Power station boiler pipeline creep damage state characterization method and device based on magnetoacoustic detection

Abstract

The invention provides a power station boiler pipeline creep damage state characterization method and device based on magnetoacoustic detection, and the method comprises the steps: obtaining samples in different creep damage states, and carrying out the magnetoacoustic detection of the samples to obtain corresponding original magnetoacoustic signals; de-noising processing and characteristic parameter extraction are carried out on the original magnetoacoustic signal, and a first characteristic parameter x and a second characteristic parameter y are extracted; constructing a nonlinear mapping relation between the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y, and solving a polynomial coefficient through an optimization algorithm, so that the comprehensive creep state parameter z is monotonically increased along with the creep damage state t; and performing normalization processing on the comprehensive creep state parameter z to form a creep state normalized calibration curve t = f (x, y) for realizing quantitative characterization of the creep damage state of the power station boiler pipeline. According to the method, the normalized calibration curve of the creep state can be constructed based on the magnetoacoustic detection characteristic parameters, and the creep damage state characterization of the power station boiler pipeline is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nondestructive testing of material damage, and in particular to a method and device for characterizing the creep damage state of a power station boiler pipeline based on magnetic acoustic detection. BACKGROUND

[0002] As a key power generation equipment of a power system, a supercritical power station boiler is long-term served in a complex environment of high pressure and high temperature, and is prone to creep damage, which causes hidden troubles for the safe operation of the power station. Magnetic acoustic emission, magnetic Barkhausen noise and other magnetic acoustic signals are sensitive to the microstructure changes caused by creep, and provide an effective means for creep damage detection and evaluation.

[0003] The magnetic acoustic detection method has advantages of non-contact and high sensitivity, but still has deficiencies in practical application. For example, most methods can only realize qualitative judgment of the trend of creep damage, and lack accurate quantitative mapping models. The selection of signal characteristic parameters lacks a unified standard, the evaluation results depend on artificial judgment, and the subjectivity is strong, which is difficult to meet the demand of accurate evaluation of in-service equipment SUMMARY

[0004] The present application aims to at least partially solve one of the problems in the related art.

[0005] To this end, a first object of the present application is to propose a method for characterizing the creep state of a power station boiler pipeline based on magnetic acoustic detection, to construct a creep state normalization calibration curve based on magnetic acoustic detection characteristic parameters, and to realize the characterization of the creep damage state of the power station boiler pipeline.

[0006] A second object of the present application is to propose a method for characterizing the creep state of a power station boiler pipeline based on magnetic acoustic detection.

[0007] A third object of the present application is to propose an electronic device.

[0008] A fourth object of the present application is to propose a computer-readable storage medium.

[0009] A fifth object of the present application is to propose a computer program product.

[0010] To achieve the above objects, a first aspect of the present application proposes a method for characterizing the creep state of a power station boiler pipeline based on magnetic acoustic detection, comprising:

[0011] Obtaining samples with different creep damage states, and performing magnetic acoustic detection on the samples to obtain corresponding original magnetic acoustic signals;

[0012] Performing denoising processing on the original magnetic acoustic signals, and extracting characteristic parameters from the denoised magnetic acoustic signals to extract first characteristic parameters x and second characteristic parameters y;

[0013] constructing a nonlinear mapping relationship of the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y, and solving polynomial coefficients through an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t;

[0014] normalizing the comprehensive creep state parameter z to form a creep state normalized calibration curve t=f(x, y), which is used to realize quantitative characterization of the creep damage state of the power plant boiler pipeline.

[0015] Optionally, the test samples of different creep damage states are obtained, and the test samples are subjected to magnetic acoustic detection to obtain corresponding original magnetic acoustic signals, and the method further comprises:

[0016] obtaining creep test samples of different creep damage states t k through a high-temperature creep test, wherein k=1, 2, …, N, t1=0% represents an undamaged state of an original test sample, and t N =100% represents a creep fracture state; the test sample material is the same as or similar in composition to the material of the power plant boiler pipeline;

[0017] magnetic acoustic detection is carried out on the test samples of different creep damage states by using a magnetic acoustic detection device, and magnetic acoustic signals are synchronously collected, wherein the magnetic acoustic signals include magnetic Barkhausen noise signals and magnetic acoustic emission signals.

