CN108508093A - A kind of detection method and system of workpiece, defect height - Google Patents
A kind of detection method and system of workpiece, defect height Download PDFInfo
- Publication number
- CN108508093A CN108508093A CN201810250129.6A CN201810250129A CN108508093A CN 108508093 A CN108508093 A CN 108508093A CN 201810250129 A CN201810250129 A CN 201810250129A CN 108508093 A CN108508093 A CN 108508093A
- Authority
- CN
- China
- Prior art keywords
- signal
- extreme point
- defect
- workpiece
- measurement
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
- G01N29/0609—Display arrangements, e.g. colour displays
- G01N29/0645—Display representation or displayed parameters, e.g. A-, B- or C-Scan
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B17/00—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations
- G01B17/02—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations for measuring thickness
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/028—Material parameters
- G01N2291/02854—Length, thickness
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/028—Material parameters
- G01N2291/0289—Internal structure, e.g. defects, grain size, texture
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The present invention discloses a kind of detection method and system of workpiece, defect height, and this method includes：Obtain the D scanning images of the weld seam of workpiece for measurement；The defect and defective locations of workpiece for measurement are determined according to D scanning images；The A at defective locations, which is obtained, according to D scanning images sweeps signal；Signal is swept to A and carries out Wavelet Denoising Method processing, obtains reconstruction signal；Wiener filtering processing is carried out to reconstruction signal, obtains the estimated value of the defect response signal of workpiece for measurement；Inverse Fourier transform is carried out to the estimated value of defect response signal, obtains the time-domain signal of defect response signal；According to time-domain signal, the upper extreme point diffracted signal of defect and the time difference of lower extreme point diffracted signal, the upper extreme point depth of defect, lower extreme point depth are calculated；The height of defect is calculated according to the time difference of upper extreme point depth, lower extreme point depth, upper extreme point and lower extreme point diffracted signal.Defect quantitative error can be effectively reduced using the method for the present invention or system, improve recall rate.
Description
Technical field
The present invention relates to field of non destructive testing, more particularly to a kind of detection method and system of workpiece, defect height.
Background technology
With the development of non-destructive testing technology, ultrasonic wave diffraction time difference method (Time Of Flight Diffraction,
TOFD) application of detection method is also more and more extensive, and compared with traditional supersonic detection method, ultrasonic TOFD has detection speed
Faster, detection efficiency is high, and the positioning and quantitative precision higher relative error to defect are smaller, and can record and preserve for a long time
The advantages such as data.
Ultrasonic TOFD detection is the time difference propagated according to the diffracted signal that endpoint above and below defect generates to realize flaw height
Accurate quantification, influenced by examined workpiece thickness, when thickness of workpiece is relatively thin, ultrasonic TOFD detection A sweep in signal lead directly to wave,
Aliasing easily occurs defect for endpoint diffracted wave and Bottom echo up and down, and temporal resolution is caused to reduce.And in the prior art then
It is by artificially judging endpoint up and down, and then the height of determining endpoint up and down.A sweeps noise in signal in being detected due to ultrasonic TOFD
Presence cause defect upper and lower side diffracted signal to be difficult to differentiate between so that in the prior art to flaw height it is quantitative exist compared with
Big error.
Invention content
The object of the present invention is to provide a kind of detection methods and system of workpiece, defect height, solve ultrasonic TOFD detection
The presence that middle A sweeps noise in signal causes defect upper and lower side diffracted signal to be difficult to differentiate between so that flaw height quantitative error is larger
The problem of.
To achieve the above object, the present invention provides following schemes：
A kind of detection method of workpiece, defect height, including：
Obtain the D scanning images of the weld seam of workpiece for measurement；The D scannings image by scanner to the weld seam of workpiece for measurement into
Row D scannings obtain；
The defective locations of the workpiece for measurement are determined according to the D scannings image；
The A obtained at the defective locations according to the D scannings image sweeps signal；It is the defective bit that the A, which sweeps signal,
Set the elevation information at place；
Signal is swept to the A and carries out Wavelet Denoising Method processing, obtains reconstruction signal；
Wiener filtering processing is carried out to the reconstruction signal, obtains the estimation of the defect response signal of the workpiece for measurement
Value；
Inverse Fourier transform is carried out to the estimated value of the defect response signal, obtains the defect response of the workpiece for measurement
The time-domain signal of signal；
According to the time-domain signal, the upper extreme point diffracted signal and lower extreme point diffraction letter of the defect of the workpiece for measurement are calculated
Number time difference, the defect upper extreme point depth, lower extreme point depth；
According to the time difference of the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point diffracted signal
The height of the defect is calculated.
