CN110726538B - Transverse crack characteristic identification and extraction method of stepped cylindrical shaft elastic wave signal - Google Patents
Transverse crack characteristic identification and extraction method of stepped cylindrical shaft elastic wave signal Download PDFInfo
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Abstract
The invention discloses a transverse crack characteristic identification and extraction method of a stepped cylindrical shaft elastic wave signal. The existing analysis method of the elastic wave signal of the rotating shaft is interfered by frequency doubling signals when the characteristics are extracted. The method comprises the steps of respectively filtering elastic wave signals at two ends of a tested stepped cylindrical shaft, decomposing the elastic wave signals into a plurality of IMF components and residual signals by using an EMD (empirical mode decomposition), EEMD (empirical mode decomposition) or CEEMD (empirical mode decomposition) method, subtracting a frequency multiplication component from the decomposed signals, taking the central frequency of a transverse crack stop band and the relation characteristic of bandwidth and time distribution as characteristic parameters of cracks, and analyzing and matching the characteristic parameters with a characteristic database to obtain the position and depth information of the transverse crack. According to the invention, the frequency doubling component in the elastic wave signal is decomposed and removed, so that the problem of large interference of the frequency doubling signal when the energy of the elastic wave component is analyzed is solved, and the final analysis result of the transverse crack is more accurate.
Description
Technical Field
The invention belongs to the field of signal processing and crack nondestructive testing, and particularly relates to a transverse crack characteristic identification and extraction method of a stepped cylindrical shaft elastic wave signal.
Background
During the operation of a rotating shaft of a rotating machine, fatigue cracks are easily generated under the action of complex external loads, and the expansion of the fatigue cracks can cause serious breakage accidents and even great damage to lives and properties of people. Vibrations of the shaft during operation propagate therein in the form of elastic waves. The propagation characteristic of the elastic wave in the rotating shaft is influenced by various factors such as the geometric dimension of the rotating shaft, the physical properties of materials and the like, and when the rotating shaft has defects such as cracks, the propagation characteristic of the elastic wave is influenced, and the cracks can be researched through analysis of the propagation characteristic of the elastic wave, so that the purpose of crack detection is finally achieved.
The operating environment of the main shaft of the rotary machine is complex, and the obtained elastic wave signal has the characteristics of large background noise interference, instability and nonlinearity. In addition, when the rotating shaft runs by the power frequency signal Xf, due to the reasons of misalignment, oil film vortex and the like, frequency multiplication signals of 0.5Xf, 1Xf, 2Xf and the like can appear, and the signals are also coupled in the elastic wave signals. The elastic wave signal can be generally considered to be transmitted into the rotating shaft from one end (input end) of the rotating shaft and transmitted out of the rotating shaft from the other end (output end). Generally, a signal of an elastic wave may be subjected to spectrum analysis (FFT) or short-time fourier transform (STFT), and propagation characteristics of the elastic wave are compared by changes in energy distribution (spectrum distribution) at an input end and an output end of the elastic wave, so as to achieve the purpose of identifying a transverse crack. In the conventional method, when the spectrum analysis is performed, the characteristics of the crack signal cannot be accurately identified in the spectrum analysis due to the interference of the frequency-multiplied signals such as 0.5Xf, 1Xf and 2 Xf.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a transverse crack characteristic identification and extraction method of a stepped cylindrical shaft elastic wave signal, which mainly solves the problem that the conventional method is interfered by a frequency doubling signal during characteristic extraction.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
the invention comprises the following steps:
(1) the method comprises the steps that a three-way acceleration sensor or a three-way displacement sensor is respectively arranged at two ends of a tested stepped cylindrical shaft, when the tested stepped cylindrical shaft rotates, signals at two ends of the tested stepped cylindrical shaft are collected, and three signals at each end are combined into an elastic wave signal.
(2) And filtering the acquired elastic wave signals at two ends of the tested stepped cylindrical shaft by using a high-pass filter to filter white noise.
(3) And (3) decomposing the signals at two ends of the tested stepped cylindrical shaft filtered in the step (2) into a plurality of IMF components and residual signals respectively by using an EMD (empirical mode decomposition), EEMD (empirical mode decomposition) or CEEMD (empirical mode decomposition) method.
