A fatigue damage location method and system for metal materials

Abstract

The present invention relates to the technical field of fatigue damage location, and provides a fatigue damage location method and system for metal materials, including: obtaining a nonlinear response signal on each sensing path of the metal material; performing Fourier transform on the nonlinear response signal, extracting the fundamental wave and the third harmonic, and calculating the third-order nonlinear coefficient based on the fundamental wave and the third harmonic; using the third-order nonlinear coefficient as a damage factor, combined with a probabilistic imaging algorithm, to obtain the probability of damage at each imaging point in the metal material, wherein the probability of damage at each imaging point is linearly superimposed by the probability of damage on all sensing paths. It has the advantages of small detection scale, wide range, strong anti-interference, etc.

Description

Technical Field

[0001] The invention belongs to the technical field of fatigue damage location, and in particular relates to a fatigue damage location method and system for metal materials. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Metal alloy materials are widely used in the field of advanced industrial major equipment. During the service of metal alloy material structures, under the action of fatigue loads, early fatigue damage is easily generated in the stress concentration area of ​​the structure, resulting in the gradual degradation of mechanical properties. If the safety and health status is not evaluated in time, the failure of the structure may cause major safety accidents. Therefore, the early fatigue damage detection of metal alloy material structures has important theoretical and engineering application significance.

[0004] At present, a variety of detection methods have been developed for fatigue damage of metal alloy material structures, such as acoustic emission detection technology, eddy current detection technology, infrared detection technology, penetration detection technology and ultrasonic detection technology.

[0005] Acoustic emission detection technology: The acoustic emission signal emitted by fatigue crack extension is used to evaluate material properties. This detection technology has high requirements for the detection location and is easily disturbed by environmental noise. Eddy current detection technology: The performance detection is completed by measuring the changes in the induced eddy currents in the structure. This detection technology has low efficiency, is difficult to meet the quantitative assessment of damage, and is only suitable for surface damage detection. Infrared detection technology: By radiating infrared heat energy outward, a temperature field is formed on the surface of the structure, and infrared detectors are used to complete thermal imaging of the surface of the structure. This detection technology is expensive and difficult to meet the damage detection inside the structure. Penetration detection technology: The penetrant is infiltrated into the fatigue damage of the structure, and the developer is used to infiltrate the penetrant to the surface to complete the detection. This detection technology is difficult to quantitatively detect damage and is prone to pollution.

[0006] Compared with the above detection technologies, ultrasonic detection technology has obvious advantages: strong penetration ability, which can be used for large-scale structural detection; secondly, ultrasonic waves are more sensitive to smaller damage and can detect the shape and size of damage; the operation process is relatively simple. The research on the state positioning of early fatigue damage of metal material structures based on nonlinear ultrasound is still in its initial stage. The development and improvement of non-destructive detection and evaluation methods for early fatigue damage of structures is of great significance for achieving full life coverage of structural service damage detection, ensuring safe and stable operation of structural performance and timely maintenance, reducing maintenance costs and extending service life. However, the current ultrasonic detection technology has a small detection range and poor anti-interference ability. Summary of the invention

[0007] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a fatigue damage location method and system for metal materials. The fundamental wave and third harmonic in the nonlinear response signal are extracted by Fourier transform, the nonlinear coefficient is calculated, and the third-order nonlinear coefficient is proposed as the damage factor. Combined with the probabilistic imaging algorithm, the accurate location of early fatigue damage is achieved, which has the advantages of small detection scale, wide range, and strong anti-interference.

[0008] In order to achieve the above object, the present invention adopts the following technical solution:

[0009] A first aspect of the present invention provides a fatigue damage location method for a metal material, comprising:

[0010] Obtaining nonlinear response signals on each sensing path of the metal material;

[0011] Performing Fourier transform on the nonlinear response signal, extracting the fundamental wave and the third harmonic, and calculating the third-order nonlinear coefficient based on the fundamental wave and the third harmonic;

[0012] The third-order nonlinear coefficient is used as the damage factor and combined with the probabilistic imaging algorithm to obtain the probability of damage at each imaging point in the metal material. The probability of damage at each imaging point is the linear superposition of the probabilities of damage on all sensing paths.

[0013] Furthermore, the nonlinear response signal is subjected to wavelet denoising and then Fourier transform.

[0014] Furthermore, the damage existence probability is expressed as:

[0015]

[0016]

[0017]

[0018] Among them, DI ij is the third-order nonlinear coefficient on the sensing path from the excitation source i to the receiving source j, (x, y) represents the coordinates of the imaging point, (x i ,y i ) represents the center position of the excitation source i, (x j ,y j ) represents the center position of the receiving source j, w is the scaling factor, and M represents the number of sensors.