[0018] Optionally, the original magnetic acoustic signals are subjected to denoising processing to extract the first characteristic parameter x and the second characteristic parameter y, and the method further comprises:

[0019] The magnetic Barkhausen noise signals and the magnetic acoustic emission signals are subjected to band-pass filtering, the square of the signals is calculated, the envelope line thereof is drawn by using a moving average method, and periodic waveforms with high similarity are filtered according to the Euclidean distance, so as to obtain an average envelope line;

[0020] The denoised magnetic acoustic signals are subjected to characteristic parameter extraction, representative characteristics of the magnetic acoustic signals are extracted, or the mean values of multiple characteristic parameters are subjected to principal component analysis, and the two most representative characteristic parameters are selected as the first characteristic parameter x and the second characteristic parameter y, wherein the representative characteristics include a peak value, energy, kurtosis, and skewness.

[0021] Optionally, the nonlinear mapping relationship of the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y is constructed, and polynomial coefficients are solved through an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t, and the method further comprises:

[0022] The polynomial expression of the comprehensive creep state parameter z is constructed as:

[0023] z=k1(x+b1) 2+k2(y+b2) 2 +k3(xy+b3) 2 +c

[0024] Wherein, k i , b i , c are polynomial coefficients to be solved, i = 1, 2, 3;

[0025] The objective function is set as:

[0026]

[0027] Wherein, λ is a smoothing regularization parameter, used to control the smoothness of the curve.

[0028] The objective function is optimized to obtain a set of optimal polynomial coefficients that make the parameter z monotonically increasing with respect to the creep damage state t.

[0029] Optionally, it further comprises:

[0030] Collecting the magnetoacoustic signals of the on-site pipeline to be measured, and extracting the first characteristic parameter x and the second characteristic parameter y thereof;

[0031] Substituting the first characteristic parameter x and the second characteristic parameter y of the magnetoacoustic signals of the on-site pipeline to be measured into the normalized calibration curve, the corresponding creep damage state t is calculated.

[0032] To achieve the above purpose, the second aspect embodiment of the present application proposes a creep damage state characterization device for power plant boiler pipeline based on magnetoacoustic detection, comprising:

[0033] A sample acquisition and detection module is used to acquire samples with different creep damage states, and to perform magnetoacoustic detection on the samples to obtain corresponding original magnetoacoustic signals;

[0034] A denoising and feature extraction module is used to perform denoising processing on the original magnetoacoustic signals, and to extract the first characteristic parameter x and the second characteristic parameter y from the denoised magnetoacoustic signals;

[0035] A nonlinear mapping construction and optimization module is used to construct a nonlinear mapping relationship between the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y, and to solve the polynomial coefficients through an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t;

[0036] A normalized curve generation module is used to normalize the comprehensive creep state parameter z to form a creep state normalized calibration curve t = f(x, y), which is used to realize quantitative characterization of the creep damage state of the power plant boiler pipeline.

[0037] To achieve the above object, the third aspect of the present application provides an electronic device, comprising: a processor, and a memory connected with the processor in communication;

[0038] The memory stores computer execution instructions.

[0039] The processor executes the computer execution instructions stored in the memory to realize the method according to any one of the first aspect.

[0040] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to realize the method according to any one of the first aspect.

[0041] To achieve the above object, the fifth aspect of the present application provides a computer program product, wherein the computer program is executed by a processor to realize the method according to any one of the first aspect.

[0042] The embodiments of the present application provide at least the following beneficial effects: the creep state normalization calibration curve can be constructed, and the creep damage state of the power plant boiler pipeline is characterized. Compared with the traditional detection technology, the method has the advantages of high sensitivity, multi-parameter fusion characterization, etc., and can efficiently evaluate the creep damage state during the shutdown of the power plant. The present application constructs the comprehensive creep state parameter and the normalization calibration curve, realizes the monotonic mapping of the creep damage state through the nonlinear polynomial fitting and the optimization algorithm, and improves the accuracy and interpretability of the creep damage state characterization. At the same time, the developed magnetic acoustic detection device has the advantages of modular structure and high integration, is convenient for field deployment and data reuse, and has a wide application prospect in the fields of intelligent operation and maintenance and non-destructive testing.