Optionally, described that signal progress Wavelet Denoising Method processing is swept to the A, it obtains reconstruction signal and specifically includes：
According to wavelet transformation formulaTo the A
It sweeps signal to be decomposed, obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is mother wavelet function, will be female
Wavelet function scale stretches and is obtained after translatingA is scale factor, and b is shift factor, ψ* a,b
(t) it is ψa,b(t) conjugation, y (t) are that A sweeps signal；
By the radio-frequency component zero setting, the low-frequency component remains unchanged, and obtains filtering signal；
Wavelet inverse transformation is carried out to the filtering signal to reconstruct to obtain the reconstruction signal.
Optionally, described that Wiener filtering processing is carried out to the reconstruction signal, obtain the defect response of the workpiece for measurement
The estimated value of signal specifically includes：
Fourier transformation, the reconstruction signal after being converted are carried out to the reconstruction signal；Reconstruct letter after the transformation
It number is expressed as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruction signal after the transformation, and X (t) is after converting
Ultrasound enters workpiece signal, and H (t) is the defect response signal of the workpiece for measurement after transformation, and N (t) is the noise signal after transformation；
According to formulaWiener filtering is carried out to the reconstruction signal after the transformation, is obtained
To the estimated value of the defect response signal of the workpiece for measurement, wherein G (t) is the reconstruction signal after the transformation, X*(t) it is X
(t) conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectral density function, h (t) be it is to be measured
The defect response signal of workpiece, n (t) is noise signal, by Snn(t)/Shh(t) it is set as 0.01 | X (t)max|2。
Optionally, the upper extreme point diffracted signal and lower extreme point diffraction letter that the defect is calculated according to the time-domain signal
Number time difference, the defect upper extreme point depth, lower extreme point depth specifically include：
Obtain the propagation time t of the upper extreme point diffracted signal of the defect1；
Obtain the propagation time t of the lower extreme point diffracted signal of the defect2；
According to formula Δ t=t2-t1Calculate the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal；
According to formulaCalculate the upper extreme point depth, wherein d1For the upper extreme point depth；
According to formulaCalculate the lower extreme point depth；Wherein, d2For the lower extreme point depth, c is
Spread speed of the longitudinal wave in the workpiece for measurement, s are the ultrasonic wave transmitting probe and receiving transducer centre-to-centre spacing of the scanner
From half.
Optionally, described to be believed according to the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point diffraction
Number time difference the height of the defect be calculated be specially：
According to formulaThe height of the defect is calculated,
In, d1For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanning
The half of the ultrasonic wave transmitting probe and receiving transducer centre distance of device, t1For the propagation of the upper extreme point diffracted signal of the defect
Time, Δ t are the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
A kind of detecting system of workpiece, defect height, including：
D scanning image collection modules, the D scanning images of the weld seam for obtaining workpiece for measurement；The D scannings image is by sweeping
Device is looked into obtain the weld seam progress D scannings of workpiece for measurement；
Defect determining module, the defective locations for determining the workpiece for measurement according to the D scannings image；
A sweeps signal acquisition module, and the A for being obtained at the defective locations according to the D scannings image sweeps signal；It is described
It is the elevation information at the defective locations that A, which sweeps signal,；
Wavelet Denoising Method module carries out Wavelet Denoising Method processing for sweeping signal to the A, obtains reconstruction signal；
Filter module, for carrying out Wiener filtering processing to the reconstruction signal, the defect for obtaining the workpiece for measurement is rung
The estimated value of induction signal；
Time-domain signal acquisition module carries out inverse Fourier transform for the estimated value to the defect response signal and obtains institute
State the time-domain signal of the defect response signal of workpiece for measurement；
Endpoint computing module, for according to the time-domain signal, calculating the upper extreme point diffraction of the defect of the workpiece for measurement
The time difference of signal and lower extreme point diffracted signal, the upper extreme point depth of the defect, lower extreme point depth；
Height computing module, for according to the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point
The height of the defect is calculated in the time difference of diffracted signal.
Optionally, the Wavelet Denoising Method module specifically includes：
Wavelet transform unit, for according to wavelet transformation formula
Signal is swept to the A to decompose, and obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is morther wavelet letter
Number, after mother wavelet function scale is stretched and translatedA is scale factor, b be translation because
Son, ψ* a,b(t) it is ψa,b(t) conjugation, y (t) are that A sweeps signal；
High frequency removal unit is used for the radio-frequency component zero setting, and the low-frequency component remains unchanged, and obtains filtering letter
Number；
Signal reconstruction unit reconstructs to obtain the reconstruction signal for carrying out wavelet inverse transformation to the filtering signal.
