CN110161131A - Defect reflection signal recognition method and its device based on sequential hypothesis testing - Google Patents
Defect reflection signal recognition method and its device based on sequential hypothesis testing Download PDFInfo
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Abstract
The invention discloses a kind of defect reflection signal recognition method and its device based on sequential hypothesis testing emits ultrasonic signal using ultrasound emission probe on defect test specimen, and receives ultrasound echo signal on the defect test specimen is coplanar using ultrasonic reception probe；After collecting echo-signal, and wavelet package transforms denoising is carried out to echo-signal；Sequential probability is carried out than test identifying processing to the echo-signal after wavelet package transforms denoising, obtains the starting point of diffracted signal；The position of defect is determined according to the starting point of the diffracted signal.The present invention proposes a kind of recognition detection and localization method based on sequential probability than test, can be widely used in the detection and positioning of different types of fault of construction, and precision and universality are high.
Description
Technical field
The invention belongs to technical field of nondestructive testing more particularly to a kind of defect reflection signals based on sequential hypothesis testing
Recognition methods and its device.
Background technique
In the industry, structure often generates defect crack due to production environment etc., these defect cracks are certain
In the case of, it suffers erosion and changes from small to big, development slowly is macroscopic cracking, so as to cause structural damage, in some instances it may even be possible to cause
The consequence that can not be retrieved.Therefore, the defect crack detection at structure initial stage is just particularly important.
It is mainly at present that TOFD and ultrasonic phase array detect for the research of defect crack detection, they all can not be to defect
Crackle accomplishes effectively stable detection, due to defect crack detection must accomplish it is accurately sorry without staying, to prevent leaving potential danger
Danger, makes the fault of missing inspection go to zero as far as possible, compares TOFD and ultrasonic phase array, it is desirable to be able to reduce cost, can improve inspection
The method of efficiency.
Summary of the invention
The defect reflection signal identification based on sequential hypothesis testing that the technical problem to be solved by the invention is to provide a kind of
Method and device thereof, detection structure defect crack can reduce cost, can improve the efficiency examined.
The technical solution adopted by the present invention to solve the technical problems is: present invention firstly provides one kind to be based on sequential hypothesis
The defect reflection signal recognition device of inspection, including ultrasound emission signal element, ultrasonic reception signal element, wavelet package transforms list
Member, sequential hypothesis testing test cell and position acquisition unit；The ultrasound emission signal element, for being visited using ultrasound emission
Head emits ultrasonic signal on defect test specimen；The ultrasonic reception signal element, for being lacked using ultrasonic reception probe to described
It falls on test specimen and receives ultrasound echo signal；The wavelet package transforms unit, for carrying out signal denoising according to the echo-signal
Processing；The sequential hypothesis testing test cell, for carrying out sequential probability than surveying to the echo-signal after filtering processing
Identifying processing is tried, the starting point of diffracted signal is obtained；Position acquisition unit is lacked for being determined according to the starting point of the diffracted signal
Sunken position.
By ultrasound emission signal element excitation ultrasound signal, ultrasonic reception signal element receives diffraction pulse signal, leads to
Wavelet package transforms unit is crossed, is used to carry out signal denoising processing according to the echo-signal, then pass through sequential hypothesis testing and test
Unit obtains diffracted signal for carrying out sequential probability than test identifying processing to the echo-signal after filtering processing
Starting point obtains the position of defect crack by position acquisition unit.Ultrasound emission signal and ultrasonic reception signal determination unit
Institute for determining the parameter of the ultrasound emission to match probe respectively according to the parameter of the defect test specimen and matching
State the parameter of ultrasonic reception probe.
It according to the above technical scheme, further include signal source determination unit, signal source determination unit is used to be tried according to the defect
The parameter of part determines the parameter and the parameter of the ultrasonic reception probe to match of the ultrasound emission to match probe respectively.
According to the above technical scheme, the parameter of defect test specimen includes the size of defect test specimen, material, velocity of sound spread speed and micro-
Crack defect range, the parameter of low frequency ultrasound probe include pore size, centre frequency and sample frequency, and ultrasound receives probe
Parameter includes pore size, centre frequency and sample frequency.
