Ultrasonic guided wave detection method suitable for fatigue crack of immersion structure

Abstract

The invention relates to an ultrasonic guided wave detection method suitable for fatigue cracks of an immersion structure, and belongs to the field of ultrasonic guided wave detection of material defects. The method specifically comprises the following steps: acquiring a time-frequency ridge line of an effective signal in an ultrasonic guided wave signal by adopting a TFMST method; all time-frequency ridge lines of the effective signals are obtained repeatedly; setting any two intersected time-frequency ridge lines as # imgabs0 # and # imgabs1 # respectively, and determining an intersection interval between the time-frequency ridge line # imgabs2 # and the time-frequency ridge line # imgabs3 #; reconstructing the time-frequency ridge line in each intersection interval; time-frequency ridge line extraction of effective signals in the ultrasonic guided wave signals is completed, an accurate ultrasonic time-frequency representation result is obtained, and accurate identification of crack positions in an immersed structure is achieved; according to the method, a method of combining time-frequency multi-compression transformation (TFMST) and ridge line path recombination (RPRG) is used for processing non-stationary ultrasonic guided wave signals, clear time-frequency characteristics can be extracted from the non-stationary signals, and therefore the condition of fatigue cracks can be accurately recognized.

Description

Technical Field

[0001] The invention belongs to the field of ultrasonic guided wave detection of material defects and relates to an ultrasonic guided wave detection method suitable for fatigue cracks of immersed structures. Background Art

[0002] Submerged structures refer to structures such as buildings, bridges, docks, offshore platforms, ships, tanks, etc. that are partially or completely covered by liquids (such as water, fuel, etc.). Such structures have very important applications and significance in modern engineering. However, in actual working environments, due to external loads, defects or inhomogeneities in materials, long-term use and environmental corrosion, etc., stress concentration and fatigue damage will occur in submerged structures, eventually leading to cracks. If they are not discovered and repaired in time, they may lead to further damage to the structure, causing serious safety accidents and economic losses.

[0003] Ultrasonic guided wave testing technology is a non-destructive testing method that can perform testing without affecting the structural integrity. It can also detect tiny cracks and defects. In addition, ultrasonic guided wave testing technology can realize quantitative analysis and positioning detection, helping to find fatigue cracks impatiently. Therefore, it is widely used in fatigue crack detection of immersed parts.

[0004] Ultrasonic guided wave signals usually have the characteristics of time-frequency intersection, non-stationarity and sparsity, that is, the frequency characteristics of the signal change with time, and its frequency components change with time. For such signals, traditional spectrum analysis methods may not be able to accurately describe the time-frequency characteristics of the signal. Therefore, it is necessary to use time-frequency analysis methods to analyze the signal in both the time domain and the frequency domain, such as short-time Fourier transform, continuous wavelet transform, etc. However, traditional time-frequency analysis methods cannot obtain clear resolution in both the time and frequency domains, that is, problems such as energy divergence and modal aliasing occur, which will lead to inaccurate identification of crack locations in immersed structures. Therefore, how to extract clear time-frequency diagrams for signal analysis is an important prerequisite for accurately identifying defect information in structures.

[0005] In order to overcome the problem of poor resolution in time-frequency analysis, many scholars have proposed the use of Wigner-ville distribution (WVD) to extract time-frequency components in signals. WVD can capture subtle time-frequency changes and improve its resolution. However, the cross-term interference generated when calculating the time-frequency representation will cause additional interference components in the time-frequency analysis, reducing the accuracy of the analysis. Based on WVD, many different improvement methods have been proposed, among which the typical methods are pseudo WVD (PWVD), smoothed PWVD, S transform, etc. However, WVD-based methods usually cannot reduce the interference of cross-terms while ensuring high time-frequency resolution. Summary of the invention

[0006] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and propose an ultrasonic guided wave detection method suitable for fatigue cracks of immersed structures, and to use a method combining time-frequency multi-compression transform (TFMST) and ridge path reconstruction (RPRG) to process non-stationary ultrasonic guided wave signals, so as to extract clear time-frequency features from the non-stationary signals, thereby realizing accurate identification of fatigue cracks.