Optionally, the filter module specifically includes：
Fourier transform unit, for carrying out Fourier transformation, the reconstruction signal after being converted to the reconstruction signal；
Reconstruction signal after the transformation is expressed as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruct letter after the transformation
Number, X (t) is that the ultrasound after transformation enters workpiece signal, and H (t) is the defect response signal of the workpiece for measurement after transformation, and N (t) is
Noise signal after transformation；
Estimated value computing unit, for according to formulaTo the reconstruct after the transformation
Signal carries out Wiener filtering, obtains the estimated value of the defect response signal of the workpiece for measurement, wherein G (t) is after the transformation
Reconstruction signal, X*(t) be X (t) conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectrum
Density function, h (t) are the defect response signal of workpiece for measurement, and n (t) is noise signal, by Snn(t)/Shh(t) it is set as 0.01
|X(t)max|2。
Optionally, the endpoint computing module specifically includes：
Upper extreme point time acquisition unit, the propagation time t of the upper extreme point diffracted signal for obtaining the defect1；
Lower extreme point time acquisition unit, the propagation time t of the lower extreme point diffracted signal for obtaining the defect2；
Time difference calculating unit, for according to formula Δ t=t2-t1It calculates the upper extreme point diffracted signal and lower extreme point spreads out
Penetrate the time difference of signal；
Upper extreme point depth calculation unit, for according to formulaThe upper extreme point depth is calculated,
In, d1For the upper extreme point depth；
Lower extreme point depth calculation unit, for according to formulaCalculate the lower extreme point depth；Its
In, d2For the lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the ultrasonic wave of the scanner
The half of transmitting probe and receiving transducer centre distance.
Optionally, the height computing module is specially：
According to formulaThe height of the defect is calculated,
In, d1For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanning
The half of the ultrasonic wave transmitting probe and receiving transducer centre distance of device, t1For the propagation of the upper extreme point diffracted signal of the defect
Time, Δ t are the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
According to specific embodiment provided by the invention, the invention discloses following technique effects：
The present invention obtains D scanning images, and then the A for obtaining defect sweeps signal, to A by carrying out D scannings to workpiece for measurement
It sweeps signal and carries out wavelet transformation and Wiener filtering, and then obtain accurate flaw height.By wavelet transformation and wiener in the present invention
Filtering, which is combined, improves ultrasonic TOFD flaw height quantitative accuracy, can be good at inhibiting the noise in signal, removal ultrasound
A sweeps the noise signal of signal in TOFD detections, improves temporal resolution, reduces the height quantitative error of defect, improves defect inspection
Extracting rate realizes the accurate quantification of flaw height, has actual engineering application value.
Description of the drawings
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the detection method flow chart of workpiece, defect height of the embodiment of the present invention；
Fig. 2 is the detecting system module map of workpiece, defect height of the embodiment of the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of detection methods and system of workpiece, defect height, solve ultrasonic TOFD detection
The presence that middle A sweeps noise in signal causes defect upper and lower side diffracted signal to be difficult to differentiate between so that flaw height quantitative error is larger
The problem of.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is the detection method flow chart of workpiece, defect height of the embodiment of the present invention.Referring to Fig. 1, a kind of workpiece, defect is high
The detection method of degree, including：
Step 101：Obtain the D scanning images of the weld seam of workpiece for measurement；The D scannings image is by scanner to workpiece for measurement
Weld seam carry out D scannings obtain；
Step 102：The defective locations of the workpiece for measurement are determined according to the D scannings image；
Step 103：The A obtained at the defective locations according to the D scannings image sweeps signal；The A sweeps signal as institute
State the elevation information at defective locations；
Step 104：Signal is swept to the A and carries out Wavelet Denoising Method processing, obtains reconstruction signal；
Step 105：Wiener filtering processing is carried out to the reconstruction signal, obtains the defect response signal of the workpiece for measurement
Estimated value；
Step 106：Inverse Fourier transform is carried out to the estimated value of the defect response signal, obtains the workpiece for measurement
The time-domain signal of defect response signal；
Step 107：According to the time-domain signal, upper extreme point diffracted signal and the lower end of the defect of the workpiece for measurement are calculated
The point time difference of diffracted signal, the upper extreme point depth of the defect, lower extreme point depth；
Step 108：According to the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point diffracted signal
Time difference the height of the defect is calculated.
Ultrasonic TOFD flaw height quantitative accuracy can be improved using the above method, can be good at inhibiting making an uproar in signal
Sound, A sweeps the noise signal of signal in removal ultrasonic TOFD detection, improves temporal resolution, reduces the height quantitative error of defect,
Defect detection rate is improved, realizes the accurate quantification of flaw height.
