Pipeline internal detection system and method based on ultrasonic phased array

Abstract

The invention relates to the technical field of pipeline defect detection, in particular to a pipeline interior detection system and method based on an ultrasonic phased array, and the method comprises the following steps: collecting defect feature information and defect distribution information of volume type defects in a pipeline; performing defect feature analysis based on the defect feature information, and determining a defect influence coefficient; determining a defect aggregation coefficient of the pipeline based on the defect distribution information; and a pipeline defect index is determined according to the defect influence coefficient and the defect aggregation coefficient, and when the pipeline defect index is larger than a preset defect threshold value, pipeline defect early warning is sent out. According to the method, the influence degree of the defects in the pipeline and the defect aggregation effect are quantified, so that the accuracy and reliability of pipeline defect detection are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline defect detection, and in particular to an ultrasonic phased array-based pipeline in-pipeline detection system and method. Background Art

[0002] Pipelines are an important part of industrial development and an effective tool for energy transportation. They play an indispensable role in industrial production because of their high efficiency, safety and economy. In-pipeline detection technology is an effective means of pipeline status perception and safety maintenance.

[0003] In-pipeline detection technology refers to the technology that relies on in-pipeline detectors to conduct online detection of internal defects in pipelines without affecting the normal and safe operation of the pipeline. It mainly includes magnetic flux leakage detection technology, ultrasonic detection technology and eddy current detection technology.

[0004] Among them, ultrasonic detection technology represented by ultrasonic phased array detection technology has been widely used in the field of pipeline nondestructive testing due to its flexible sound beam controllability, strong detection adaptability, and good defect detection rate. By mining defect information from the detection signal, ultrasonic phased array detection technology can identify, locate and quantify pipeline defects, thereby realizing pipeline status assessment.

[0005] Existing pipeline defect detection methods usually only focus on single defect characteristics, lack analysis of the defect impact and defect aggregation effect, and cannot fully reflect the overall condition of the pipeline. The impact of a single defect on the structural integrity of the pipeline is amplified under the influence of the defect aggregation effect, increasing the risk of pipeline failure. Summary of the invention

[0006] In order to overcome the defects and shortcomings of the prior art, the present invention provides an in-pipeline detection system and method based on an ultrasonic phased array, which improves the accuracy and reliability of pipeline defect detection by quantifying the degree of defect impact and defect aggregation effect inside the pipeline.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a pipeline in-pipeline detection method based on an ultrasonic phased array, comprising the following steps:

[0009] Collect defect characteristic information and defect distribution information of volume defects in pipelines;

[0010] Perform defect feature analysis based on the defect feature information to determine a defect influence coefficient;

[0011] Determining a defect aggregation coefficient of the pipeline based on the defect distribution information;

[0012] The pipeline defect index is determined by the defect influence coefficient and the defect aggregation coefficient, and when the pipeline defect index is greater than a preset defect threshold, a pipeline defect warning is issued.

[0013] As a preferred technical solution, the step of determining the defect influence coefficient includes:

[0014] Acquire the defect characteristic information and pipeline wall thickness information, wherein the defect characteristic information includes defect maximum length information, defect maximum width information and defect maximum depth information;

[0015] Substitute the defect feature information and the pipe wall thickness information into the defect influence coefficient calculation formula to calculate the defect influence coefficient. The defect influence coefficient calculation formula is as follows:

[0016]

[0017] Where H(i) represents the maximum depth of the i-th defect in the pipeline, δ(i) represents the defect location influencing factor, D represents the pipeline wall thickness information, L(i) represents the maximum length of the i-th defect in the pipeline, W(i) represents the maximum width of the i-th defect in the pipeline, N represents the number of defects in the pipeline, e represents a natural constant, ln[·] represents taking the natural logarithm, η represents the adjustment factor, and K DI Defect influence coefficient.