According to the above technical scheme, wavelet package transforms unit, for being filtered denoising to crack tip diffraction echo-signal
Processing.
The present invention also provides a kind of sequential hypothesis testing defect reflection signal recognition method based on claim 1, the party
Method includes the following steps, step 1: emitting ultrasonic signal on defect test specimen using ultrasound emission probe, and uses ultrasonic reception
Probe receives ultrasound echo signal on defect test specimen is coplanar；Step 2: after collecting echo-signal, echo-signal being carried out small
Wave packet transform denoising；Step 3: sequential probability is carried out than test identification to the echo-signal after wavelet package transforms denoising
Processing, obtains the starting point of diffracted signal；Step 4: the position of defect is determined according to the starting point of diffracted signal.
According to the above technical scheme, in the step 2 wavelet package transforms handle specifically: using wavelet package transforms to signal into
Row three-level is decomposed, and carries out denoising to original signal.
Due to TOFD experiment in collected ultrasound data by ambient enviroment, sensor, data collection system and other
The noise that unknown source generates is destroyed, it is also generated by the crystal boundary in material, and random distribution at any time, comes from crystal boundary and material
In the ultrasonic echos of other microstructure inhomogeneities be to lead to there is master in terms of examining crackle, defect and other metallurgical imperfections
Want difficult, the very noisy in collected ultrasonic signal makes it difficult to accurately verify starting point, it is necessary to which identification collects
Ultrasonic signal data flow in echo starting point, with the position of crackle in accurate evaluation material and size, at wavelet package transforms
Reason can reduce the noise crack detection signal of ultrasonic wave, can substantially increase echo signal to noise ratio, it is ensured that defect crack
Positioning it is more accurate, improve detection accuracy.
According to the above technical scheme, sequential probability ratio test specific steps in the step 3 are as follows:
Step 31: the starting point of ultrasonic echo signal is identified, accurately to determine the depth of crackle；
Step 32: according to the waveform of SPRT likelihood ratio on one point on mutation identify the starting point of diffracting ultrasonic pulse.
Test parameter of root mean square (RMS) value as SPRT is selected, under different experiments data, SPRT is for analyzing crackle
The reflection signal at tip, it is seen that the waveform of SPRT likelihood ratio is on a declining curve at any time, and the waveform of SPRT increases suddenly in specified point
Add, for identification the starting point of diffracting ultrasonic pulse, the position of readily available defect crack, convenient for the subsequent position to defect crack
It sets and is positioned, detection is high with positioning accuracy.
According to the above technical scheme, the step 4 is specifically, according to the root mean square sequence Y (S of defect test specimen ultrasonic signali
And Y (S (0))i(1)) input equation calculates SPRT likelihood ratio λ0,1(Y(Si) and λ (0))0,1(Y(Si(1))), and according to square
Root sequence coordinate calculates the starting point for identifying ultrasound emission pulse of spreading out, and calculates specific formula are as follows:
I=0,0.2,1,0j=0,1；Wherein, i indicates the distance between two sensors；J indicate each away from
Two groups of signals are collected from place.
Starting point based on the identification diffraction reflection signal that sequential probability ratio test obtains, can estimate crackle in conjunction with TOFD
Accurate position coordinates, calculation method is simple, and positioning accuracy is high.
According to the above technical scheme, in the step 1, the ultrasound to match is determined respectively according to the parameter information of defect test specimen
The parameter of transmitting probe and the ultrasound to match receive the parameter of probe.
The ultrasound emission to match probe and ultrasonic reception probe are determined by the parameter of defect test specimen, preferably to swash
Ultrasound emission signal is sent out, convenient for effectively receiving ultrasonic pulse-echo, small echo is carried out according to collected echo-signal convenient for subsequent
Packet transform, to obtain the echo-signal of denoising to determine the accurate location of crackle diffraction reflection signal.
According to the above technical scheme, the parameter information of defect test specimen includes size, material, the velocity of sound spread speed of defect test specimen
With the indicated range of crackle, the parameter of ultrasound emission probe includes pore size, centre frequency and sample frequency, and ultrasonic reception is visited
The parameter of head includes pore size, centre frequency and the sample frequency of probe.