(4) And (3) subtracting the signals: calculating the power frequency Xf of the tested stepped cylindrical shaft by using FFT; analyzing the frequency of all IMFs in the step (3), if the frequency of the IMF component falls within the range of 0.44-0.5, 0.9-1.1, 1.9-2.1, 2.9-3.1, 3.9-4.1 or 4.9-5.1 times of the power frequency Xf of the tested step-shaped cylindrical shaft, subtracting the IMF component from the decomposed signal in the step (3), reserving the residual IMF component and residual error signals, and respectively obtaining residual signals X at the input end and the output end of the tested step-shaped cylindrical shaftres,inAnd Xres,out。
(5) Extracting crack characteristic parameters: first the residual signal Xres,inAnd Xres,outNormalization processing is carried out, and the flow of the normalization processing is as follows: obtaining Xres,inAnd Xres,outData value x with the largest absolute value of the two signalsmax(ii) a ② respectively mixing Xres,inAnd Xres,inDivided by xmaxTo obtain
And
and then using FFT pairs
And
performing comparative analysis to obtain a spectrum distribution contrast diagram, and obtaining the spectrum distribution contrast diagram by using an STFT method
And
time-frequency domain distribution of the signal is compared with a graph. Then, using the spectrum distribution contrast map, will
And
the amplitudes of the signals at the same frequency are compared and
the amplitude of the signal being higher than
Comparing the frequency range of which the signal amplitude is 1.05 times with the frequency domain resolution of the STFT, and if the frequency range is larger than the frequency domain resolution of the STFT, defining the frequency range as a stop band; and finally, judging whether the stop band exists or not, if not, returning to the step (2) to continue detection, if so, combining the time distribution contrast diagram of the frequency domain distribution, further determining the time distribution of the center frequency of the stop band and the bandwidth, taking the relationship characteristics of the center frequency of the stop band and the bandwidth and the time distribution as characteristic parameters of the crack, and executing the step (6).
(6) Identification of transverse cracks: and analyzing and matching the characteristic parameters of the transverse cracks with the characteristic database to obtain the position and depth information of the transverse cracks.
Further, the high-pass filter is a digital filter with a pass frequency of [2, + ∞).
Further, in the decomposition process of the step (3), an end effect processing method is adopted for end effect processing.
Further, the end effect processing method is an ISBM extension method, a mirror image extension method or a parallel extension method.
Further, in the step (6), a feature database is pre-established, and the relationship characteristics of the central frequency of the transverse crack stop band and the bandwidth and the time distribution of the transverse crack stop band are respectively determined for a plurality of axial transverse cracks and a plurality of depth values of each position transverse crack when the feature database is established. The determination process of the characteristics of the central frequency and the bandwidth of the transverse crack stop band in relation to the time distribution is as follows: and (3) selecting a stepped cylindrical shaft without transverse cracks, processing the transverse cracks with preset positions and depths on the stepped cylindrical shaft in advance, and then executing the steps (1) to (5) without executing the step (6), so as to determine the central frequency of the transverse crack stop band and the relation characteristics of the bandwidth and the time distribution.
Further, in the step (6), if the relation between the transverse crack stop band width and the time distribution is inconsistent with the characteristic database, selecting the positions of the two transverse cracks with the minimum difference value with the transverse crack stop band width in the characteristic database to obtain a middle value as the position of the transverse crack, and taking the average value of the depth values of the two transverse cracks with the minimum difference value with the transverse crack stop band width as the depth value of the transverse crack.
The invention has the following beneficial effects:
according to the method, the EMD, EEMD or CEEMD method is adopted to decompose and remove the frequency doubling component in the elastic wave signal, so that the problem of large interference of the frequency doubling signal when the energy of the elastic wave component is analyzed is solved, and the final analysis result of the transverse crack is more accurate.
Drawings
FIG. 1 is a flow chart of the operation of the present invention;
fig. 2 is a detailed view of the operation flow in fig. 1.
Detailed Description
In order that those skilled in the art can better understand the present invention, the following technical solutions are further described with reference to the accompanying drawings and examples.
As shown in fig. 1 and 2, the transverse crack feature identification and extraction method of the stepped cylindrical axis elastic wave signal includes the following steps:
(1) the method comprises the steps of respectively arranging a three-way acceleration sensor or a three-way displacement sensor at two ends of a tested stepped cylindrical shaft, acquiring signals (vibration acceleration or vibration amplitude) at two ends of the tested stepped cylindrical shaft, and synthesizing three signals at each end into an elastic wave signal. Elastic waves are input from one end of the tested stepped cylindrical shaft, and are output from the other end of the tested stepped cylindrical shaft; the elastic wave signal with large vibration energy corresponds to the input end of the tested stepped cylindrical shaft, and the elastic wave signal with small vibration energy corresponds to the output end of the tested stepped cylindrical shaft. In this embodiment, the elastic wave signals at the two ends of the tested stepped cylindrical shaft are subjected to spectrum analysis to determine the magnitude of the vibration energy, and the vibration energy is considered to be large when the frequency band is wide and the amplitude is large.
(2) And filtering the acquired elastic wave signals at two ends of the tested stepped cylindrical shaft by using a high-pass filter to filter white noise. The high pass filter employed in this embodiment is a digital filter with a pass frequency of [2, + ∞).