[0019] Furthermore, the third-order nonlinear coefficient is:

[0020]

[0021] Where A1 is the fundamental amplitude and A3 is the third harmonic amplitude.

[0022] Furthermore, M piezoelectric sensors are arranged on the surface of the metal material to generate M×(M-1) sensing paths.

[0023] Furthermore, each piezoelectric sensor can act as both an excitation source and a receiving source.

[0024] A second aspect of the present invention provides a fatigue damage location system for metal materials, comprising:

[0025] A signal acquisition module, which is configured to: acquire a nonlinear response signal on each sensing path of the metal material;

[0026] A calculation module is configured to: perform Fourier transform on the nonlinear response signal, extract the fundamental wave and the third harmonic, and calculate the third-order nonlinear coefficient based on the fundamental wave and the third harmonic;

[0027] The positioning module is configured to: use the third-order nonlinear coefficient as a damage factor, combine it with a probabilistic imaging algorithm, and obtain the probability of damage at each imaging point in the metal material, wherein the probability of damage at each imaging point is a linear superposition of the probabilities of damage on all sensing paths.

[0028] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the fatigue damage location method for metal materials as described above.

[0029] The fourth aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in a method for locating fatigue damage in metal materials as described above are implemented.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention provides a fatigue damage location method for metal materials. The method extracts the fundamental wave and the third harmonic in the nonlinear response signal through Fourier transform, calculates the nonlinear coefficient, proposes the third-order nonlinear coefficient as the damage factor, and combines the probabilistic imaging algorithm to achieve accurate location of early fatigue damage. The method has the advantages of small detection scale, wide range, strong anti-interference, etc.

[0032] The present invention provides a fatigue damage location method for metal materials, which is based on nonlinear early fatigue damage location based on third harmonic phase velocity matching. The third-order nonlinear coefficient is more sensitive to early fatigue damage of structural components, which is of great significance for ensuring the safe operation and timely maintenance of industrial equipment, thereby reducing maintenance (or repair) costs and prolonging life. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0034] Figure 1 This is a flow chart of a fatigue damage location method for metal materials according to the first embodiment of the present invention;

[0035] FIG2( a ) is an example diagram of the phase velocity of the third harmonic S1-S3 mode pair of the dispersion curve of the first embodiment of the present invention;

[0036] FIG2( b ) is an example diagram of the group velocity of the third harmonic S1-S3 mode pair of the dispersion curve of the first embodiment of the present invention;

[0037] Figure 3 is a schematic diagram of a damage location sensing path according to the first embodiment of the present invention;

[0038] Figure 4 It is a schematic diagram of the standard test piece dimensions of Example 1 of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0040] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0041] Embodiment 1

[0042] This embodiment provides a fatigue damage location method for metal materials, which specifically includes the following steps:

[0043] Step 1: Study the propagation characteristics and fatigue damage characterization of ultrasonic guided waves in aluminum alloy materials, such as Figure 1 As shown, including:

[0044] (1) The dispersion curves are plotted from the dispersion equation, as shown in Figure 2(a) and Figure 2(b). It can be seen from the dispersion curves that the S1 mode and the S3 mode meet the phase velocity matching, and the phase velocity is 6.356 km / s. The frequency-thickness product of the S1 mode is 3.57 MHz·mm, and the frequency-thickness product of the S3 mode is 10.71 MHz·mm.

[0045] The dispersion equation is:

[0046]

[0047] Among them, +1 represents the symmetric S mode, -1 represents the antisymmetric A mode, h is the plate thickness, k is the wave number, c is L With c T are the longitudinal and shear wave velocities, respectively.

[0048] (2) By performing FFT transformation on the response signal, the fundamental wave and third harmonic amplitudes are extracted to solve the third-order nonlinear coefficient, which is the early fatigue damage representation:

[0049]

[0050] Where A1 is the fundamental amplitude and A3 is the third harmonic.

[0051] The sensor network consists of M piezoelectric sensors, covering the entire detection area. Each sensor can be used as both an excitation source and a receiving source, thus generating M×(M-1) sensing paths. When damage occurs in the material structure, the nonlinear damage coefficient (third-order nonlinear coefficient) will change. Therefore, the nonlinear response signal on the sensing path is used to predict whether there is damage on and near the sensing path. Within the detection area of ​​the sensor network, the probability of damage at a certain point in the metal material structure can be linearly superimposed by the probability of damage on all sensing paths. The probability of damage at the detection area coordinate (x, y) can be expressed as:

[0052]

[0053] Among them, p ij (x, y) is the estimated probability of damage on the sensing path from the excitation source i to the sensor (receiving source) j, DI ij is the signal nonlinear coefficient (third-order nonlinear coefficient) γ on this path, is a non-negative linear distribution function, and the function R is defined as:

[0054]

[0055] in,

[0056]

[0057] Among them, RD ij (x,y) represents the distance from the imaging point (x,y) to the center of the excitation source (x i ,y i ) and the sensor center position (x j ,y j ) and the ratio of the distance from the center of the excitation source to the center of the sensor; w is the scaling factor used to control the size of the area affected by the excitation-receiving path; when RD ij When (x, y) = 1, the imaging point (x, y) is directly located on the excitation-reception path, P ij (x,y)=DI ij ; When RD ij When (x, y) = w, the imaging point (x, y) is located at the edge of the ellipse, P ij (x,y)=0.