[0043] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following description and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0044] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description, taken in conjunction with the accompanying drawings, in which:

[0045] Figure 1 A flowchart of a power plant boiler pipeline creep damage state characterization method based on magnetic acoustic detection provided by the embodiments of the present application;

[0046] Figure 2 A structural schematic diagram of a power plant boiler pipeline creep damage state characterization device based on magnetic acoustic detection provided by the embodiments of the present application;

[0047] Figure 3 is a waveform diagram of the magnetic Barkhausen noise signal and magnetoacoustic emission signal measured in an experiment according to an embodiment of this application;

[0048] Figure 4 is a graph showing the variation of key feature parameters of magnetoacoustic signal with creep damage state according to an embodiment of this application.

[0049] Figure 5 The distribution diagrams of principal components 1 and 2 obtained from the principal component analysis of the magnetoacoustic signal characteristic parameters according to the embodiments of this application are shown.

[0050] Figure 6 This is a normalized calibration curve of the creep state according to an embodiment of this application;

[0051] Figure 7 This is a schematic diagram of a device for characterizing the creep damage state of power plant boiler pipes based on magnetoacoustic detection, provided in an embodiment of this application. Detailed Implementation

[0052] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0053] Figure 1 This is a schematic flowchart of a method for characterizing the creep damage state of power plant boiler pipelines based on magnetoacoustic detection, provided in an embodiment of the present invention.

[0054] like Figure 1 As shown, the method includes the following steps:

[0055] Step S1: Obtain samples with different creep damage states and perform magnetoacoustic detection on the samples to obtain the corresponding original magnetoacoustic signals.

[0056] In this embodiment of the invention, different creep damage states t are first obtained through high-temperature creep tests. k The creep specimens, where k = 1, 2, ..., N, t1 = 0% represents the original undamaged state of the specimen, t N =100% indicates creep rupture state. The material of the sample is the same as or similar in composition to the material of the power plant boiler pipes, with P92 heat-resistant steel being a common material.

[0057] For example, assuming N=6, t1=0% represents the original undamaged state of the sample, t6=100% represents the creep fracture state, corresponding to the creep life, and the remaining creep damage states are t2=20%, t3=40%, t4=60%, and t5=80%, respectively, corresponding to different stages of the creep life.

[0058] Next, the magnetic acoustic detection device is used to detect the samples with different creep damage states, and the magnetic acoustic signals are collected synchronously. The collected magnetic acoustic signals include two types: magnetic Barkhausen noise signals and magnetic acoustic emission signals. Specifically, the magnetic acoustic detection device used in the present application includes several key modules:

[0059] (1) Excitation signal generation module: composed of excitation device and power amplifier, used to generate a preset alternating excitation signal. The main function of this module is to excite the sample to produce magnetization effect.

[0060] (2) Joint magnetic acoustic signal pickup module: composed of magnetic core coil and acoustic emission sensor, used to collect magnetic Barkhausen noise and magnetic acoustic emission signals. Magnetic Barkhausen noise is caused by magnetic domain reversal in the material, while magnetic acoustic emission signal is generated when the material produces micro cracks or defects under external force.

[0061] (3) Signal processing module: this module includes preamplifier and filter components, used to amplify and filter the collected raw signals, so as to extract more accurate signal features.

[0062] (4) Signal analysis module: this module is responsible for denoising, feature extraction and creep damage state characterization of the processed signals. Through this analysis, accurate signal features can be provided for different creep damage states.

[0063] The structure diagram of the magnetic acoustic detection device is shown in Figure 2 The signal acquisition card is used to generate excitation signal, which drives the excitation coil to generate alternating excitation magnetic field after power amplification. When the sample is plate-shaped or large in size, U-shaped yoke with wound excitation coil is usually used for excitation to ensure effective magnetization of the target pipe section. By applying a sine wave or triangular wave alternating voltage with a frequency range of 1-50 Hz to the excitation coil, the magnetization of the sample is realized. At the same time, a 1Ω resistor is connected in series with the excitation coil to monitor the amplitude of the excitation current.