It wherein first has to determine the information such as workpiece for measurement material, thickness before step 101, be selected according to workpiece for measurement information
Suitable frequency probe, size and angle are selected, ultrasonic wave transmitting probe and two center probe spacing (PCS) of receiving transducer are calculated,
Ultrasonic wave transmitting probe and receiving transducer spacing on scanner are adjusted, and it is symmetrically placed on to examined workpiece weld seam both sides, super
The relevant parameters such as PCS, emitting voltage, detecting way, repetition rate are set on sound TOFD survey meters, Scanning sensitivity is set；
Scanner is pushed to carry out D scannings to workpiece for measurement weld seam then along with weld seam parallel direction.
Wherein step 104 specifically includes：
According to wavelet transformation formulaTo the A
It sweeps signal to be decomposed, obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is mother wavelet function, will be female
Wavelet function scale stretches and is obtained after translatingA is scale factor, and b is shift factor, ψ* a,b
(t) it is ψa,b(t) conjugation, y (t) are that A sweeps signal；
By the radio-frequency component zero setting, the low-frequency component remains unchanged, and obtains filtering signal；
Wavelet inverse transformation is carried out to the filtering signal to reconstruct to obtain the reconstruction signal.
Step 105 specifically includes：
Fourier transformation, the reconstruction signal after being converted are carried out to the reconstruction signal；Reconstruct letter after the transformation
It number is expressed as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruction signal after the transformation, and x (t) is that ultrasound enters
Workpiece signal, h (t) are the defect response signal of workpiece for measurement, and n (t) is noise signal, and X (t) is that the ultrasound after transformation enters work
Part signal, H (t) are the defect response signal of the workpiece for measurement after transformation, and N (t) is the noise signal after transformation；
According to formulaWiener filtering is carried out to the reconstruction signal after the transformation, is obtained
To the estimated value of the defect response signal of the workpiece for measurement, wherein G (t) is the reconstruction signal after the transformation, X*(t) it is X
(t) conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectral density function, by Snn(t)/Shh
(t) it is set as 0.01 | X (t)max|2。
Step 107 specifically includes：
Obtain the propagation time t of the upper extreme point diffracted signal of the defect1；
Obtain the propagation time t of the lower extreme point diffracted signal of the defect2；
According to formula Δ t=t2-t1Calculate the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal；
According to formulaCalculate the upper extreme point depth, wherein d1For the upper extreme point depth；
According to formulaCalculate the lower extreme point depth；Wherein, d2For the lower extreme point depth, c is
Spread speed of the longitudinal wave in the workpiece for measurement, s are the ultrasonic wave transmitting probe and receiving transducer centre-to-centre spacing of the scanner
From half.
Step 108 is specially：
According to formulaThe height of the defect is calculated,
In, d1For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanning
The half of the ultrasonic wave transmitting probe and receiving transducer centre distance of device, t1For the propagation of the upper extreme point diffracted signal of the defect
Time, Δ t are the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
Fig. 2 is the detecting system module map of workpiece, defect height of the embodiment of the present invention.Referring to Fig. 2, a kind of workpiece, defect is high
The detecting system of degree, including：
D scannings image collection module 201, the D scanning images of the weld seam for obtaining workpiece for measurement；The D scannings image
D scannings are carried out by scanner to the weld seam of workpiece for measurement to obtain；
Defect determining module 202, the defective locations for determining the workpiece for measurement according to the D scannings image；
A sweeps signal acquisition module 203, and the A for being obtained at the defective locations according to the D scannings image sweeps signal；
It is the elevation information at the defective locations that the A, which sweeps signal,；
Wavelet Denoising Method module 204 carries out Wavelet Denoising Method processing for sweeping signal to the A, obtains reconstruction signal；
Filter module 205 obtains the defect of the workpiece for measurement for carrying out Wiener filtering processing to the reconstruction signal
The estimated value of response signal；
Time-domain signal acquisition module 206 carries out inverse Fourier transform for the estimated value to the defect response signal and obtains
To the time-domain signal of the defect response signal of the workpiece for measurement；
Endpoint computing module 207, for according to the time-domain signal, the upper extreme point for calculating the defect of the workpiece for measurement to spread out
Penetrate the time difference of signal and lower extreme point diffracted signal, the upper extreme point depth of the defect, lower extreme point depth；
Height computing module 208, for according to the upper extreme point depth, the lower extreme point depth, the upper extreme point and under
The height of the defect is calculated in the time difference of endpoint diffracted signal.
Ultrasonic TOFD flaw height quantitative accuracy can be improved using above system, improve defect detection rate, realize defect
The accurate quantification of height has actual engineering application value.