[0007] The solution of the present invention is:

[0008] An ultrasonic guided wave detection method for fatigue cracks of immersed structures, comprising:

[0009] The TFMST method is used to obtain a time-frequency ridge line of the effective signal in the ultrasonic guided wave signal; all time-frequency ridge lines of the effective signal are repeatedly obtained;

[0010] Assume that any two intersecting time-frequency ridges are and Determine time-frequency ridges and time-frequency ridges The intersection interval of

[0011] Reconstruct the time-frequency ridges in each intersection interval;

[0012] The time-frequency ridge extraction of effective signals in ultrasonic guided wave signals is completed, and accurate ultrasonic time-frequency representation results are obtained to achieve accurate identification of crack locations in immersed structures.

[0013] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, the method for determining the intersection interval is:

[0014] Set the previous sampling time to The next sampling time is

[0015] When the inequality is satisfied:

[0016]

[0017]

[0018] Where D f is the preset separation distance;

[0019] F s is the sampling frequency;

[0020] Then determine the time interval Time-frequency ridge and The intersection interval of

[0021] Repeat the above method to determine the time-frequency ridge and time-frequency ridges All intersection intervals of .

[0022] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, two intersecting time-frequency ridges and There are 1 or more intersecting intervals.

[0023] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, and There are one or more intersection points in any intersection interval of .

[0024] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, the method for reconstructing the time-frequency ridges in the intersection interval is:

[0025] S31, deleting the original time-frequency ridges in the intersecting intervals;

[0026] S32. Reconnect the time-frequency ridges according to the rate of change of the time-frequency ridges in the intersection interval.

[0027] In the above-mentioned ultrasonic guided wave detection method applicable to fatigue cracks of immersed structures, in S32, the method of reconnecting the time-frequency ridge line is:

[0028] S321, calculate the time-frequency ridge line at middle The slope at

[0029] S322, calculate the time-frequency ridge line at middle The slope at

[0030] S323, calculate the time-frequency ridge line and The connection matrix CM of the i-th time interval (i) (m,n);

[0031] S324, from the connection matrix CM (i) Find the position of the smallest element in (m,n) a ,n a ); when a=1, the interval The time-frequency ridges in With interval The time-frequency ridges in Have the same rate of change; use high-order interpolation method to reconstruct the time-frequency ridges and complete the first pair of time-frequency ridges and connection;

[0032] S325, CM (i) All elements of the m1th row and all elements of the n1th column are set to infinity; let a=2, ..., I, repeat S324, connect other time-frequency ridges in the intersection interval, and obtain the reconstructed time-frequency ridges.

[0033] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, in S321, the slope The calculation method is:

[0034]

[0035] In the formula, is the kth time-frequency ridge in the i-th time interval;

[0036] Time-frequency ridge exist The slope of the moment;

[0037] Δt is the preset time increment.

[0038] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, in S322, the slope The calculation method is:

[0039]

[0040] In the formula, is the kth time-frequency ridge in the i-th time interval;

[0041] Time-frequency ridge exist The slope of the moment;

[0042] Δt is the preset time increment.

[0043] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, in S323, the connection matrix CM (i) (m,n) is:

[0044]

[0045] Where m is the connection matrix CM (i) The number of rows in (m,n);

[0046] n is the connection matrix CM (i) The number of columns of (m,n);

[0047] I The number of intersecting time-frequency ridges within the range.

[0048] In the above-mentioned ultrasonic guided wave detection method for fatigue cracks of immersed structures, in S324, the position of the minimum element (m a ,n a ) is calculated as:

[0049]

[0050] The beneficial effects of the present invention compared with the prior art are:

[0051] (1) The present invention proposes a multiple compression ridge reconstruction method to improve the time resolution and frequency resolution of the time-frequency ridge, solving the problem of large ridge error when multiple components are superimposed;

[0052] (2) The present invention verifies the ability of the multiple compression ridge reconstruction method to improve the accuracy of ridge extraction and the ability to process time-frequency cross signals by using two simulation signals and experiments;

[0053] (3) The present invention applies the multiple compressed ridge reconstruction method to the reflected wave signal of ultrasonic guided waves of immersed structures. The results show that this method can effectively process signals with characteristics such as time-frequency intersection, non-stationarity and sparsity, which provides a powerful signal processing method for fatigue crack detection of immersed structures based on ultrasonic guided waves. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of ultrasonic guided wave detection of the present invention;

[0055] Figure 2 It is a schematic diagram of the existence of multiple intersection intervals of two intersecting time-frequency ridge lines of the present invention;

[0056] Figure 3 It is a schematic diagram that there are one or more intersection points in each intersection interval of the present invention. DETAILED DESCRIPTION

[0057] The present invention will be further described below in conjunction with the embodiments.