[0018] As a preferred technical solution, the calculation formula of the defect position influencing factor is as follows:

[0019]

[0020] Where d in (i) represents the distance between the i-th defect in the pipeline and the inner wall of the pipeline, d out (i) represents the distance between the i-th defect in the pipeline and the outer wall of the pipeline, D represents the pipeline wall thickness information, min[d in (i),d out (i)] means taking d in (i) and d out (i), δ(i) represents the defect location influence factor.

[0021] As a preferred technical solution, the method of determining the defect aggregation coefficient of the pipeline includes:

[0022] Acquiring the defect distribution information, wherein the defect distribution information includes defect quantity information and defect location information of a pipe wall cross section;

[0023] Substituting the defect distribution information into a defect concentration calculation formula to calculate the defect concentration of the pipe wall cross section;

[0024] Substitute the defect aggregation degree into the defect aggregation coefficient calculation formula to calculate the defect aggregation coefficient. The defect aggregation coefficient calculation formula is as follows:

[0025]

[0026] Where C k represents the defect concentration of the kth layer of the pipe wall cross section, M represents the number of layers of the pipe wall cross section, K DA Represents the defect aggregation coefficient of the pipeline.

[0027] As a preferred technical solution, the defect aggregation calculation formula is as follows:

[0028]

[0029] Where d k (i,j) represents the distance between the i-th defect and the j-th defect in the cross section of the k-th layer of the tube wall, N k represents the number of defects in the cross section of the k-th layer of pipe wall, C k Represents the defect concentration of the cross section of the kth layer of the tube wall.

[0030] As a preferred technical solution, the step of determining the pipeline defect index includes:

[0031] Obtaining the defect influence coefficient and the defect aggregation coefficient;

[0032] The pipeline defect index is calculated by the defect influence coefficient and the defect aggregation coefficient. The calculation formula of the pipeline defect index is as follows:

[0033] K=ω1×K DI +ω2×K DA ;

[0034] Where K DI Defect influence coefficient, K DA represents the defect aggregation coefficient, ω1 represents the defect impact weight, ω2 represents the defect aggregation weight, and K represents the pipeline defect index.

[0035] It should be noted that the adjustment factor, defect impact weight, defect aggregation weight and preset defect threshold are obtained as follows: 5000 sets of defect feature information and defect distribution information are collected to distinguish whether the pipeline defect detection effect meets the detection requirements, the defect feature information and defect distribution information are substituted into the pipeline defect index calculation formula for calculation, the calculated pipeline defect index and the distinction result are simultaneously imported into the fitting software, and the optimal adjustment factor, defect impact weight, defect aggregation weight and preset defect threshold that meet the distinction accuracy of the distinction result are output.

[0036] In a second aspect, an embodiment of the present invention provides a pipeline detection system based on an ultrasonic phased array, comprising:

[0037] Information collection module, used to collect defect characteristic information and defect distribution information of volume defects in pipelines;

[0038] A defect influence coefficient calculation module, used to perform defect feature analysis based on the defect feature information and determine the defect influence coefficient;

[0039] A defect aggregation coefficient calculation module, used to determine the defect aggregation coefficient of the pipeline based on the defect distribution information;

[0040] The pipeline defect index calculation module is used to determine the pipeline defect index through the defect influence coefficient and the defect aggregation coefficient, and issue a pipeline defect warning when the pipeline defect index is greater than a preset defect threshold.

[0041] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes an ultrasonic phased array-based in-pipeline detection method by calling the computer program stored in the memory.

[0042] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute an in-pipeline detection method based on an ultrasonic phased array.