Wherein, Wavelet Denoising Method module 204 specifically includes：
Wavelet transform unit, for according to wavelet transformation formula
Signal is swept to the A to decompose, and obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is morther wavelet letter
Number, after mother wavelet function scale is stretched and translatedA is scale factor, b be translation because
Son, ψ* a,b(t) it is ψa,b(t) conjugation, y (t) are that A sweeps signal；
High frequency removal unit is used for the radio-frequency component zero setting, and the low-frequency component remains unchanged, and obtains filtering letter
Number；
Signal reconstruction unit reconstructs to obtain the reconstruction signal for carrying out wavelet inverse transformation to the filtering signal.
The filter module 205 specifically includes：
Fourier transform unit, for carrying out Fourier transformation, the reconstruction signal after being converted to the reconstruction signal；
Reconstruction signal after the transformation is expressed as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruct letter after the transformation
Number, x (t) is that ultrasound enters workpiece signal, and h (t) is the defect response signal of workpiece for measurement, and n (t) is noise signal, and X (t) is
Ultrasound after transformation enters workpiece signal, and H (t) is the defect response signal of the workpiece for measurement after transformation, and N (t) is after converting
Noise signal；
Estimated value computing unit, for according to formulaTo the reconstruct after the transformation
Signal carries out Wiener filtering, obtains the estimated value of the defect response signal of the workpiece for measurement, wherein G (t) is after the transformation
Reconstruction signal, X*(t) be X (t) conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectrum
Density function, by Snn(t)/Shh(t) it is set as 0.01 | X (t)max|2。
Endpoint computing module 207 specifically includes：
Upper extreme point time acquisition unit, the propagation time t of the upper extreme point diffracted signal for obtaining the defect1；
Lower extreme point time acquisition unit, the propagation time t of the lower extreme point diffracted signal for obtaining the defect2；
Time difference calculating unit, for according to formula Δ t=t2-t1It calculates the upper extreme point diffracted signal and lower extreme point spreads out
Penetrate the time difference of signal；
Upper extreme point depth calculation unit, for according to formulaThe upper extreme point depth is calculated,
In, d1For the upper extreme point depth；
Lower extreme point depth calculation unit, for according to formulaCalculate the lower extreme point depth；Its
In, d2For the lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the ultrasonic wave of the scanner
The half of transmitting probe and receiving transducer centre distance.
Height computing module 208 is specially：
According to formulaThe height of the defect is calculated,
In, d1For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanning
The half of the ultrasonic wave transmitting probe and receiving transducer centre distance of device, t1For the propagation of the upper extreme point diffracted signal of the defect
Time, Δ t are the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, just to refer each other for identical similar portion between each embodiment.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so description is fairly simple, related place is said referring to method part
It is bright.
Principle and implementation of the present invention are described for specific case used herein, and above example is said
The bright method and its core concept for being merely used to help understand the present invention；Meanwhile for those of ordinary skill in the art, foundation
The thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of detection method of workpiece, defect height, which is characterized in that including：
Obtain the D scanning images of the weld seam of workpiece for measurement；The D scannings image carries out D by scanner to the weld seam of workpiece for measurement
Scanning obtains；
The defective locations of the workpiece for measurement are determined according to the D scannings image；
The A obtained at the defective locations according to the D scannings image sweeps signal；It is at the defective locations that the A, which sweeps signal,
Elevation information；
Signal is swept to the A and carries out Wavelet Denoising Method processing, obtains reconstruction signal；
Wiener filtering processing is carried out to the reconstruction signal, obtains the estimated value of the defect response signal of the workpiece for measurement；
Inverse Fourier transform is carried out to the estimated value of the defect response signal, obtains the defect response signal of the workpiece for measurement
Time-domain signal；
According to the time-domain signal, the upper extreme point diffracted signal and lower extreme point diffracted signal of the defect of the workpiece for measurement are calculated
Time difference, upper extreme point depth, lower extreme point depth；
It is calculated according to the time difference of the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point diffracted signal
Obtain the height of the defect.
2. detection method according to claim 1, which is characterized in that described to be swept at signal progress Wavelet Denoising Method to the A
Reason, obtains reconstruction signal and specifically includes：
According to wavelet transformation formulaLetter is swept to the A
It number is decomposed, obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is mother wavelet function, by morther wavelet
Function scale stretches and is obtained after translatingA is scale factor, and b is shift factor, ψ* a,b(t) it is
ψa,b(t) conjugation, y (t) are that A sweeps signal；
By the radio-frequency component zero setting, the low-frequency component remains unchanged, and obtains filtering signal；
Wavelet inverse transformation is carried out to the filtering signal to reconstruct to obtain the reconstruction signal.