[0058] The present invention provides an ultrasonic guided wave detection method suitable for fatigue cracks of immersed structures. A method combining time-frequency multi-compression transform (TFMST) and ridge path reorganization (RPRG) is used to process non-stationary ultrasonic guided wave signals, so as to extract clear time-frequency features from the non-stationary signals, thereby realizing accurate identification of fatigue cracks.

[0059] Ultrasonic guided wave detection method for fatigue cracks in submerged structures, such as Figure 1 As shown, the specific steps include:

[0060] The TFMST method is used to obtain a time-frequency ridge line of the effective signal in the ultrasonic guided wave signal; all time-frequency ridge lines of the effective signal are obtained repeatedly.

[0061] Assume that any two intersecting time-frequency ridges are and Determine time-frequency ridges and time-frequency ridges The intersection interval.

[0062] The intersection interval is determined as follows:

[0063] Set the previous sampling time to The next sampling time is

[0064] When the inequality is satisfied:

[0065]

[0066] and

[0067] Where D f is the preset separation distance;

[0068] F s is the sampling frequency;

[0069] Then determine the time interval Time-frequency ridge and The intersection interval of

[0070] Repeat the above method to determine the time-frequency ridge and time-frequency ridges All intersection intervals of .

[0071] Two intersecting time-frequency ridges and There are 1 or more intersecting intervals, such as Figure 2 As shown. and In any intersection interval of , there are one or more intersection points, such as Figure 3 shown.

[0072] The time-frequency ridges in each intersection interval are reconstructed.

[0073] The method for reconstructing the time-frequency ridges in the intersection interval is:

[0074] S31. Delete the original time-frequency ridges in the intersection interval.

[0075] S32. Reconnect the time-frequency ridges according to the rate of change of the time-frequency ridges in the intersection interval.

[0076] The method to reconnect the time-frequency ridges is:

[0077] S321, calculate the time-frequency ridge line at middle The slope at

[0078] Slope The calculation method is:

[0079]

[0080] In the formula, is the kth time-frequency ridge in the i-th time interval;

[0081] Time-frequency ridge exist The slope of the moment;

[0082] Δt is the preset time increment.

[0083] S322, calculate the time-frequency ridge line at middle The slope at

[0084] Slope The calculation method is:

[0085]

[0086] In the formula, is the kth time-frequency ridge in the i-th time interval;

[0087] Time-frequency ridge exist The slope of the moment;

[0088] Δt is the preset time increment.

[0089] S323, calculate the time-frequency ridge line and The connection matrix CM of the i-th time interval (i) (m,n).

[0090] Connection Matrix CM (i) (m,n) is:

[0091]

[0092] Where m is the connection matrix CM (i) The number of rows in (m,n);

[0093] n is the connection matrix CM (i) The number of columns of (m,n);

[0094] I The number of intersecting time-frequency ridges within the range.

[0095] S324, from the connection matrix CM (i) Find the position of the smallest element in (m,n) a ,n a ); when a=1, the interval The time-frequency ridges in With interval The time-frequency ridges in Have the same rate of change; use high-order interpolation method to reconstruct the time-frequency ridges and complete the first pair of time-frequency ridges and connection.

[0096] The position of the smallest element (m a ,n a ) is calculated as:

[0097]

[0098] S325, CM (i) All elements of the m1th row and all elements of the n1th column are set to infinity; let a=2, ..., I, repeat S324, connect other time-frequency ridges in the intersection interval, and obtain the reconstructed time-frequency ridges.

[0099] The time-frequency ridge extraction of effective signals in ultrasonic guided wave signals is completed, and accurate ultrasonic time-frequency representation results are obtained to achieve accurate identification of crack locations in immersed structures.

[0100] The RPRG algorithm proposed in this patent can effectively identify these cross components by considering the rate of change of the ridge curve. In order to reduce the interference of noise, the least squares fitting of the Fourier model can further smooth the extracted instantaneous frequency. After extracting the instantaneous frequency, the components of the signal are separated by ICCD. The results show that this method can correctly track the instantaneous frequency in the signal and successfully extract all components, so it is more superior when the components cross the signal.