[0064] In actual test, the acoustic emission probe and the magnetic Barkhausen noise induction coil are placed on the surface of the sample to collect the required magnetic acoustic signals. These signals are processed through preamplifier, filter and other devices, and the subsequent signal processing and analysis are finally completed in the host computer software. Through this process, accurate magnetic acoustic signals can be obtained, providing necessary data support for the characterization of creep damage state.

[0065] Step S2, denoising the original magnetic acoustic signal, and extracting the first characteristic parameter x and the second characteristic parameter y from the denoised magnetic acoustic signal.

[0066] In step S2, the original magnetoacoustic signal is first denoised, the purpose is to improve the signal-to-noise ratio of the signal and extract useful characteristic parameters. Specifically, first, a 4th order Butterworth filter is used to band-pass filter the magnetic Barkhausen noise signal and the magnetoacoustic emission signal at 10kHz-200kHz. This filtering process helps to remove high-frequency noise and low-frequency interference signals, making the subsequent feature extraction more accurate.

[0067] In order to further remove noise and improve the signal-to-noise ratio of the signal, the present application adopts discrete wavelet transform to denoise the magnetoacoustic signal. Wavelet transform can effectively remove high-frequency noise in the signal while preserving the main features of the signal, thereby improving the signal quality.

[0068] In addition, in order to eliminate the influence of random fluctuations and environmental noise in the signal on the signal quality, the average envelope of the magnetoacoustic signal is drawn respectively. Specifically, by calculating the square of the signal and using the moving average method to draw its envelope, and then filtering the periodic waveforms with high similarity according to the Euclidean distance, a more smooth and representative average envelope is obtained. This processing process helps to better represent the useful information in the magnetoacoustic signal and reduce the influence of external interference. Figure 3 shows the magnetoacoustic signal obtained after band-pass filtering, Figure 3(a) is the magnetic Barkhausen noise signal, and Figure 3(b) is the magnetoacoustic emission signal.

[0069] After denoising, the next step is to extract the characteristic parameters. These characteristic parameters include but are not limited to the peak value, energy, kurtosis, skewness, etc. of the magnetoacoustic signal. By performing principal component analysis (PCA) on the mean values of multiple characteristic parameters, the two most representative characteristic parameters can be selected as the first characteristic parameter x and the second characteristic parameter y. Through PCA, the dimensionality can be effectively reduced, redundant information can be removed, and the main features of the signal can be preserved, thereby improving the accuracy of the analysis. Figures 4(a) and 4(b) show the kurtosis of the magnetic Barkhausen noise signal and the ringing count of the magnetoacoustic emission signal as the creep damage state changes. Figure 5 Figure 5 shows the data distribution of the first two principal components with the largest cumulative variance contribution rate, i.e. principal component 1 and principal component 2, reflecting the trend of signal characteristics under different creep damage states. Through the extraction and analysis of these characteristic parameters, the performance changes of the material under different creep damage states can be accurately represented.

[0070] Step S3, construct a nonlinear mapping relationship between the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y, and solve the polynomial coefficients through an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t.

[0071] In step S3, first, a nonlinear mapping relationship of the comprehensive creep state parameter z and the first characteristic parameter x and the second characteristic parameter y is constructed, aiming to obtain the comprehensive creep state parameter z related to the creep damage state t through the mapping of the characteristic parameters. In order to realize this nonlinear mapping relationship, the following polynomial expression is constructed:

[0072] z = k1(x + b1) 2 + k2(y + b2) 2 + k3(xy + b3) 2 + c

[0073] Wherein, k i , b i , c are polynomial coefficients to be solved, which need to be solved by optimization algorithm, i = 1, 2, 3.

[0074] In order to ensure that the comprehensive creep state parameter z monotonically increases with the creep damage state t, a target function is needed to guide the optimization process so that z monotonically increases and smoothly changes with t. The target function is as follows:

[0075]

[0076] Wherein, λ is a smoothing regularization parameter, used to control the smoothness of the curve, z k is the comprehensive creep state parameter calculated by the polynomial model, and t k is the actual creep damage state.

[0077] By minimizing the target function, a set of polynomial coefficients can be optimized and solved, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t, and changes smoothly. This process obtains the optimal solution through the optimization algorithm, so as to accurately represent the comprehensive performance change of the material under different creep damage states.