3. detection method according to claim 1, which is characterized in that described to be carried out at Wiener filtering to the reconstruction signal
Reason, obtains the estimated value of the defect response signal of the workpiece for measurement, specifically includes：
Fourier transformation, the reconstruction signal after being converted are carried out to the reconstruction signal；Reconstruction signal table after the transformation
It is shown as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruction signal after the transformation, and X (t) is the ultrasound after transformation
Into workpiece signal, H (t) is the defect response signal of the workpiece for measurement after transformation, and N (t) is the noise signal after transformation；
According to formulaWiener filtering is carried out to the reconstruction signal after the transformation, obtains institute
State the estimated value of the defect response signal of workpiece for measurement, wherein G (t) is the reconstruction signal after the transformation, X*(t) it is X (t)
Conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectral density function, h (t) be work to be measured
The defect response signal of part, n (t) is noise signal, by Snn(t)/Shh(t) it is set as 0.01 | X (t)max|2。
4. detection method according to claim 1, which is characterized in that described to calculate the defect according to the time-domain signal
Upper extreme point diffracted signal and the time difference of lower extreme point diffracted signal, the upper extreme point depth of the defect, lower extreme point depth it is specific
Including：
Obtain the propagation time t of the upper extreme point diffracted signal of the defect1；
Obtain the propagation time t of the lower extreme point diffracted signal of the defect2；
According to formula Δ t=t2-t1Calculate the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal；
According to formulaCalculate the upper extreme point depth, wherein d1For the upper extreme point depth；
According to formulaCalculate the lower extreme point depth；Wherein, d2For the lower extreme point depth, c is longitudinal wave
Spread speed in the workpiece for measurement, s are the ultrasonic wave transmitting probe and receiving transducer centre distance of the scanner
Half.
5. detection method according to claim 4, which is characterized in that described according to the upper extreme point depth, the lower end
Point depth, the upper extreme point and lower extreme point diffracted signal time difference the height of the defect be calculated be specially：
According to formulaCalculate the height of the defect, wherein d1
For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanner
The half of ultrasonic wave transmitting probe and receiving transducer centre distance, t1For the upper extreme point diffracted signal of the defect propagation when
Between, Δ t is the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
6. a kind of detecting system of workpiece, defect height, which is characterized in that including：
D scanning image collection modules, the D scanning images of the weld seam for obtaining workpiece for measurement；The D scannings image is by scanner
D scannings are carried out to the weld seam of workpiece for measurement to obtain；
Defect determining module, the defective locations for determining the workpiece for measurement according to the D scannings image；
A sweeps signal acquisition module, and the A for being obtained at the defective locations according to the D scannings image sweeps signal；The A is swept
Signal is the elevation information at the defective locations；
Wavelet Denoising Method module carries out Wavelet Denoising Method processing for sweeping signal to the A, obtains reconstruction signal；
Filter module obtains the defect response letter of the workpiece for measurement for carrying out Wiener filtering processing to the reconstruction signal
Number estimated value；
Time-domain signal acquisition module carries out inverse Fourier transform for the estimated value to the defect response signal and obtains described wait for
Survey the time-domain signal of the defect response signal of workpiece；
Endpoint computing module, for according to the time-domain signal, calculating the upper extreme point diffracted signal of the defect of the workpiece for measurement
With the time difference of lower extreme point diffracted signal, the upper extreme point depth of the defect, lower extreme point depth；
Height computing module, for according to the upper extreme point depth, the lower extreme point depth, the upper extreme point and lower extreme point diffraction
The height of the defect is calculated in the time difference of signal.
7. detecting system according to claim 6, which is characterized in that the Wavelet Denoising Method module specifically includes：
Wavelet transform unit, for according to wavelet transformation formula
Signal is swept to the A to decompose, and obtains radio-frequency component and low-frequency component that the A sweeps signal；Wherein, ψ (t) is morther wavelet letter
Number, after mother wavelet function scale is stretched and translatedA is scale factor, b be translation because
Son, ψ* a,b(t) it is ψa,b(t) conjugation, y (t) are that A sweeps signal；
High frequency removal unit, for by the radio-frequency component zero setting, the low-frequency component to remain unchanged, and obtains filtering signal；
Signal reconstruction unit reconstructs to obtain the reconstruction signal for carrying out wavelet inverse transformation to the filtering signal.