[0043] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0044] The present invention firstly collects defect feature information to analyze defect features, and quantifies the degree of defect influence by calculating the defect influence coefficient, then determines the defect aggregation coefficient of the pipeline through the defect distribution information, and quantifies the degree of defect aggregation inside the pipeline through the defect aggregation coefficient, and finally obtains the pipeline defect index through the defect influence coefficient and the defect aggregation coefficient, and comprehensively evaluates the internal defects of the pipeline through the pipeline defect index, thereby improving the accuracy and reliability of pipeline defect detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0046] Figure 1A schematic diagram of the overall process of an ultrasonic phased array-based pipeline detection method provided by the present invention;

[0047] Figure 2 A schematic diagram of the structure of an in-pipeline detection system based on an ultrasonic phased array provided by the present invention;

[0048] Figure 3 This is a schematic structural diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0050] Before introducing a pipeline detection method based on an ultrasonic phased array provided in an embodiment of the present invention, some concepts involved in the embodiment of the present invention are first introduced:

[0051] Ultrasonic phased array technology is a multi-beam scanning imaging technology developed on the basis of traditional ultrasonic technology. It uses a precise array probe containing a specific number of array element chips, and cooperates with comprehensive phased array detection imaging software to control the high-frequency sound beam to follow the basic propagation law of ultrasonic waves to propagate in the material. After the defect is detected, a defect scanning image can be formed on the screen in real time and intuitively. Ultrasonic phased array technology generates and receives ultrasonic beams through multiple small piezoelectric chips (the number is 16, 32, 64 or 128) installed in the shell of the phased array probe. The cooperation between the electronic control unit and the ultrasonic phased array control software realizes the piezoelectric The pulse phase changes during the chip array excitation process. The piezoelectric chips generate their own ultrasonic fields under different excitation pulse phases and interfere with each other in the propagation medium, thereby forming a synthetic sound beam with different deflection angles, focal positions and focusing depths to control the shape of the ultrasonic radiation wave field. In the process of transmitting sound waves to encountering defects, the data acquisition module transmits a trigger signal to the phased array unit. Based on the transmission focusing law, the phased array unit converts the trigger signal into a high-voltage pulse signal with a specific pulse width and time delay. After each array element in the phased array probe receives a specific pulse, it will form a specific deflection angle and focus. The sound waves overlap and interfere with each other to form a composite sound beam, which continues to propagate forward until it encounters a defect. In the process from encountering the defect to receiving the sound wave, the composite sound beam hits the defect and is reflected by the phased array element. Based on the receiving focusing law, the reflected defect echoes are combined to form an ultrasonic pulse according to the time offset. The ultrasonic pulse is transmitted to the data acquisition module to obtain the defect detection information, and the defect information is processed to determine the defect characteristics. The ultrasonic pulse is imaged through the ultrasonic phased array detection view to display the detection images of different sections, which is convenient for locating and quantitatively analyzing the defects at the inspected position. This completes the entire process of ultrasonic phased array testing. Ultrasonic phased array testing technology has two major characteristics: controllable beam angle and dynamic focusing. Compared with traditional ultrasonic testing technology, it has obvious advantages: (1) The ultrasonic phased array probe is composed of an array of multiple independent piezoelectric chips and is controlled by an electronic system, with high detection efficiency; (2) The phase of each beam is controllable, and the focus and beam direction can be dynamically controlled by software to achieve multi-angle, multi-level, and multi-directional scanning of the area of ​​interest. It has good adaptability to working conditions and can scan various areas of thick workpieces and complex-shaped workpieces without moving the probe or moving the probe as little as possible. In addition, the detection system is more flexible;(3) The length of the focal column, the focal size, and the direction of the sound beam can be optimized and controlled, thereby improving the defect resolution, signal-to-noise ratio, and defect detection rate. Therefore, the acquisition of defect information in pipelines through ultrasonic phased array technology has the following advantages: (1) High resolution and adjustability. Ultrasonic phased array technology transmits and receives ultrasonic beams through the independent control of multiple array elements. It can flexibly adjust the angle and focus of the beam according to the needs of defect acquisition in the pipeline, thereby improving the positioning accuracy and resolution of the defects; (2) Compared with traditional ultrasonic detection, ultrasonic phased array can obtain ultrasonic reflection signals at multiple angles through a single scan, thereby reducing the need for repeated scanning, making full coverage detection of pipelines more efficient, especially suitable for defect detection in complex pipeline structures or pipeline bends; (3) Fast data acquisition. Ultrasonic phased array technology can obtain information on multiple data points in a single scan by controlling multiple array elements at the same time. The parallel acquisition method greatly speeds up the detection speed, shortens the time for collecting defect information in the pipeline, and improves the efficiency of defect detection; (4) Visualization and imaging. Ultrasonic phased array technology can generate real-time 2D, 3D images provide clear visualization results, helping operators to more intuitively analyze and evaluate the size, shape and location of defects. Real-time visualization has important application value for quantitative analysis of complex defects in pipelines. (5) Strong penetration ability and wide adaptability. Ultrasonic waves have good penetration ability in metal materials and can detect different types of defects such as corrosion, cracks, and wear inside pipelines. At the same time, ultrasonic phased array technology can adapt to pipelines of different thicknesses and material types by adjusting the frequency and emission angle of ultrasonic waves, and has strong adaptability. (6) Higher signal-to-noise ratio. Since the ultrasonic phased array system can control the focus of the beam, it can improve the control of the signal and the recognition of the defect echo. Compared with traditional ultrasonic testing, it can obtain a higher signal-to-noise ratio and reduce the interference of background noise, thereby more accurately identifying the defect characteristics in the pipeline. (7) Suitable for complex defect detection. The defects inside the pipeline have various forms such as corrosion, cracks, and pores. Ultrasonic phased array technology can flexibly respond to different defect forms through beam control, especially in areas that are difficult to cover by traditional methods such as pipeline welds or bends.