[0078] In step S4, the comprehensive creep state parameter z is normalized to form a creep state normalized calibration curve t = f(x, y), which is used to realize the quantitative characterization of the creep damage state of the power plant boiler pipeline.

[0079] In step S4, the comprehensive creep state parameter z is normalized. The purpose of normalization is to map the value of z to a standard interval, usually [0, 1], so as to realize the quantitative characterization of different creep damage states and facilitate comparison or analysis with other variables.

[0080] After normalizing the comprehensive creep state parameter z, a normalized calibration curve t = f(x, y) of the creep damage state can be obtained, which can be used to realize the quantitative characterization of the creep damage state of the power plant boiler pipeline.

[0081] The calibration curve obtained by normalization processing can clearly show the trend of creep damage state changing with x and y, and can quantitatively characterize the performance change of the material at different damage stages, thereby providing an important basis for health monitoring and maintenance of power plant boiler pipes.

[0082] As shown in Figure 6 The normalized creep state curve shows the relationship between t and the characteristic parameters x and y, which can effectively reflect the creep characteristics under different damage states and provide a precise quantitative analysis tool for practical application.

[0083] In the application process, first, the magnetic acoustic signal of the pipe to be tested on site is collected, and the first characteristic parameter x and the second characteristic parameter y are extracted according to the above steps S1 and S2. This process includes collecting the magnetic Barkhausen noise and the magnetic acoustic emission signal of the pipe to be tested, and then performing noise removal processing and feature extraction to obtain the characteristic parameters related to the damage state of the pipe.

[0084] When the power plant boiler is in a shutdown state, the target pipe section that needs to carry out creep damage detection is preprocessed. This preprocessing step is very critical, aiming to remove the influencing factors on the surface of the pipe, so that the subsequent detection results are more accurate. The specific preprocessing steps include:

[0085] (1) Remove the insulation layer: In order to avoid the interference of the insulation layer on the magnetic acoustic signal, the insulation layer of the target pipe section needs to be removed to ensure that the signal collection can truly reflect the internal condition of the pipe.

[0086] (2) Grind the oxidation layer on the surface of the pipe: The surface of the pipe may have an oxidation layer, which will affect the transmission and induction of the magnetic acoustic signal. Therefore, the oxidation layer on the surface of the pipe must be ground to ensure that the signal can accurately reflect the true state of the pipe material.

[0087] (3) Record and position mark the geometric appearance of the pipe section: In order to ensure the comparative analysis of the subsequent detection results, the geometric appearance of the pipe section must be recorded and position marked. This step facilitates consistent detection of the same pipe section in subsequent multiple detection processes, thereby achieving effective comparative analysis.

[0088] Once the preprocessing of the pipe is completed and the magnetic acoustic signal is collected, the next step is to extract the features of the collected magnetic acoustic signal to obtain the first characteristic parameter x and the second characteristic parameter y. These characteristic parameters are extracted from the magnetic Barkhausen noise signal and the magnetic acoustic emission signal, and are denoised and feature-extracted according to the previous step S2.

[0089] Finally, the first characteristic parameter x and the second characteristic parameter y of the to-be-tested pipeline are substituted into the calibration curve t = f(x, y) obtained by the normalization processing. Through this nonlinear mapping, the corresponding creep damage state t is calculated. The creep damage state t represents the damage degree of the pipeline at the current detection time, thereby providing a quantitative basis for the health assessment of the power plant boiler pipeline.

[0090] Through this method, the creep damage state of the field pipeline can be effectively detected and characterized, thereby providing important support for the maintenance and safe operation of the power plant boiler pipeline.

[0091] In order to realize the above-mentioned embodiment, the application further provides a creep damage state characterization device for a power plant boiler pipeline based on magnetic acoustic detection. Figure 7 A structure schematic diagram of a creep damage state characterization device for a power plant boiler pipeline based on magnetic acoustic detection provided by the embodiment of the application is shown in the figure. Figure 7 As shown in the figure, the device comprises:

[0092] A sample acquisition and detection module 100 is configured to acquire samples with different creep damage states and perform magnetic acoustic detection on the samples to obtain corresponding original magnetic acoustic signals;

[0093] A denoising and feature extraction module 200 is configured to perform denoising processing on the original magnetic acoustic signals and extract first characteristic parameters x and second characteristic parameters y from the denoised magnetic acoustic signals;

[0094] A nonlinear mapping construction and optimization module 300 is configured to construct a nonlinear mapping relationship between a comprehensive creep state parameter z and the first characteristic parameters x and the second characteristic parameters y, and solve polynomial coefficients through an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t;

[0095] A normalization curve generation module 400 is configured to perform normalization processing on the comprehensive creep state parameter z to form a creep state normalization calibration curve t = f(x, y) for realizing quantitative characterization of the creep damage state of the power plant boiler pipeline.