(3) Decomposing the signals at two ends of the tested stepped cylindrical shaft filtered in the step (2) into a plurality of IMF components and residual signals respectively by using an EMD (empirical mode decomposition), EEMD (empirical mode decomposition) or CEEMD (empirical mode decomposition) method; in the decomposition process, an endpoint effect processing method is adopted for endpoint effect processing; the end effect processing method is ISBM extension method, mirror image extension method or parallel extension method.
(4) And (3) subtracting the signals: calculating the power frequency Xf of the tested stepped cylindrical shaft by using FFT; analyzing the frequencies of all IMFs in the step (3), if the frequency of a certain IMF component falls within the range of 0.44-0.5, 0.9-1.1, 1.9-2.1, 2.9-3.1, 3.9-4.1 or 4.9-5.1 times of the power frequency Xf of the tested step-shaped cylindrical shaft, subtracting the IMF component from the decomposed signal in the step (3), reserving the residual IMF component and residual error signals, and respectively obtaining residual signals X at the input end and the output end of the tested step-shaped cylindrical shaftres,inAnd Xres,out。
(5) Extracting crack characteristic parameters: the residual signal Xres,inAnd Xres,outNormalization processing is carried out, and the flow of the normalization processing is as follows: obtaining Xres,inAnd Xres,outData value x with the largest absolute value of the two signalsmax(ii) a ② respectively mixing Xres,inAnd Xres,inDivided by xmaxTo obtain
And
and then using FFT pairs
And
performing comparative analysis to obtain a spectrum distribution contrast diagram, and obtaining the spectrum distribution contrast diagram by using an STFT method
And
time-frequency domain distribution of the signal is compared with a graph. Then, using the spectrum distribution contrast map, will
And
the amplitudes of the signals at the same frequency are compared and
the amplitude of the signal being higher than
Comparing the frequency range of which the signal amplitude is 1.05 times with the frequency domain resolution of the STFT, and if the frequency range is larger than the frequency domain resolution of the STFT, defining the frequency range as a stop band; finally, judging whether a stop band exists or not, if not, returning to the step (2) for continuous detection, if so, combining the time distribution contrast diagram of the frequency domain distribution, further determining the central frequency of the stop band and the time distribution of the bandwidth, taking the central frequency of the stop band and the relation characteristic of the bandwidth and the time distribution as the characteristic parameters of the crack, and executingAnd (6) carrying out a step.
When the stepped cylindrical shaft has no crack, the energy loss is very small when the elastic wave is transmitted on the stepped cylindrical shaft because the cross section of each shaft section is unchanged, and the residual signal X at the input end isres,inCan be approximately equivalent to the residual signal X of the output terminalres,outTherefore, when the stop band exists in the step (5),
and
the signal comparison can be regarded as the comparison of the elastic wave signal at the output end of the stepped cylindrical shaft without the crack and the elastic wave signal at the input end of the stepped cylindrical shaft with the crack on the premise of the same elastic wave signal.
(6) Identification of transverse cracks: and analyzing and matching the characteristic parameters of the transverse cracks with the characteristic database to obtain the position and depth information of the transverse cracks.
Further, in the step (6), a feature database is pre-established, and when the feature database is established, the relationship characteristics of the central frequency and the bandwidth of the transverse crack stop band and the time distribution need to be respectively determined for a plurality of axial transverse cracks and a plurality of depth values of each axial transverse crack, and the position distribution of the transverse cracks needs to ensure a certain concentration along the axial direction, and the depth value distribution also needs to ensure a certain concentration. The determination process of the characteristics of the central frequency and the bandwidth of the transverse crack stop band in relation to the time distribution is as follows: and (3) selecting a stepped cylindrical shaft without transverse cracks, processing the transverse cracks with preset positions and depths on the stepped cylindrical shaft in advance, and then executing the steps (1) to (5) without executing the step (6), so as to determine the central frequency of the transverse crack stop band and the relation characteristics of the bandwidth and the time distribution.
Further, in the step (6), if the relation between the transverse crack stop band width and the time distribution is inconsistent with the characteristic database, selecting the positions of the two transverse cracks with the minimum difference value with the transverse crack stop band width in the characteristic database to obtain a middle value as the position of the transverse crack, and taking the average value of the depth values of the two transverse cracks with the minimum difference value with the transverse crack stop band width as the depth value of the transverse crack.