[0052] The ultrasonic phased array detection view mainly includes A scan, B scan, C scan and S scan, where the collected original signal is recorded in the form of A scan, and the incident wave, defect wave and bottom wave of each scanning point are displayed in the form of amplitude time curve. The ultrasonic phased array C scan image is a plane top view image of the scanning area, which can provide the shape and size information of the defect. It is divided into two display modes: amplitude image and depth image. Only the defect echo characteristics of the A scan signal are used for imaging. The C scan calculates the defect wave amplitude of the A scan signal in the scanning area and displays the amplitude by color coding. The depth image calculates the depth information of the defect by using the signal transit time, and color codes the depth. It is obtained by combining all the scanning points in the scanning area. The B scan and S scan are both pipeline cross-sectional views, and the ordinates are both ultrasonic sound path. They are obtained by color coding the amplitude of all sampling points in the sound path, which can provide the defect cross-sectional shape and depth information. The B scan image is a cross-sectional view in the scanning direction, and the S scan image is a cross-sectional view in the stepping direction. The S scan view is a detection view unique to the ultrasonic phased array technology.

[0053] Volume defects are usually divided into plane defects and volume defects according to their geometric shapes and characteristics in the internal space of the pipeline. Volume defects refer to defects with a certain length, width, and depth, such as corrosion pits and holes. Ultrasonic phased array technology has a good detection effect on volume defects.

[0054] like Figure 1 As shown, an embodiment of the present invention provides a pipeline detection method based on ultrasonic phased array, which specifically includes the following steps:

[0055] S1: Collect defect characteristic information and defect distribution information of volume defects in pipelines;

[0056] The defect characteristic information and the defect distribution information of the volumetric defects in the pipeline are collected by ultrasonic phased array technology.

[0057] S2: performing defect feature analysis based on the defect feature information to determine a defect influence coefficient;

[0058] The length, width and depth of internal defects in pipelines directly affect the bearing capacity and overall structural safety of pipelines. Longer or wider defects may lead to stress concentration in a larger range and increase the risk of local damage. The depth of the defect is related to the effective thickness of the pipeline wall. Deeper defects can significantly reduce the ability of the pipeline to resist external pressure and corrosion, thereby increasing the possibility of leakage or rupture. The defect influence coefficient quantifies the impact of specific defects on the safety of pipeline structures by comprehensively considering the defect characteristic information and combining the pipeline wall thickness information, and determines the defect influence coefficient, including:

[0059] Acquire the defect characteristic information and pipeline wall thickness information, wherein the defect characteristic information includes defect maximum length information, defect maximum width information and defect maximum depth information;

