, production efficiency improvement, etc., which can effectively help manufacturers to improve product quality and safety, and reduce production cost and risk.
S7, comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value, and judging whether the copper pipe blank is qualified or not according to a comparison result;
comparing the obtained copper pipe blank defect risk evaluation index with a preset defect risk evaluation threshold;
If the calculated risk evaluation index of the defects of the copper pipe blanks is lower than a preset threshold value, the internal defect risk of the copper pipe blanks is within an acceptable range, and the copper pipe blanks can be judged to be qualified products, so that the copper pipe blanks are suitable for further processing;
Otherwise, if the defect risk evaluation index of the copper pipe blank exceeds a preset threshold value, the defect in the copper pipe blank has a non-negligible effect on the pressure bearing capacity, the service life and the safety of the copper pipe blank, and the risk of causing faults and safety accidents is generated in practical application, so that the copper pipe blank is judged to be unqualified, and corresponding repair measures or waste treatment are needed to ensure the quality and the use safety of the product;
the setting influence factors of the preset defect risk evaluation threshold value include:
S71, industry standard and legal regulation requirements, wherein related standard and legal regulation requirements exist in different industries, the requirements on product quality and safety are regulated, and a preset defect risk evaluation threshold value meets the requirements of the standard and the legal regulation;
s72, the application and environment requirements of the products are different, and the quality and safety requirements of some products are higher;
s73, design parameters, expected working pressure, working temperature, service life of the copper pipe, bearing capacity, heat conduction efficiency, corrosion resistance and the like required under a specific application scene all influence the setting of a defect risk evaluation threshold;
S74, engineering experience and historical data summarize the influence degree of defects of different types, sizes and positions on the performance and safety of the copper pipe based on past production practice, failure case analysis and experimental study, and determine a reasonable threshold value according to the influence degree;
S75, manufacturing cost and economic benefit, wherein on the premise of ensuring safety and performance, economic cost is considered as much as possible, defect tolerance is reasonably set, and excessive high production cost or increased rejection rate caused by excessively strict standards are avoided;
s76, customer requirements and market positioning, wherein for high-end application or special fields, the customer may put more strict quality requirements, which also affect the setting of the preset defect risk evaluation threshold.
In the step, the defect risk evaluation index of the copper pipe blank is compared with a preset defect risk evaluation threshold value, so that quality control can be effectively performed, and the safety and performance of a product are ensured to meet the requirements;
defining a proper defect risk evaluation threshold value is helpful for improving production efficiency; through an automatic or semi-automatic evaluation flow, the qualification of the product can be rapidly judged, and complicated detection of all products is avoided, so that the time and the cost are saved;
when the defect risk evaluation index of the copper pipe blank exceeds a preset threshold value, corresponding repair measures or waste treatment can be timely adopted, so that the possible failure and safety accident risks caused by the product in the use process are reduced; this helps to improve the reliability and safety of the product, protecting the interests of the user;
considering that the setting of the preset defect risk evaluation threshold is influenced by industry standards and laws and regulations, the quality evaluation of the product can be ensured to meet the related requirements through the step, and the legal risk and the compliance risk are reduced;
In summary, the product quality can be effectively controlled through the step, the production efficiency is improved, the risk is reduced, the product is ensured to meet the requirements of laws and standards, and the competitiveness and sustainable development capability of enterprises are further enhanced.
Example two
As shown in FIG. 3, the system for detecting defects of an internally threaded pipe blank of the invention specifically comprises the following modules;
The pipe blank segmentation module is used for segmenting the copper pipe blank according to the design size and the structure of the copper pipe blank to obtain a pipe blank segment set, wherein the pipe blank segment set comprises a first internal thread segment, a first straight cylinder segment, a second straight cylinder segment and a second internal thread segment;
The ultrasonic scanning module is used for respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section collection to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
The defect identification module is used for respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
The risk assessment module is used for respectively carrying out risk assessment on the defect type characteristic data of each pipe embryo section to obtain defect risk factors of the corresponding pipe embryo section;
The influence weight calculation module is used for traversing a pre-constructed comprehensive influence weight database of pipe blank sections according to the design size and structure of the copper pipe blank, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the copper pipe blank; the comprehensive influence weight set of the pipe blank section comprises influence weight coefficients of defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defects of the pipe blank;
the defect risk evaluation module is used for calculating and obtaining a defect risk evaluation index of the copper pipe blank according to the defect risk factors of each pipe blank section and the comprehensive influence weight set of the pipe blank section;
The qualification judging module is used for comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value and judging whether the copper pipe blank is qualified or not according to the comparison result.