[0058] Step 2: Prepare fatigue damage specimens, optimize sensor layout, and build a nonlinear ultrasonic detection system.

[0059] (1) Build a nonlinear ultrasonic testing system. The nonlinear ultrasonic testing system mainly consists of an early fatigue damage specimen (metal material), several (6) piezoelectric ceramic sensors PZT, a high-power waveform generator, a 50 ohm resistor, a 6 dB attenuator, and an oscilloscope. Figure 3 As shown, when PZT1 and PZT2 are used as excitation sensors, PZT4, PZT5, and PZT6 are used as receiving sensors, and when PZT4 and PZT5 are used as excitation sensors, PZT1, PZT2, and PZT3 are used as receiving sensors. The excitation sensor, 6dB attenuator, 50 ohm resistor, and high-power waveform generator are connected in sequence, and the receiving sensor, high-power waveform generator, and oscilloscope are connected in sequence.

[0060] (2) Preparation of test specimens: Fatigue test specimens were prepared using a fatigue testing machine with a maximum force of 32 kN, a stress ratio of 0.1, and a loading frequency of 15 Hz.

[0061] (3) Optimize the sensor layout and use epoxy resin AB glue to stick the piezoelectric ceramic sensor on the surface of the specimen. The sticking position and size are as follows: Figure 4 As shown, the sensors are pasted on both sides of the semicircular arc, with an interval of 12 cm on the opposite side and 1 cm between the sensors on the same side.

[0062] Step 3: Conduct nonlinear ultrasonic testing experiments.

[0063] (1) According to the material mechanical properties of aluminum alloy, fatigue loading conditions are set. Two standard specimens are numbered T1 and T2. Standard specimen T1 is taken to carry out fatigue test. Fatigue loading is applied until the specimen breaks. The number of fatigue loading times is the total fatigue life.

[0064] (2) Fatigue specimen T2 was prefabricated and fatigue loaded in stages. The fatigue life was limited to 80%-90%. Specimens with two damage states were prepared. Nonlinear ultrasonic damage location detection was performed in each fatigue stage, and nonlinear response signals were obtained using an oscilloscope.

[0065] (3) The nonlinear response signal on each sensing path of the metal material obtained in (2) is subjected to wavelet noise reduction processing, and then the nonlinear response signal is subjected to Fourier transform to obtain the fundamental wave A1 and the third harmonic A3, which are substituted into formula (2) to obtain the third-order nonlinear coefficient.

[0066] (4) The third-order nonlinear coefficient is selected as the damage factor. Combining formula (3), formula (4) and formula (5), an early fatigue damage location method is proposed based on the third-order nonlinear coefficient combined with the probabilistic imaging algorithm to obtain the probability of damage at each imaging point in the metal material (specimen).

[0067] The present invention is based on the dispersion curve of ultrasonic guided waves, utilizes the third harmonic phase velocity matching mode of ultrasonic guided waves, extracts the fundamental wave and third harmonic in the nonlinear response signal through Fourier transform, calculates the nonlinear coefficient, and proposes the third-order nonlinear coefficient as the damage factor. Combined with the probabilistic imaging algorithm, the accurate positioning of early fatigue damage is achieved, which has the advantages of small detection scale, wide range, and strong anti-interference.

[0068] The present invention mainly comprises: according to the propagation law of ultrasonic guided waves in aluminum alloy structural materials, by analyzing the dispersion curve of ultrasonic guided waves, a mode matching the phase velocity of the fundamental wave and the third harmonic is obtained as an excitation signal; the structure to be tested is designed, early damage is prepared by a fatigue testing machine, the sensor layout is optimized, and a nonlinear ultrasonic detection system is built; the excitation parameters are determined, and the frequency of the excitation signal is determined according to the size of the structure to be tested; ultrasonic experiments are carried out on early fatigue damage under two states to obtain a "transmit-receive" response signal; a noise reduction analysis is performed on the response signal, and then the fundamental wave and the third harmonic are extracted through Fourier transform, and the third-order nonlinear coefficient is calculated; the nonlinear coefficient is selected as the damage factor, and a method for locating early fatigue damage is proposed in combination with a probabilistic imaging algorithm.