[0060] Substitute the defect feature information and the pipe wall thickness information into the defect influence coefficient calculation formula to calculate the defect influence coefficient. The defect influence coefficient calculation formula is as follows:

[0061]

[0062] Where H(i) represents the maximum depth of the i-th defect in the pipeline, δ(i) represents the defect location influencing factor, D represents the pipeline wall thickness information, L(i) represents the maximum length of the i-th defect in the pipeline, W(i) represents the maximum width of the i-th defect in the pipeline, N represents the number of defects in the pipeline, e represents a natural constant, ln[·] represents taking the natural logarithm, η represents the adjustment factor, and K DI represents the defect influence coefficient;

[0063] The distance of the defect relative to the inner and outer walls of the pipeline will affect the pressure bearing capacity and corrosion rate of the pipeline. In terms of pressure bearing capacity, defects close to the inner wall can directly affect the pipeline's ability to withstand internal pressure and increase the risk of rupture, while defects close to the outer wall affect the pipeline's ability to resist external loads. At the same time, defects close to the inner and outer walls will cause stress concentration, thereby reducing the fatigue life of the pipeline and increasing the risk of pipeline rupture or failure. In terms of corrosion rate, inner wall defects are more likely to accumulate corrosive substances in the fluid, thereby accelerating corrosion, while outer wall defects are more susceptible to the environmental factors of the pipeline. The calculation formula for the defect position influencing factor is as follows:

[0064]

[0065] Where d in (i) represents the distance between the i-th defect in the pipeline and the inner wall of the pipeline, d out (i) represents the distance between the i-th defect in the pipeline and the outer wall of the pipeline, D represents the pipeline wall thickness information, min[d in (i),d out (i)] means taking d in (i) and d out (i), δ(i) represents the defect location influence factor.

[0066] S3: Determine a defect aggregation coefficient of the pipeline based on the defect distribution information;

[0067] The defect aggregation coefficient is a quantitative indicator used to evaluate the distribution of defects on the cross section of the pipe wall. It reflects the concentration of defects on the pipeline by analyzing the defect aggregation of different levels of the pipe wall cross section. A higher defect aggregation coefficient usually means that there are more defects in a specific area, resulting in more serious stress concentration and damage risks, which in turn affects the overall safety and reliability of the pipeline. Determine the defect aggregation coefficient of the pipeline, including:

[0068] Acquiring the defect distribution information, wherein the defect distribution information includes defect quantity information and defect location information of a pipe wall cross section;

[0069] Substituting the defect distribution information into a defect concentration calculation formula to calculate the defect concentration of the pipe wall cross section;

[0070] Substitute the defect aggregation degree into the defect aggregation coefficient calculation formula to calculate the defect aggregation coefficient. The defect aggregation coefficient calculation formula is as follows:

[0071]

[0072] Where C k represents the defect concentration of the kth layer of the pipe wall cross section, M represents the number of layers of the pipe wall cross section, K DA It represents the defect aggregation coefficient of the pipeline;

[0073] The defect concentration calculation formula is as follows:

[0074]

[0075] Where d k (i,j) represents the distance between the i-th defect and the j-th defect in the cross section of the k-th layer of the tube wall, N k represents the number of defects in the cross section of the k-th layer of pipe wall, C k Represents the defect concentration of the cross section of the kth layer of pipe wall.