The system divides the pipe blank into different parts through the pipe blank segmentation module, and carries out independent detection and evaluation aiming at each part, so that different influence degrees of the different parts on the whole function and safety are fully considered, and the detection precision and accuracy are improved;
the system utilizes the defect recognition module and the risk assessment module to carry out defect recognition and risk assessment on the pipe embryo paragraphs, comprehensively considers risk factors of different types of defects, and enables assessment results to be more comprehensive and reliable;
The influence weight calculation module calculates the influence weight of each part defect according to the design size and structure of the pipe blank and by combining a pipe blank paragraph comprehensive influence weight database, and more objectively evaluates the influence degree of each part defect on the quality of the whole pipe blank;
Through the defect risk evaluation module, the system can quantify the defect risk evaluation index of the pipe blank, so that the evaluation result is more visual and operable, and the follow-up treatment measures can be formulated;
the qualification judging module is used for automatically judging the qualification of the pipe blank by comparing the qualification judging module with a preset defect risk evaluation threshold value, so that the interference of human subjective factors is reduced, and the objectivity and consistency of judgment are improved;
in conclusion, the system has higher practicability and operability in the field of internal thread pipe blank defect detection, can effectively improve the detection efficiency and reliability of the pipe blank quality, and reduces the occurrence risk of potential safety hazards.
The various modifications and embodiments of the method for detecting a defect of an internally threaded pipe blank in the first embodiment are equally applicable to the system for detecting a defect of an internally threaded pipe blank in the present embodiment, and those skilled in the art will be able to clearly understand the method for detecting a defect of an internally threaded pipe blank in the present embodiment through the foregoing detailed description of the method for detecting a defect of an internally threaded pipe blank, so that the detailed description thereof will be omitted herein for brevity.
In addition, the application also provides an electronic device, which comprises a bus, a transceiver, a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the transceiver, the memory and the processor are respectively connected through the bus, and when the computer program is executed by the processor, the processes of the method embodiment for controlling output data are realized, and the same technical effects can be achieved, so that repetition is avoided and redundant description is omitted.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that modifications and variations can be made without departing from the technical principles of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (9)
1. A method for detecting defects of an internally threaded pipe blank, the method comprising:
Based on the design size and structure of the copper pipe blank, carrying out paragraph division on the copper pipe blank to obtain a pipe blank paragraph set, wherein the pipe blank paragraph set comprises a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section;
Respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section set to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
Performing risk assessment on the defect type characteristic data of each pipe blank section to obtain defect risk factors of the corresponding pipe blank section;
Traversing a pre-constructed comprehensive influence weight database of pipe blank sections by utilizing the design size and structure of the pipe blank of the copper pipe, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the pipe blank of the copper pipe;
Based on the defect risk factors of all the pipe blank sections and the comprehensive influence weight set of the pipe blank sections, calculating to obtain a defect risk evaluation index of the copper pipe blank; the calculation formula of the defect risk evaluation index is as follows:
；
Wherein, Representing a defect risk assessment index,/>Representing a defect risk factor corresponding to the first internal thread segment,/>Representing a defect risk factor corresponding to the first cylinder segment,/>Representing a defect risk factor corresponding to the second straight barrel section,/>Representing a defect risk factor corresponding to the second internal thread segment,/>、/>、/>And/>The method comprises the steps that the method respectively shows the influence weight coefficient of the defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defect of a pipe blank, the Y function is a standardized function of the first internal thread degree and the second internal thread section, and the X function is a standardized function of the first straight barrel section and the second straight barrel section;
and comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value, and judging whether the copper pipe blank is qualified or not according to a comparison result.
2. The method of claim 1, wherein the first internal thread segment is a segment of the internal thread length of the input end, the first straight barrel segment is used for providing a distance sufficient for the fluid to recover a laminar flow state after passing through the internal thread segment, the second straight barrel segment is a segment of the fluid to maintain a laminar flow state in the copper pipe, and the second internal thread segment is a segment of the internal thread length of the output end.
3. The method for detecting defects of an internally threaded tubular blank according to claim 1, wherein the method for acquiring ultrasonic scanning echo signal data comprises:
Selecting the type of an ultrasonic probe according to the material and the size of the copper pipe blank, and setting scanning parameters;
scanning all areas of each embryo section of the copper pipe according to the set parameters;
the ultrasonic probe sends ultrasonic signals and receives echo signals, and the echo signals are collected and recorded to form scanning data;
processing and analyzing the acquired scanning data, and extracting the characteristic information of the pipe blank defect;
And outputting the defect detection result of each pipe blank section according to the analysis result to obtain ultrasonic scanning echo signal data.