[0096] As to the device in the above-mentioned embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.

[0097] In order to realize the above-mentioned embodiment, the application further provides an electronic device, comprising a processor and a memory in communication connection with the processor; the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory to realize the method provided by the foregoing embodiment.

[0098] In order to achieve the above-mentioned embodiments, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are used to implement the method provided by the above-mentioned embodiments when executed by a processor.

[0099] In order to achieve the above-mentioned embodiments, the application further provides a computer program product, comprising a computer program, and the computer program is used to implement the method provided by the above-mentioned embodiments when executed by a processor.

[0100] The collection, storage, use, processing, transmission, provision and disclosure of the personal information of the user involved in the application comply with the relevant laws and regulations and do not violate public order and good customs.

[0101] It should be noted that the personal information from the user should be collected for legal and reasonable purposes and should not be shared or sold outside these legal uses. In addition, such collection / sharing should be carried out after the user's informed consent is received, including but not limited to informing the user to read the user agreement / user notice before the user uses the function, and signing the agreement / authorization including the authorization of the relevant user information. In addition, any necessary steps should be taken to protect and ensure access to such personal information data, and to ensure that other people with access to personal information data comply with their privacy policy and processes.

[0102] The application is expected to provide embodiments in which the user can selectively prevent the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk is minimized by limiting data collection and deleting data. In addition, such personal information is de-identified, if applicable, to protect the privacy of the user.

[0103] In the foregoing embodiment description, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0104] Moreover, the terms "first", "second", "third", etc. are used herein only to describe different steps or categories of steps in a claim for patent purposes, and are not to be construed as implying or implying relative importance or a number of indicated technical features. Thus, features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0105] Any process or method descriptions or descriptions of the flow diagrams described herein or otherwise described herein can be understood as representing the modules, segments or portions of code that include executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the present application includes additional implementations in which the order described or discussed is not the order in which the functions are performed, including functions performed in substantially simultaneous, or in reverse order, as will be understood by those skilled in the art of the embodiments of the present application.

[0106] The logic and / or steps represented in the flow diagrams or otherwise described herein, for example, can be considered as a list of executable instructions for implementing the logic function, which can be specifically embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor or other system that can take instructions from an instruction execution system, apparatus or device and execute them. For the purposes of this specification, "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate or transport a program for use by or in connection with an instruction execution system, apparatus or device or in conjunction with these instruction execution systems, apparatus or devices. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connections having one or more wires (electronic devices), portable computer diskette (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, as the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by editing, interpretation or necessary processing, if necessary, in other suitable manner, and then stored in computer memory.

[0107] It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. As such, in some embodiments, the steps or methods can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, a combination thereof, or the like.

[0108] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiment method can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium. When the programs are executed, one or a combination of the steps of the method embodiments is included.

[0109] In addition, each functional unit in each embodiment of the present application can be integrated into one processing module, or each unit can exist physically independently, or two or more units can be integrated into one module. The integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0110] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

[0111] It should be understood that various forms of flow shown above can be reordered, added or deleted steps. For example, each step described in the present application can be executed in parallel, sequentially or in different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0112] The above detailed description does not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and replacements can be made according to design requirements and other factors. Any modification, equivalent replacement and improvement within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for representing the creep damage state of a power plant boiler pipe based on magnetoacoustic detection, characterized in that, The method comprises the following steps: obtain samples with different creep damage states, and perform magnetic acoustic detection on the samples to obtain corresponding original magnetic acoustic signals; perform denoising processing on the original magnetic acoustic signals, and extract first characteristic parameters x and second characteristic parameters y from the denoised magnetic acoustic signals; construct a nonlinear mapping relationship between a comprehensive creep state parameter z and the first characteristic parameters x and the second characteristic parameters y, and solve polynomial coefficients by an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t; perform normalization processing on the comprehensive creep state parameter z to form a creep state normalization calibration curve t=f(x, y), which is used to realize quantitative characterization of the creep damage state of the power plant boiler pipeline.