[0076] S4: determining a pipeline defect index by using the defect influence coefficient and the defect aggregation coefficient, and issuing a pipeline defect warning when the pipeline defect index is greater than a preset defect threshold;

[0077] The defect impact coefficient reflects the potential threat of different defects to the safety of pipeline structures, while the defect aggregation coefficient describes the concentration of defects in a specific area. When the defect impact coefficient is high, even if the number of defects is small, it may still have a greater impact on the pipeline, while a high defect aggregation coefficient means that there are multiple defects in a specific location, which may lead to a significant decrease in local bearing capacity. Therefore, by combining the defect impact coefficient and the defect aggregation coefficient to calculate the pipeline defect index, the overall risk level of the pipeline can be more comprehensively evaluated and the pipeline defect index can be determined, including:

[0078] Obtaining the defect influence coefficient and the defect aggregation coefficient;

[0079] The pipeline defect index is calculated by the defect influence coefficient and the defect aggregation coefficient. The calculation formula of the pipeline defect index is as follows:

[0080] K=ω1×K DI +ω2×K DA ;

[0081] Where K DI Defect influence coefficient, K DA represents the defect aggregation coefficient, ω1 represents the defect impact weight, ω2 represents the defect aggregation weight, and K represents the pipeline defect index.

[0082] like Figure 3 As shown, an embodiment of the present invention provides a pipeline detection system based on ultrasonic phased array, comprising:

[0083] The information collection module 210 is used to collect defect characteristic information and defect distribution information of volume defects in the pipeline;

[0084] A defect influence coefficient calculation module 220 is used to perform defect feature analysis based on the defect feature information to determine the defect influence coefficient;

[0085] A defect aggregation coefficient calculation module 230 is used to determine the defect aggregation coefficient of the pipeline based on the defect distribution information;

[0086] The pipeline defect index calculation module 240 is used to determine the pipeline defect index through the defect influence coefficient and the defect aggregation coefficient, and issue a pipeline defect warning when the pipeline defect index is greater than a preset defect threshold.

[0087] In an embodiment of the present invention, the information acquisition module 210 is used to acquire defect characteristic information and defect distribution information of volume defects in the pipeline, wherein the defect characteristic information and the defect distribution information of volume defects in the pipeline are acquired by ultrasonic phased array technology.

[0088] In an embodiment of the present invention, the defect influence coefficient calculation module 220 is used to perform defect feature analysis based on the defect feature information to determine the defect influence coefficient. Determining the defect influence coefficient includes:

[0089] Acquire the defect characteristic information and pipeline wall thickness information, wherein the defect characteristic information includes defect maximum length information, defect maximum width information and defect maximum depth information;

[0090] Substitute the defect feature information and the pipe wall thickness information into the defect influence coefficient calculation formula to calculate the defect influence coefficient. The defect influence coefficient calculation formula is as follows:

[0091]

[0092] Where H(i) represents the maximum depth of the i-th defect in the pipeline, δ(i) represents the defect location influencing factor, D represents the pipeline wall thickness information, L(i) represents the maximum length of the i-th defect in the pipeline, W(i) represents the maximum width of the i-th defect in the pipeline, N represents the number of defects in the pipeline, e represents a natural constant, ln[·] represents taking the natural logarithm, η represents the adjustment factor, and K DI represents the defect influence coefficient;

[0093] The calculation formula of defect location influencing factor is as follows:

[0094]

[0095] Where d in (i) represents the distance between the i-th defect in the pipeline and the inner wall of the pipeline, d out (i) represents the distance between the i-th defect in the pipeline and the outer wall of the pipeline, D represents the pipeline wall thickness information, min[d in (i),d out (i)] means taking d in (i) and d out (i), δ(i) represents the defect location influence factor.

[0096] In an embodiment of the present invention, the defect aggregation coefficient calculation module 230 is used to determine the defect aggregation coefficient of the pipeline based on the defect distribution information. Determining the defect aggregation coefficient of the pipeline includes:

[0097] Acquiring the defect distribution information, wherein the defect distribution information includes defect quantity information and defect location information of a pipe wall cross section;

[0098] Substituting the defect distribution information into a defect concentration calculation formula to calculate the defect concentration of the pipe wall cross section;

[0099] Substitute the defect aggregation degree into the defect aggregation coefficient calculation formula to calculate the defect aggregation coefficient. The defect aggregation coefficient calculation formula is as follows:

[0100]

[0101] Where C k represents the defect concentration of the kth layer of the pipe wall cross section, M represents the number of layers of the pipe wall cross section, K DA It represents the defect aggregation coefficient of the pipeline;

[0102] The defect concentration calculation formula is as follows:

[0103]

[0104] Where d k (i,j) represents the distance between the i-th defect and the j-th defect in the cross section of the k-th layer of the tube wall, N k represents the number of defects in the cross section of the k-th layer of pipe wall, C k Represents the defect concentration of the cross section of the kth layer of pipe wall.