8. detecting system according to claim 6, which is characterized in that the filter module specifically includes：
Fourier transform unit, for carrying out Fourier transformation, the reconstruction signal after being converted to the reconstruction signal；It is described
Reconstruction signal after transformation is expressed as：G (t)=X (t) * H (t)+N (t)；Wherein, G (t) is the reconstruction signal after the transformation, X
(t) enter workpiece signal for the ultrasound after transformation, H (t) is the defect response signal of the workpiece for measurement after transformation, and N (t) is transformation
Noise signal afterwards；
Estimated value computing unit, for according to formulaTo the reconstruction signal after the transformation
Wiener filtering is carried out, the estimated value of the defect response signal of the workpiece for measurement is obtained, wherein G (t) is the weight after the transformation
Structure signal, X*(t) be X (t) conjugation, Snn(t) be n (t) power spectral density function, Shh(t) be h (t) power spectral density
Function, h (t) are the defect response signal of workpiece for measurement, and n (t) is noise signal, by Snn(t)/Shh(t) it is set as 0.01 | X
(t)max|2。
9. detecting system according to claim 6, which is characterized in that the endpoint computing module specifically includes：
Upper extreme point time acquisition unit, the propagation time t of the upper extreme point diffracted signal for obtaining the defect1；
Lower extreme point time acquisition unit, the propagation time t of the lower extreme point diffracted signal for obtaining the defect2；
Time difference calculating unit, for according to formula Δ t=t2-t1Calculate the upper extreme point diffracted signal and lower extreme point diffraction letter
Number time difference；
Upper extreme point depth calculation unit, for according to formulaCalculate the upper extreme point depth, wherein d1For
The upper extreme point depth；
Lower extreme point depth calculation unit, for according to formulaCalculate the lower extreme point depth；Wherein, d2
For the lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is that the ultrasonic wave of the scanner emits
The half of probe and receiving transducer centre distance.
10. detecting system according to claim 6, which is characterized in that the height computing module is specially：
According to formulaCalculate the height of the defect, wherein d1
For upper extreme point depth, d2For lower extreme point depth, c is spread speed of the longitudinal wave in the workpiece for measurement, and s is the scanner
The half of ultrasonic wave transmitting probe and receiving transducer centre distance, t1For the upper extreme point diffracted signal of the defect propagation when
Between, Δ t is the time difference of the upper extreme point diffracted signal and lower extreme point diffracted signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810250129.6A CN108508093A (en) | 2018-03-26 | 2018-03-26 | A kind of detection method and system of workpiece, defect height |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810250129.6A CN108508093A (en) | 2018-03-26 | 2018-03-26 | A kind of detection method and system of workpiece, defect height |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108508093A true CN108508093A (en) | 2018-09-07 |
Family
ID=63378396
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810250129.6A Pending CN108508093A (en) | 2018-03-26 | 2018-03-26 | A kind of detection method and system of workpiece, defect height |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108508093A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109900805A (en) * | 2019-04-08 | 2019-06-18 | 大连理工大学 | Defect quantitative detection method in the blind area TOFD based on frequency-domain sparse inverting |
| CN110967409A (en) * | 2018-09-29 | 2020-04-07 | 东莞灵虎智能科技有限公司 | Method for extracting and identifying original data features based on multi-channel ultrasonic flaw detection |
| CN113960178A (en) * | 2021-10-21 | 2022-01-21 | 南京裕扬工程检测有限责任公司 | Precise scanning method based on TOFD technology |
| CN115451876A (en) * | 2022-09-23 | 2022-12-09 | 成都飞机工业（集团）有限责任公司 | Device and method for measuring width of annular groove in revolving body part |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1804611A (en) * | 2005-12-27 | 2006-07-19 | 哈尔滨工业大学 | Ultrasonic time-of-flight diffraction detection method based on synthetic aperture focusing technique |
| CN101839895A (en) * | 2009-12-17 | 2010-09-22 | 哈尔滨工业大学 | Near-surface defect recognition method based on ultrasonic TOFD |
| CN102435675A (en) * | 2011-09-23 | 2012-05-02 | 南昌航空大学 | Ultrasonic TOFD technology detection method for butt seam of different thickness plates |
| US9109433B2 (en) * | 2005-08-01 | 2015-08-18 | Baker Hughes Incorporated | Early kick detection in an oil and gas well |