4. The method for detecting defects of an internally threaded pipe blank according to claim 1, wherein the method for constructing the identification model of defects of the pipe blank of the copper pipe comprises the following steps:
Collecting ultrasonic scanning echo signal data of a copper pipe blank, wherein the ultrasonic scanning echo signal data comprise reference data of cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth and normal defects;
Labeling the collected data, and definitely marking defect types, positions and size information corresponding to each section of echo signals;
preprocessing the ultrasonic scanning echo signal data, including denoising, smoothing and normalizing;
selecting a machine learning model as a model basis, wherein the machine learning model comprises a convolutional neural network, a cyclic neural network and a transfer learning model;
Dividing the processed ultrasonic scanning echo signal data into a training set and a verification set;
Training the model by using a training set, and adjusting model parameters by optimizing a loss function;
Evaluating the performance of the model using the validation set;
after model training is completed, it is deployed into the actual defect detection system.
5. The method for detecting defects of an internally threaded pipe blank according to claim 1, wherein the method for constructing a pipe blank section comprehensive influence weight database comprises the following steps:
Analyzing design characteristics of the copper pipe blank, including functions and importance of the internal thread section and the straight section;
The potential influence degree of different types of defects on the performance and the safety of each pipe blank section is obtained through expert opinion, engineering experience, experimental data and a numerical simulation method;
collecting and sorting data of various pipe blank sections affected by different types of defects; including cracks, air holes, inclusions, uneven wall thickness, uneven and disordered teeth;
determining corresponding weight coefficients for different types of defects of each pipe blank section according to the evaluation result;
and (5) sorting the obtained comprehensive influence weight data of the pipe blank paragraphs and establishing a database.
6. The method of claim 1, wherein the predetermined risk assessment threshold is set to include industry standard and legal requirements, product use and environmental requirements, design specifications and performance requirements, engineering experience and historical data, manufacturing costs and economic benefits, customer requirements and market location.
7. An internally threaded tubular blank defect detection system, the system comprising:
The pipe blank segmentation module is used for segmenting the copper pipe blank according to the design size and the structure of the copper pipe blank to obtain a pipe blank segment set, wherein the pipe blank segment set comprises a first internal thread segment, a first straight cylinder segment, a second straight cylinder segment and a second internal thread segment;
The ultrasonic scanning module is used for respectively carrying out ultrasonic scanning on each pipe blank section in the pipe blank section collection to obtain ultrasonic scanning echo signal data corresponding to the pipe blank section;
The defect identification module is used for respectively inputting ultrasonic scanning echo signal data of each pipe blank section into a pre-constructed copper pipe blank defect identification model to obtain defect type characteristic data of the corresponding pipe blank section;
The risk assessment module is used for respectively carrying out risk assessment on the defect type characteristic data of each pipe embryo section to obtain defect risk factors of the corresponding pipe embryo section;
The influence weight calculation module is used for traversing a pre-constructed comprehensive influence weight database of pipe blank sections according to the design size and structure of the copper pipe blank, and determining a comprehensive influence weight set of the pipe blank sections corresponding to the copper pipe blank; the comprehensive influence weight set of the pipe blank section comprises influence weight coefficients of defect risk indexes of a first internal thread section, a first straight barrel section, a second straight barrel section and a second internal thread section on the integral defects of the pipe blank;
the defect risk evaluation module is used for calculating and obtaining a defect risk evaluation index of the copper pipe blank according to the defect risk factors of each pipe blank section and the comprehensive influence weight set of the pipe blank section;
The qualification judging module is used for comparing the defect risk evaluation index of the copper pipe blank with a preset defect risk evaluation threshold value and judging whether the copper pipe blank is qualified or not according to the comparison result.