[0105] In an embodiment of the present invention, the pipeline defect index calculation module 240 is used to determine the pipeline defect index by using the defect influence coefficient and the defect aggregation coefficient. When the pipeline defect index is greater than a preset defect threshold, a pipeline defect warning is issued. The pipeline defect index is determined, including:

[0106] Obtaining the defect influence coefficient and the defect aggregation coefficient;

[0107] The pipeline defect index is calculated by the defect influence coefficient and the defect aggregation coefficient. The calculation formula of the pipeline defect index is as follows:

[0108] K=ω1×K DI +ω2×K DA ;

[0109] Where K DI Defect influence coefficient, K DA represents the defect aggregation coefficient, ω1 represents the defect impact weight, ω2 represents the defect aggregation weight, and K represents the pipeline defect index.

[0110] For the above-mentioned parameters in the in-pipeline detection system based on ultrasonic phased array of the present invention and the steps for each unit module to realize the corresponding functions, reference can be made to the parameters and steps in the embodiment of the in-pipeline detection method based on ultrasonic phased array above, and no further details will be given here.

[0111] like Figure 3 As shown, an embodiment of the present invention further provides an electronic device 300, including a memory 320 for storing a computer program 322; a processor 310 for executing the computer program 322 to implement a pipeline detection method based on an ultrasonic phased array as in any of the above embodiments.

[0112] It should be noted that Figure 3 It is a structural diagram of an electronic device 300 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of application of the present invention.

[0113] Specifically, the electronic device 300 may include: at least one processor 310, at least one memory 320, a power supply 330, a communication interface 340, an input / output interface 350, and a communication bus 360. The memory 320 is used to store a computer program 322, which is loaded and executed by the processor 310 to implement the relevant steps in a pipeline detection method based on an ultrasonic phased array disclosed in any of the above embodiments. In addition, the electronic device 300 in the embodiment of the present invention may be specifically an electronic computer.

[0114] In an embodiment of the present invention, a power supply 330 is used to provide a working voltage for each hardware device on the electronic device 300; the communication interface 340 can create a data transmission channel between the electronic device 300 and an external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present invention, and is not specifically limited here; the input and output interface 350 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0115] In addition, the memory 320, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 321, a computer program 322, etc., and the storage method can be temporary storage or permanent storage.

[0116] The operating system 321 is used to manage and control the hardware devices and computer programs on the electronic device 300, and may be Windows Server, NetWare, Unix, Linux, etc. In addition to the computer program 322 that can be used to complete the ultrasonic phased array-based pipeline detection method performed by the electronic device 300 disclosed in any of the aforementioned embodiments, the computer program 322 may further include a computer program 322 that can be used to complete other specific tasks.

[0117] An embodiment of the present invention further provides a computer-readable storage medium for storing a computer program 322. When the computer program 322 is executed by the processor 310, it implements a pipeline detection method based on ultrasonic phased array as described in any of the above embodiments.

[0118] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0119] In the embodiments provided by the present invention, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system and method embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0120] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0121] It should be noted that, in this article, the terms "comprise", "include" or any other variations 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 includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0122] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A pipeline detection method based on ultrasonic phased array, characterized in that: The steps include: Collect defect characteristic information and defect distribution information of volume defects in pipelines; Perform defect feature analysis based on the defect feature information to determine a defect influence coefficient; Determining a defect aggregation coefficient of the pipeline based on the defect distribution information; The pipeline defect index is determined by the defect influence coefficient and the defect aggregation coefficient, and when the pipeline defect index is greater than a preset defect threshold, a pipeline defect warning is issued.