[0069] Based on the probabilistic imaging algorithm, the present invention studies two different types of fatigue damage locations, proposes a damage probability imaging algorithm with a third-order nonlinear coefficient as a damage factor, designs fatigue specimens with two different initial states, and completes the location of fatigue damage in different states; it is suitable for early fatigue state monitoring of key components of large equipment.

[0070] The present invention is based on the nonlinear early fatigue damage positioning of third harmonic phase velocity matching. At the same time, the third-order nonlinear coefficient is more sensitive to the early fatigue damage of structural components, which is of great significance for ensuring the safe operation and timely maintenance of industrial equipment, thereby reducing maintenance (or repair) costs and prolonging.

[0071] Embodiment 2

[0072] This embodiment provides a fatigue damage location system for metal materials, which specifically includes:

[0073] A signal acquisition module, which is configured to: acquire a nonlinear response signal on each sensing path of the metal material;

[0074] A calculation module is configured to: perform Fourier transform on the nonlinear response signal, extract the fundamental wave and the third harmonic, and calculate the third-order nonlinear coefficient based on the fundamental wave and the third harmonic;

[0075] The positioning module is configured to: use the third-order nonlinear coefficient as a damage factor, combine it with a probabilistic imaging algorithm, and obtain the probability of damage at each imaging point in the metal material, wherein the probability of damage at each imaging point is a linear superposition of the probabilities of damage on all sensing paths.

[0076] It should be noted here that each module in this embodiment corresponds to each step in Example 1 one by one, and the specific implementation process is the same, which will not be repeated here.

[0077] Embodiment 3

[0078] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the fatigue damage location method for metal materials described in the first embodiment are implemented.

[0079] Embodiment 4

[0080] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in a fatigue damage location method for metal materials as described in the first embodiment are implemented.

[0081] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program codes.

[0082] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0085] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0086] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A fatigue damage location method for metal materials, characterized in that: include: Obtaining nonlinear response signals on each sensing path of the metal material; Performing Fourier transform on the nonlinear response signal, extracting the fundamental wave and the third harmonic, and calculating the third-order nonlinear coefficient based on the fundamental wave and the third harmonic; The third-order nonlinear coefficient is used as the damage factor and combined with the probabilistic imaging algorithm to obtain the probability of damage at each imaging point in the metal material. The probability of damage at each imaging point is linearly superimposed by the probability of damage on all sensing paths; specifically: M piezoelectric sensors are set on the surface of the metal material to generate M×(M-1) sensing paths; When damage occurs in the material structure, the third-order nonlinear coefficient will change; the nonlinear response signal on the sensing path is used to predict whether there is damage on and near the sensing path; within the sensor network detection area, the probability of damage at a certain point in the metal material structure is linearly superimposed by the probability of damage on all sensing paths, and the probability of damage at the detection area coordinate (x, y) is expressed as: Among them, p ij (x, y) is the estimated probability of damage on the sensing path from the excitation source i to the sensor receiving source j, DI ij is the third-order nonlinear coefficient γ of the signal on this path; The damage existence probability is expressed as: Among them, DI ij is the third-order nonlinear coefficient on the sensing path from excitation source i to receiving source j, (x, y) represents the coordinates of the imaging point, (xi, yi) represents the center position of excitation source i, (x j ,y j ) represents the center position of the receiving source j, w is the scaling factor, and M represents the number of sensors.

2. A fatigue damage location method for metal materials according to claim 1, characterized in that: After the nonlinear response signal is processed by wavelet denoising, Fourier transform is performed.

3. A fatigue damage location method for metal materials according to claim 1, characterized in that: The third-order nonlinear coefficient is: Where A1 is the fundamental amplitude and A3 is the third harmonic.

4. A fatigue damage location method for metal materials according to claim 1, characterized in that: Each piezoelectric sensor can act as both an excitation source and a receiving source.

5. A fatigue damage location system for metal materials, based on a fatigue damage location method for metal materials as claimed in any one of claims 1 to 4, characterized in that: include: A signal acquisition module, which is configured to: acquire a nonlinear response signal on each sensing path of the metal material; A calculation module is configured to: perform Fourier transform on the nonlinear response signal, extract the fundamental wave and the third harmonic, and calculate the third-order nonlinear coefficient based on the fundamental wave and the third harmonic; The positioning module is configured to: use the third-order nonlinear coefficient as a damage factor, combine it with a probabilistic imaging algorithm, and obtain the probability of damage at each imaging point in the metal material, wherein the probability of damage at each imaging point is a linear superposition of the probabilities of damage on all sensing paths.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of a fatigue damage location method for metal materials as described in any one of claims 1 to 4 are implemented.

7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the fatigue damage location method for metal materials as described in any one of claims 1 to 4 are implemented.

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