The beneficial effect comprise that: the recognition methods based on sequential probability than test is used, wherein identifying system
Propagation ducts can adaptively and be intelligently inquired by using ultrasound data, identify the starting point of transmitting signal, and are led to
Cross the position that TOFD estimates defect in material, there is higher discrimination and precision, by sequential probability ratio test and TOFD with it is small
Wave packet transform combines, but so that the detection of metal thin plate structure is no longer limited to the detection of defect crack, also no longer
Limit to the detection and positioning to closure defect crack, the positioning of fault of construction crackle, detection and positioning accuracy can be widely used in
It is substantially improved, universality is high.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the defect reflection signal recognition method embodiment flow diagram of the invention based on sequential hypothesis testing；
Fig. 2 is the structural schematic diagram of the of the invention one defect reflection signal recognition device based on sequential hypothesis testing.
Wherein, 1, defect test specimen, 2, ultrasound emission probe, 3, ultrasonic reception probe, 4, data line, 5, oscillograph, 6, wave
Shape generator, 7, processor, 8, display.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
Embodiment one: as shown in Figure 1, for the present invention is based on the realities of the defect reflection signal recognition method of sequential hypothesis testing
Apply example, comprising the following steps: the present embodiment chooses one piece of long 200mm, and wide 200mm, the low carbon steel plate of thick 22.5mm is as defect
A defect crack is contained in test specimen, defect test specimen inside.In the steel plate, the spread speed of shear wave is 3.25mm/ μ s, the biography of longitudinal wave
Broadcasting speed is 6.0mm/ μ s, thereby determines that the centre frequency of the ultrasound emission probe in the present embodiment is 0.5MHz, sample frequency
For 100MHz, the centre frequency of ultrasonic reception probe is 5MHZ, sample frequency 100MHZ.
The present embodiment thereby determines that in the present embodiment according to the parameter of above-mentioned ultrasound emission probe and ultrasonic reception probe
Ultrasonic reception probe selection 5L14 model, ultrasonic probe select 0.5L14 model；Further determine that the ultrasound by 5L14 model connects
The top that probe is mounted on defect test specimen is received, and face defect test specimen is placed, the ultrasound emission probe of 0.5L14 signal is also pacified
Mounted in the top side of defect test specimen, with the equidistant face defect crack of ultrasound emission probe.
S1: ultrasonic signal is emitted on defect test specimen using ultrasound emission probe, and is popped one's head in using ultrasonic reception described
Receive ultrasound echo signal on defect test specimen is coplanar.
S2: the echo-signal is acquired, and wavelet package transforms processing is carried out to the echo-signal.
It is decomposed using three-level and denoising is carried out to the echo-signal, the echo-signal after being denoised.Due to echo
Signal is to be generated by crackle diffracted wave and bottorm echo, therefore can regard defect crack as the sound source of echo-signal, is passed through
The bottorm echo signal in echo-signal is denoised, the crack tip diffracted wave signal in detection signal is extracted, convenient for subsequent right
It carries out sequential probability than test processes, and diffraction reflection will occur at defect crack position for ultrasonic signal, lacks to realize
The positioning of micro-crack is fallen into, to guarantee that in crack tip diffracted wave occurs for ultrasonic signal, wavelet package transforms denoising is selected to improve noise
Than as echo-signal, it is ensured that the positioning of defect crack is more accurate, improves detection accuracy.
S3: sequential probability is carried out than test identifying processing to the echo-signal after wavelet package transforms denoising, is obtained
Obtain the starting point of diffracted signal.
The denoising echo-signal of different moments is loaded into simulation model using Abaqus finite element software, is carried out
Sequential probability obtains the starting point of the diffracted signal than test processes.
Echo-signal can to denoise in simulation model than test by sequential probability, decomposed in time domain, and
Retransmitted away respectively by corresponding receiving sensor unit so that different experiments distance issue, along different propagateds
Signal simultaneously reach sound source position, at crack tip occur diffracted wave, at ultrasonic reception probe collect multiple groups echo letter
Number, it can occur to increase suddenly in specified point by multiple groups echo-signal known to the analysis of SPRT likelihood ratio, it follows that this point is to split
Line tip diffraction starting point positions consequently facilitating obtaining defect crack starting point convenient for the subsequent position to defect crack.