[0101] In order to further compare the analysis results of different time-frequency analysis methods and time-frequency post-processing methods, their Rayleigh entropies are calculated. Rayleigh entropy is an objective indicator for evaluating the energy concentration of time-frequency results. The lower the Rayleigh entropy value, the more concentrated the energy of the time-frequency representation under this method. The corresponding Rayleigh entropy is shown in Table 1. It can be seen that the TFMST result in this patent has a lower Rayleigh entropy, which indicates that it can generate a time-frequency representation with concentrated energy. Although MSST and STET have lower Rayleigh entropy values, the complete signal components cannot be identified in their time-frequency representation. It can be concluded that whether from the quantized Rayleigh entropy or the observed time-frequency representation results, it can be shown that TFMST can produce the most energy-concentrated and more advantageous time-frequency representation.

[0102] Table 1 Rayleigh entropy analysis results

[0103]

[0104] The present invention proposes a multiple compression ridge reconstruction method for improving the time resolution and frequency resolution of time-frequency ridges, and solves the problem of large ridge errors when multiple components are superimposed.

[0105] The present invention verifies the ability of the multiple compression ridge reconstruction method to improve the accuracy of ridge extraction and the ability to process time-frequency cross signals by two simulation signals and experiments.

[0106] The present invention applies the multiple compressed ridge reconstruction method to the reflected wave signal of ultrasonic guided waves of immersed structures. The results show that this method can effectively process signals with the characteristics of time-frequency intersection, non-stationarity and sparsity, which provides a powerful signal processing means for fatigue crack detection of immersed structures based on ultrasonic guided waves.

[0107] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. An ultrasonic guided wave detection method for fatigue cracks in submerged structures, characterized in that: include: The TFMST method is used to obtain a time-frequency ridge line of the effective signal in the ultrasonic guided wave signal; Repeat to obtain all time-frequency ridges of the valid signal; Assume that any two intersecting time-frequency ridges are and Determine time-frequency ridges and time-frequency ridges The intersection interval of Reconstruct the time-frequency ridges in each intersection interval; The time-frequency ridge extraction of effective signals in ultrasonic guided wave signals is completed, and accurate ultrasonic time-frequency representation results are obtained to achieve accurate identification of crack locations in immersed structures.

2. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 1, characterized in that: The intersection interval is determined as follows: Set the previous sampling time to The next sampling time is When the inequality is satisfied: Where D f is the preset separation distance; F s is the sampling frequency; Then determine the time interval Time-frequency ridge and The intersection interval of Repeat the above method to determine the time-frequency ridge and time-frequency ridges All intersection intervals of .

3. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 2, characterized in that: Two intersecting time-frequency ridges and There are 1 or more intersecting intervals.

4. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 3, characterized in that: exist and There are one or more intersection points in any intersection interval of .

5. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 2, characterized in that: The method for reconstructing the time-frequency ridges in the intersection interval is: S31, deleting the original time-frequency ridges in the intersecting intervals; S32. Reconnect the time-frequency ridges according to the rate of change of the time-frequency ridges in the intersection interval.

6. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 5, characterized in that: In S32, the method of reconnecting the time-frequency ridge line is: S321, calculate the time-frequency ridge line at middle The slope at S322, calculate the time-frequency ridge line at middle The slope at S323, calculate the time-frequency ridge line and The connection matrix CM of the i-th time interval (i) (m,n); S324, from the connection matrix CM (i) Find the position of the smallest element in (m,n) a ,n a ); when a=1, the interval The time-frequency ridges in With interval The time-frequency ridges in Have the same rate of change; use high-order interpolation method to reconstruct the time-frequency ridges and complete the first pair of time-frequency ridges and connection; S325, CM (i) All elements of the m1th row and all elements of the n1th column are set to infinity; let a=2, ..., I, repeat S324, connect other time-frequency ridges in the intersection interval, and obtain the reconstructed time-frequency ridges.

7. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 6, characterized in that: In S321, the slope The calculation method is: In the formula, is the kth time-frequency ridge in the i-th time interval; Time-frequency ridge In t s The slope of the moment; Δt is the preset time increment.

8. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 6, characterized in that: In S322, the slope The calculation method is: In the formula, is the kth time-frequency ridge in the i-th time interval; Time-frequency ridge exist The slope of the moment; Δt is the preset time increment.

9. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 6, characterized in that: In S323, the connection matrix CM (i) (m,n) is: Where m is the connection matrix CM (i) The number of rows in (m,n); n is the connection matrix CM (i) The number of columns of (m,n); I The number of intersecting time-frequency ridges within the range.

10. The ultrasonic guided wave detection method for fatigue cracks of submerged structures according to claim 6, characterized in that: In S324, the position of the minimum element (m a ,n a ) is calculated as:

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