2. The method of claim 1, wherein, The method for obtaining samples with different creep damage states and performing magnetic acoustic detection on the samples to obtain corresponding original magnetic acoustic signals further comprises the following steps: The creep samples in different creep damage states t k are obtained through high temperature creep test, wherein k = 1, 2, …, N, t1 = 0% represents an original sample undamaged state, t N = 100% represents a creep fracture state; the sample material is the same as or similar in composition to the power station boiler pipe material; perform magnetic acoustic detection on samples with different creep damage states by using a magnetic acoustic detection device, and synchronously collect magnetic acoustic signals, wherein the magnetic acoustic signals comprise magnetic Barkhausen noise signals and magnetic acoustic emission signals.

3. The method of claim 2, wherein, The method for performing denoising processing on the original magnetic acoustic signals and extracting first characteristic parameters x and second characteristic parameters y further comprises the following steps: perform band-pass filtering on the magnetic Barkhausen noise signals and the magnetic acoustic emission signals, calculate the square of the signals, draw envelope lines of the signals by using a moving average method, filter periodic waveforms with high similarity according to Euclidean distance, and obtain average envelope lines; extract characteristic parameters from the denoised magnetic acoustic signals, extract representative characteristics of the magnetic acoustic signals, or perform principal component analysis on the mean values of multiple characteristic parameters, select two most representative characteristic parameters as the first characteristic parameters x and the second characteristic parameters y, and the representative characteristics comprise peak value, energy, kurtosis, and skewness.

4. The method of claim 3, wherein, The method for constructing a nonlinear mapping relationship between a comprehensive creep state parameter z and the first characteristic parameters x and the second characteristic parameters y, and solving polynomial coefficients by an optimization algorithm, so that the comprehensive creep state parameter z monotonically increases with the creep damage state t further comprises the following steps: construct a polynomial expression of the comprehensive creep state parameter z as follows: z = k1(x + b1) 2 + k2(y + b2) 2 + k3(xy + b3) 2 + c wherein k i , b i , c are polynomial coefficients to be solved, i = 1, 2, 3; set a target function as follows: wherein λ is a smoothing regularization parameter, which is used to control the smoothing degree of the curve. perform optimization and solving on the target function to obtain a set of optimal polynomial coefficients, which make the parameter z monotonically increase with the creep damage state t.

5. The method of claim 4, wherein, The method further comprises the following steps: collect magnetic acoustic signals of a pipeline to be measured on site, and extract first characteristic parameters x and second characteristic parameters y therefrom; substitute the first characteristic parameters x and the second characteristic parameters y of the magnetic acoustic signals of the pipeline to be measured on site into the normalization calibration curve, and calculate a corresponding creep damage state t.

6. A device for representing the creep damage state of a power plant boiler pipe based on magnetoacoustic detection, characterized in that, The method comprises the following steps: a sample acquisition and detection module is configured to obtain samples with different creep damage states, and perform magnetic acoustic detection on the samples to obtain corresponding original magnetic acoustic signals; a denoising and characteristic extraction module is configured to perform denoising processing on the original magnetic acoustic signals, and extract first characteristic parameters x and second characteristic parameters y from the denoised magnetic acoustic signals; The nonlinear mapping construction and optimization module is configured to construct a nonlinear mapping relationship between a comprehensive creep state variable z and the first characteristic variable x and the second characteristic variable y, and solve polynomial coefficients through an optimization algorithm, so that the comprehensive creep state variable z monotonically increases with the creep damage state t; The normalization curve generation module is configured to normalize the comprehensive creep state variable z to form a creep state normalization calibration curve t=f(x, y), which is used to realize quantitative characterization of the creep damage state of the power plant boiler pipeline.

7. An electronic device, comprising: The method comprises the following steps: a processor, and a memory connected with the processor in communication; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by the processor to implement the method according to any one of claims 1-5.

9. A computer program product, characterised in that, The computer program is executed by the processor to implement the method according to any one of claims 1-5.

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