S4: the position of defect is determined according to the starting point of the diffracted signal.
According to the root mean square sequence Y (S of the defect test specimen ultrasonic signaliAnd Y (S (0))i(1)) input equation calculates
SPRT likelihood ratio λ0,1(Y(Si) and λ (0))0,1(Y(Si(1))), and the identification is calculated according to the root mean square sequence coordinate to spread out
The starting point of ultrasound emission pulse calculates specific formula are as follows:
I=0,0.2,1.0j=0,1
By establishing coordinate system, crackle diffracted wave position coordinates are determined.
Rf excitation signal is sent out using based on low frequency ultrasound transmitting probe in the present embodiment, so that sound wave is in defect test specimen
Tip diffracted wave is cracked when encountering defect crack during propagation, while bottom surface can generate the anti-wave of diffraction, and crackle is spread out
The echo-signal that ejected wave and bottom reflection wave interaction generate, by wavelet packet and sequential probability than measuring technology, by echo
Sound wave has just obtained point source of sound after being denoised, so that it is determined that in defect test specimen defect crack position, have higher discrimination
And precision, sequential probability ratio test is combined with TOFD with wavelet package transforms, but so that not to the detection of defect crack
It is confined to the detection of metal thin plate structure again, also no longer limits to detection and positioning to closure defect crack, can be widely used in
The positioning of fault of construction crackle, detection are also substantially improved with positioning accuracy, and universality is high.
Embodiment two: as shown in Fig. 2, for a kind of defect reflection signal identification dress based on sequential hypothesis testing of the invention
Set structural schematic diagram, including defect test specimen 1, ultrasound emission probe 2, ultrasonic reception probe 3, data line 4, oscillograph 5, waveform hair
Raw device 6, processor 7, display 8；Defect test specimen 1 described in the top of the defect test specimen 1 and face is arranged in ultrasonic probe 2,
Waveform generator 6, which connect and acts on ultrasound emission probe 2, loads pumping signal to the defect test specimen 1；It is described super
Sound reception probe 3 is arranged in defect test specimen 1 described in the top of the defect test specimen 1 and face, and ultrasound emission probe 2 with it is super
Sound reception 3 equidistant face defect test specimens 1 of probe；The oscillograph 5 is connect by data line 4 with ultrasonic reception probe 3,
The oscillograph 5 is used to show the echo-signal of the low-frequency excitation signal and the interaction of bottom reflection signal；The processing
Device 7 is electrically connected by the data line 4 with the oscillograph 5, and the processor 7 is used to carry out small echo according to the echo-signal
Packet transform processing is also used to carry out wavelet package transforms treated echo unit sequential probability than test processes, obtains diffraction
The starting point of signal is also used to determine the position of defect crack according to the starting point of the diffracted signal.
Low-frequency excitation signal is excited to defect test specimen by low frequency ultrasound transmitting probe, then is popped one's head in by ultrasonic reception to defect
Test specimen receives echo-signal carries out wavelet package transforms processing and sequential probability than test processes by processor, obtains diffraction letter
Number starting point, and by processor carry out calculate extract defect crack accurate location.Whole system co-ordination, can be extensively
The detection and positioning of defect crack for different structure, and detect, universality height high with positioning accuracy.It further include display 8,
Display 8 is for showing the position of the defect crack.
It is convenient for the position for the micro-crack that will acquire to show by display, intuitively understands and lack convenient for related personnel
The position of crackle is fallen into, and corresponding maintenance is made according to the position of defect crack.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (10)
1. a kind of defect reflection signal recognition device based on sequential hypothesis testing, which is characterized in that including ultrasound emission signal
Unit, ultrasonic reception signal element, wavelet package transforms unit, sequential hypothesis testing test cell and position acquisition unit；
The ultrasound emission signal element, for emitting ultrasonic signal on defect test specimen using ultrasound emission probe；
The ultrasonic reception signal element, for being believed using ultrasonic reception probe reception ultrasonic echo on the defect test specimen
Number；
The wavelet package transforms unit, for carrying out signal denoising processing according to the echo-signal；
The sequential hypothesis testing test cell, for carrying out sequential probability than test to the echo-signal after filtering processing
Identifying processing obtains the starting point of diffracted signal；
Position acquisition unit, for determining the position of defect according to the starting point of the diffracted signal.