2. The method for in-pipeline detection based on ultrasonic phased array according to claim 1, characterized in that: The determining of the defect influence coefficient comprises: Acquire the defect characteristic information and pipeline wall thickness information, wherein the defect characteristic information includes defect maximum length information, defect maximum width information and defect maximum depth information; Substitute the defect feature information and the pipe wall thickness information into the defect influence coefficient calculation formula to calculate the defect influence coefficient. The defect influence coefficient calculation formula is as follows: Where H(i) represents the maximum depth of the i-th defect in the pipeline, δ(i) represents the defect location influencing factor, D represents the pipeline wall thickness information, L(i) represents the maximum length of the i-th defect in the pipeline, W(i) represents the maximum width of the i-th defect in the pipeline, N represents the number of defects in the pipeline, e represents a natural constant, ln[·] represents taking the natural logarithm, η represents the adjustment factor, and K DI Defect influence coefficient.

3. The method for in-pipeline detection based on ultrasonic phased array according to claim 2, characterized in that: The calculation formula of the defect position influencing factor is as follows: Where d in (i) represents the distance between the i-th defect in the pipeline and the inner wall of the pipeline, d out (i) represents the distance between the i-th defect in the pipeline and the outer wall of the pipeline, D represents the pipeline wall thickness information, min[d in (i),d out (i)] means taking d in (i) and d out (i), δ(i) represents the defect location influence factor.

4. The method for in-pipeline detection based on ultrasonic phased array according to claim 1, characterized in that: The step of determining the defect aggregation coefficient of the pipeline includes: Acquiring the defect distribution information, wherein the defect distribution information includes defect quantity information and defect location information of a pipe wall cross section; Substituting the defect distribution information into a defect concentration calculation formula to calculate the defect concentration of the pipe wall cross section; Substitute the defect aggregation degree into the defect aggregation coefficient calculation formula to calculate the defect aggregation coefficient. The defect aggregation coefficient calculation formula is as follows: Where C k represents the defect concentration of the kth layer of the pipe wall cross section, M represents the number of layers of the pipe wall cross section, K DA Represents the defect aggregation coefficient of the pipeline.

5. The method for in-pipeline detection based on ultrasonic phased array according to claim 4, characterized in that: The defect concentration calculation formula is as follows: Where d k (i,j) represents the distance between the i-th defect and the j-th defect in the cross section of the k-th layer of the tube wall, N k represents the number of defects in the cross section of the k-th layer of pipe wall, C k Represents the defect concentration of the cross section of the kth layer of the tube wall.

6. The method for in-pipeline detection based on ultrasonic phased array according to claim 1, characterized in that: The step of determining the pipeline defect index comprises: Obtaining the defect influence coefficient and the defect aggregation coefficient; The pipeline defect index is calculated by the defect influence coefficient and the defect aggregation coefficient. The calculation formula of the pipeline defect index is as follows: K=ω1×K DI +ω2×K DA ; Where K DI Defect influence coefficient, K DA represents the defect aggregation coefficient, ω1 represents the defect impact weight, ω2 represents the defect aggregation weight, and K represents the pipeline defect index.

7. An ultrasonic phased array-based pipeline detection system, which is implemented based on an ultrasonic phased array-based pipeline detection method according to any one of claims 1 to 6, characterized in that: The system comprises: Information collection module, used to collect defect characteristic information and defect distribution information of volume defects in pipelines; A defect influence coefficient calculation module, used to perform defect feature analysis based on the defect feature information and determine the defect influence coefficient; A defect aggregation coefficient calculation module, used to determine the defect aggregation coefficient of the pipeline based on the defect distribution information; The pipeline defect index calculation module is used to determine the pipeline defect index through the defect influence coefficient and the defect aggregation coefficient, and issue a pipeline defect warning when the pipeline defect index is greater than a preset defect threshold.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the in-pipeline detection method based on ultrasonic phased array as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the in-pipeline detection method based on ultrasonic phased array as described in any one of claims 1 to 6.

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