| CN105973990A (en) * | 2015-09-16 | 2016-09-28 | 中国核工业二三建设有限公司 | Inclined crack TOFD quantitative detection method based on geometric relationship |
| CN107449829A (en) * | 2017-08-09 | 2017-12-08 | 上海船舶工程质量检测有限公司 | A kind of butt weld Non-Destructive Testing acceptance method |
| CN107655974A (en) * | 2017-09-29 | 2018-02-02 | 宁波恒信工程检测有限公司 | A kind of TOFD automatic scannings device |
-
2018
- 2018-03-26 CN CN201810250129.6A patent/CN108508093A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9109433B2 (en) * | 2005-08-01 | 2015-08-18 | Baker Hughes Incorporated | Early kick detection in an oil and gas well |
| CN1804611A (en) * | 2005-12-27 | 2006-07-19 | 哈尔滨工业大学 | Ultrasonic time-of-flight diffraction detection method based on synthetic aperture focusing technique |
| CN101839895A (en) * | 2009-12-17 | 2010-09-22 | 哈尔滨工业大学 | Near-surface defect recognition method based on ultrasonic TOFD |
| CN102435675A (en) * | 2011-09-23 | 2012-05-02 | 南昌航空大学 | Ultrasonic TOFD technology detection method for butt seam of different thickness plates |
| CN105973990A (en) * | 2015-09-16 | 2016-09-28 | 中国核工业二三建设有限公司 | Inclined crack TOFD quantitative detection method based on geometric relationship |
| CN107449829A (en) * | 2017-08-09 | 2017-12-08 | 上海船舶工程质量检测有限公司 | A kind of butt weld Non-Destructive Testing acceptance method |
| CN107655974A (en) * | 2017-09-29 | 2018-02-02 | 宁波恒信工程检测有限公司 | A kind of TOFD automatic scannings device |
Non-Patent Citations (2)
| Title |
|---|
| 周红明: "薄材焊缝自动化超声TOFD成像检测关键技术研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
| 曾向阳 著: "《智能水中目标识别》", 31 March 2016, 国防工业出版社 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110967409A (en) * | 2018-09-29 | 2020-04-07 | 东莞灵虎智能科技有限公司 | Method for extracting and identifying original data features based on multi-channel ultrasonic flaw detection |
| CN109900805A (en) * | 2019-04-08 | 2019-06-18 | 大连理工大学 | Defect quantitative detection method in the blind area TOFD based on frequency-domain sparse inverting |
| CN113960178A (en) * | 2021-10-21 | 2022-01-21 | 南京裕扬工程检测有限责任公司 | Precise scanning method based on TOFD technology |
| CN115451876A (en) * | 2022-09-23 | 2022-12-09 | 成都飞机工业（集团）有限责任公司 | Device and method for measuring width of annular groove in revolving body part |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104007176B (en) | Full-wave field detection system and method of complex geotechnical engineering medium | |
| CN108508093A (en) | A kind of detection method and system of workpiece, defect height | |
| CN103148815B (en) | Based on the thickness of thin layer supersonic detection method of sound pressure reflection coefficient autocorrelation function | |
| CN102636568B (en) | Finite element ultrasonic imaging method used for detecting defect in concrete | |
| CN110346453B (en) | Method for rapidly detecting reflection echoes of small defect arrays in concrete structure | |
| Zhang et al. | Monte Carlo inversion of ultrasonic array data to map anisotropic weld properties | |
| CN111855809A (en) | Crack morphology reconstruction method based on compound mode full focusing | |
| Michaels | Ultrasonic wavefield imaging: Research tool or emerging NDE method? | |
| CN114235962B (en) | Anisotropic structure-oriented ultrasonic guided wave imaging method and system | |
| CN104360046A (en) | Comprehensive geophysical-prospecting combined diagnosis method for hidden danger inside wharf concrete structure | |
| CN109900805A (en) | Defect quantitative detection method in the blind area TOFD based on frequency-domain sparse inverting | |
| CN104897777A (en) | Method for improving longitudinal resolution of TOFD (time of flight diffraction) detection with Burg algorithm based autoregressive spectrum extrapolation technology | |
| Cao et al. | A correlation-based approach to corrosion detection with lamb wave mode cutoff | |
| JP2006200901A (en) | Ultrasonic inspection method and device | |
| CN101819182B (en) | Method for reconstructing defect shape in non-uniform medium | |
| CN105044215A (en) | Non-destructive material sound velocity field measurement method | |
| KR101082085B1 (en) | Ultrasonic imaging device and Method for controlling the same | |
| Bouden et al. | Signal processing methods for materials defects detection | |
| CN102798889B (en) | Phased source consistency determining method | |
| Wiggenhauser | Advanced NDT methods for quality assurance of concrete structures | |
| Li et al. | Research on the imaging of concrete defect based on the pulse compression technique | |
| CN112461930B (en) | Concrete internal defect imaging method, system and storage medium | |
| Eisenmann et al. | Progress in quantitative GPR development at CNDE | |
| US6393917B1 (en) | System and method for ultrasonic image reconstruction using mode-converted Rayleigh wave | |
| Zatar et al. | Ultrasonic Pulse Echo Signals for Detection and Advanced Assessment of Reinforced Concrete Anomalies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180907 |