2. the defect reflection signal recognition device according to claim 1 based on sequential hypothesis testing, which is characterized in that also
Including signal source determination unit, signal source determination unit is used to determine that is matched surpasses respectively according to the parameter of the defect test specimen
The parameter of the parameter of acoustic emission probe and the ultrasonic reception to match probe.
3. the defect reflection signal recognition device according to claim 1 or 2 based on sequential hypothesis testing, feature exist
In the parameter of defect test specimen includes size, material, velocity of sound spread speed and the micro-crack indicated range of defect test specimen, and low frequency is super
The parameter of sonic probe includes pore size, centre frequency and sample frequency, ultrasound receive probe parameter include pore size, in
Frequency of heart and sample frequency.
4. the defect reflection signal recognition device according to claim 1 or 2 based on sequential hypothesis testing, feature exist
In wavelet package transforms unit, for being filtered denoising to crack tip diffraction echo-signal.
5. a kind of sequential hypothesis testing defect reflection signal recognition method based on claim 1, which is characterized in that this method packet
Following steps are included, step 1: ultrasonic signal being emitted on defect test specimen using ultrasound emission probe, and is popped one's head in using ultrasonic reception
Receive ultrasound echo signal on defect test specimen is coplanar；
Step 2: after collecting echo-signal, wavelet package transforms denoising being carried out to echo-signal；
Step 3: sequential probability being carried out than test identifying processing to the echo-signal after wavelet package transforms denoising, obtains diffraction
The starting point of signal；
Step 4: the position of defect is determined according to the starting point of diffracted signal.
6. a kind of sequential hypothesis testing defect reflection signal recognition method based on claim 5, which is characterized in that the step
Wavelet package transforms are handled in 2 specifically: are carried out three-level decomposition to signal using wavelet package transforms, carried out at denoising to original signal
Reason.
7. the defect reflection signal recognition method according to claim 5 or 6 based on sequential hypothesis testing, feature exist
In sequential probability is than test specific steps in the step 3 are as follows:
Step 31: the starting point of ultrasonic echo signal is identified, accurately to determine the depth of crackle；
Step 32: according to the waveform of SPRT likelihood ratio on one point on mutation identify the starting point of diffracting ultrasonic pulse.
8. the defect reflection signal recognition method according to claim 5 or 6 based on sequential hypothesis testing, feature exist
In the step 4 is specifically, according to the root mean square sequence Y (S of defect test specimen ultrasonic signaliAnd Y (S (0))i(1)) input equation
Calculate SPRT likelihood ratio λ0,1(Y(Si) and λ (0))0,1(Y(Si(1))), and according to the calculating identification of root mean square sequence coordinate spread out super
The starting point of sound emission pulse calculates specific formula are as follows:
I=0,0.2,1,0, i indicates the distance between two sensors；
J=0,1, j indicates to collect two groups of signals at each distance.
9. the defect reflection signal recognition method according to claim 5 or 6 based on sequential hypothesis testing, feature exist
In in the step 1, according to the parameter information of defect the test specimen determining ultrasound emission to match is popped one's head in respectively parameter and phase
The ultrasound matched receives the parameter of probe.
10. the defect reflection signal recognition method according to claim 9 based on sequential hypothesis testing, which is characterized in that
The parameter information of defect test specimen includes the indicated range of the size of defect test specimen, material, velocity of sound spread speed and crackle, ultrasound hair
The parameter for penetrating probe includes pore size, centre frequency and sample frequency, and the parameter of ultrasonic reception probe includes the aperture of probe
Size, centre frequency and sample frequency.
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| CN113640394A (en) * | 2021-07-02 | 2021-11-12 | 武汉工程大学 | Fatigue crack identification method and system |
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Application publication date: 20190823 |