Claims (6)
1. The transverse crack characteristic identification and extraction method of the ladder-shaped cylindrical shaft elastic wave signal is characterized by comprising the following steps of: the method comprises the following steps:
(1) respectively arranging a three-way acceleration sensor or a three-way displacement sensor at two ends of the tested stepped cylindrical shaft, acquiring signals at two ends of the tested stepped cylindrical shaft when the tested stepped cylindrical shaft rotates, and synthesizing three signals at each end into an elastic wave signal;
(2) filtering the acquired elastic wave signals at two ends of the tested stepped cylindrical shaft by using a high-pass filter to filter white noise;
(3) decomposing the signals at two ends of the tested stepped cylindrical shaft filtered in the step (2) into a plurality of IMF components and residual signals respectively by using an EMD (empirical mode decomposition), EEMD (empirical mode decomposition) or CEEMD (empirical mode decomposition) method;
(4) and (3) subtracting the signals: calculating the power frequency Xf of the tested stepped cylindrical shaft by using FFT; analyzing the frequency of all IMFs in the step (3), if the frequency of the IMF component falls within the range of 0.44-0.5, 0.9-1.1, 1.9-2.1, 2.9-3.1, 3.9-4.1 or 4.9-5.1 times of the power frequency Xf of the tested step-shaped cylindrical shaft, subtracting the IMF component from the decomposed signal in the step (3), reserving the residual IMF component and residual error signals, and respectively obtaining residual signals X at the input end and the output end of the tested step-shaped cylindrical shaftres,inAnd Xres,out；
(5) Extracting crack characteristic parameters: first the residual signal Xres,inAnd Xres,outNormalization processing is carried out, and the flow of the normalization processing is as follows: obtaining Xres,inAnd Xres,outData value x with the largest absolute value of the two signalsmax(ii) a ② respectively mixing Xres,inAnd Xres,inDivided by xmaxTo obtain
And
and then using FFT pairs
And
performing comparative analysis to obtain a spectrum distribution contrast diagram, and obtaining the spectrum distribution contrast diagram by using an STFT method
And
comparing the time-frequency domain distribution of the signal; then, using the spectrum distribution contrast map, will
And
the amplitudes of the signals at the same frequency are compared and
the amplitude of the signal being higher than
Comparing the frequency range of which the signal amplitude is 1.05 times with the frequency domain resolution of the STFT, and if the frequency range is larger than the frequency domain resolution of the STFT, defining the frequency range as a stop band; finally, judging whether a stop band exists or not, if not, returning to the step (2) to continue detection, if so, combining the time distribution contrast diagram of the frequency domain distribution, further determining the time distribution of the center frequency of the stop band and the bandwidth, taking the relationship characteristics of the center frequency of the stop band and the bandwidth and the time distribution as characteristic parameters of the crack, and executing the step (6);
(6) identification of transverse cracks: and analyzing and matching the characteristic parameters of the transverse cracks with the characteristic database to obtain the position and depth information of the transverse cracks.
2. The method for identifying and extracting transverse crack characteristics of a stepped cylindrical axis elastic wave signal according to claim 1, wherein the method comprises the following steps: the high pass filter is a digital filter with a pass frequency of [2, + ∞ ].
3. The method for identifying and extracting transverse crack characteristics of a stepped cylindrical axis elastic wave signal according to claim 1, wherein the method comprises the following steps: and (4) in the decomposition process of the step (3), performing endpoint effect processing by adopting an endpoint effect processing method.
4. The method for identifying and extracting transverse crack characteristics of a stepped cylindrical axis elastic wave signal according to claim 3, wherein the method comprises the following steps: the end effect processing method is an ISBM continuation method, a mirror image continuation method or a parallel continuation method.
5. The method for identifying and extracting transverse crack characteristics of a stepped cylindrical axis elastic wave signal according to claim 1, wherein the method comprises the following steps: in the step (6), a characteristic database is pre-established, and the relationship characteristics of the central frequency of the transverse crack stop band and the bandwidth and the time distribution of the transverse crack stop band are respectively determined for a plurality of axial transverse cracks and a plurality of depth values of each transverse crack; the determination process of the characteristics of the central frequency and the bandwidth of the transverse crack stop band in relation to the time distribution is as follows: and (3) selecting a stepped cylindrical shaft without transverse cracks, processing the transverse cracks with preset positions and depths on the stepped cylindrical shaft in advance, and then executing the steps (1) to (5) without executing the step (6), so as to determine the central frequency of the transverse crack stop band and the relation characteristics of the bandwidth and the time distribution.
6. The method for identifying and extracting transverse crack characteristics of a stepped cylindrical axis elastic wave signal according to claim 1, wherein the method comprises the following steps: in the step (6), if the relation between the transverse crack stop band width and the time distribution is inconsistent with the characteristic database, selecting the positions of the two transverse cracks with the minimum difference value with the transverse crack stop band width in the characteristic database to obtain a middle value as the position of the transverse crack, and taking the average value of the depth values of the two transverse cracks with the minimum difference value with the transverse crack stop band width as the depth value of the transverse crack.
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