8. An internally threaded pipe blank defect detection electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected by the bus, characterized in that the computer program when executed by the processor implements the steps of the method according to any one of claims 1-6.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-6.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS56128406A (en) * | 1980-03-14 | 1981-10-07 | Nippon Kokan Kk <Nkk> | Checking method for chamfering defect of outside face of tube with screw |
| CN101558297A (en) * | 2006-09-21 | 2009-10-14 | 住友金属工业株式会社 | Ultrasonic testing method of threaded joint of pipes or tubes |
| CN105181251A (en) * | 2015-09-22 | 2015-12-23 | 山东康迪泰克工程橡胶有限公司 | Pulse segmented pressure testing device and pressure testing method |
| JP2016045169A (en) * | 2014-08-26 | 2016-04-04 | 中国電力株式会社 | Method for evaluating defect of screw part |
| CN106124620A (en) * | 2016-06-14 | 2016-11-16 | 北京理工大学 | A kind of transverse and longitudinal ripple lossless detection method of corrugated tubing surfaces externally and internally longitudinal crack |
| EP3382386A1 (en) * | 2017-03-29 | 2018-10-03 | Fujitsu Limited | Defect detection using ultrasound scan data |
| CN208383808U (en) * | 2018-05-24 | 2019-01-15 | 海洋石油工程股份有限公司 | The track of segmented submarine pipeline phased array testing calibration test block |
| CN109725059A (en) * | 2019-01-31 | 2019-05-07 | 景德镇陶瓷大学 | A kind of method of ultrasonic Doppler non-destructive testing inner wall of the pipe corrosion default |
| JP2019184415A (en) * | 2018-04-10 | 2019-10-24 | 日立Ｇｅニュークリア・エナジー株式会社 | Ultrasonic wave flaw detection method and device |
| CN111127429A (en) * | 2019-12-24 | 2020-05-08 | 魏志康 | Water conservancy system pipe thread defect detection method based on self-training deep neural network |
| CN113866259A (en) * | 2021-12-02 | 2021-12-31 | 中国核电工程有限公司 | Electromagnetic detection method and system for stainless steel pipeline weld defects |
| CN117372433A (en) * | 2023-12-08 | 2024-01-09 | 菲沃泰纳米科技(深圳)有限公司 | Thickness parameter control method, device, equipment and storage medium |
| CN117388359A (en) * | 2023-10-16 | 2024-01-12 | 西安科技大学 | In-service drill rod thread defect nondestructive testing method based on ultrasonic guided wave |
| CN117495093A (en) * | 2023-11-08 | 2024-02-02 | 哈尔滨航天恒星数据系统科技有限公司 | Drain pipe network defect hidden danger risk assessment method, electronic equipment and storage medium |
| CN117890472A (en) * | 2024-03-06 | 2024-04-16 | 广东省特种设备检测研究院珠海检测院 | Online rapid detection device and detection method for high-temperature pipeline |
-
2024
- 2024-04-08 CN CN202410412441.6A patent/CN118010847B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS56128406A (en) * | 1980-03-14 | 1981-10-07 | Nippon Kokan Kk <Nkk> | Checking method for chamfering defect of outside face of tube with screw |
| CN101558297A (en) * | 2006-09-21 | 2009-10-14 | 住友金属工业株式会社 | Ultrasonic testing method of threaded joint of pipes or tubes |
| JP2016045169A (en) * | 2014-08-26 | 2016-04-04 | 中国電力株式会社 | Method for evaluating defect of screw part |
| CN105181251A (en) * | 2015-09-22 | 2015-12-23 | 山东康迪泰克工程橡胶有限公司 | Pulse segmented pressure testing device and pressure testing method |
| CN106124620A (en) * | 2016-06-14 | 2016-11-16 | 北京理工大学 | A kind of transverse and longitudinal ripple lossless detection method of corrugated tubing surfaces externally and internally longitudinal crack |
| EP3382386A1 (en) * | 2017-03-29 | 2018-10-03 | Fujitsu Limited | Defect detection using ultrasound scan data |
| JP2019184415A (en) * | 2018-04-10 | 2019-10-24 | 日立Ｇｅニュークリア・エナジー株式会社 | Ultrasonic wave flaw detection method and device |
| CN208383808U (en) * | 2018-05-24 | 2019-01-15 | 海洋石油工程股份有限公司 | The track of segmented submarine pipeline phased array testing calibration test block |
| CN109725059A (en) * | 2019-01-31 | 2019-05-07 | 景德镇陶瓷大学 | A kind of method of ultrasonic Doppler non-destructive testing inner wall of the pipe corrosion default |
| CN111127429A (en) * | 2019-12-24 | 2020-05-08 | 魏志康 | Water conservancy system pipe thread defect detection method based on self-training deep neural network |
| CN113866259A (en) * | 2021-12-02 | 2021-12-31 | 中国核电工程有限公司 | Electromagnetic detection method and system for stainless steel pipeline weld defects |
| CN117388359A (en) * | 2023-10-16 | 2024-01-12 | 西安科技大学 | In-service drill rod thread defect nondestructive testing method based on ultrasonic guided wave |
| CN117495093A (en) * | 2023-11-08 | 2024-02-02 | 哈尔滨航天恒星数据系统科技有限公司 | Drain pipe network defect hidden danger risk assessment method, electronic equipment and storage medium |
| CN117372433A (en) * | 2023-12-08 | 2024-01-09 | 菲沃泰纳米科技(深圳)有限公司 | Thickness parameter control method, device, equipment and storage medium |
| CN117890472A (en) * | 2024-03-06 | 2024-04-16 | 广东省特种设备检测研究院珠海检测院 | Online rapid detection device and detection method for high-temperature pipeline |
Non-Patent Citations (2)
| Title |
|---|
| GANG-YI C等: "Ultrasonic Guided Wave Detection Study of Crack Defect in Straight Pipe Based on ANSYS Numerical Simulation", PIPELINE TECHNIQUE AND EQUIPMENT, 31 January 2018 (2018-01-31), pages 24 - 27 * |
| 李黔等: "油井导管打入过程缺陷部位动应力分析", 石油矿场机械, vol. 2005, no. 04, 25 January 2023 (2023-01-25), pages 52 - 54 * |
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