CN108444921A - A kind of increasing material manufacturing component online test method based on signal correlation analysis - Google Patents
A kind of increasing material manufacturing component online test method based on signal correlation analysis Download PDFInfo
- Publication number
- CN108444921A CN108444921A CN201810224121.2A CN201810224121A CN108444921A CN 108444921 A CN108444921 A CN 108444921A CN 201810224121 A CN201810224121 A CN 201810224121A CN 108444921 A CN108444921 A CN 108444921A
- Authority
- CN
- China
- Prior art keywords
- laser
- signal
- ultrasonic
- pulse laser
- interferometer
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
- G01N2021/1706—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids in solids
Abstract
The increasing material manufacturing component online test method based on signal correlation analysis that the invention discloses a kind of.It is calculated including structure laser-ultrasound automatic checkout system, the excitation of laser ultrasonic signal and the different coefficient of signal acquisition, ultrasonic signal and defect recognition positions three steps.The technical effects of the invention are that, by to component surface detection zone gridding, utilize laser-ultrasound automatic checkout system, obtain in X direction and Y-direction propagate ultrasonic signal, and carry out different coefficient calculating, it realizes increasing material manufacturing component defect quickly to position online, is effectively improved detection efficiency.
Description
Technical field
Patent of the present invention belongs to field of non destructive testing, more particularly to a kind of increasing material manufacturing component based on signal correlation analysis
Online test method.
Background technology
Increasing material manufacturing be one kind based on digital three-dimensional CAD model file, with high energy electron gun or other modes, by liquid
The special materials such as body, molten mass, powder, silk, piece carry out successively accumulation and cohere, and final superposition molding directly constructs entity
Technology.This technology, which has, saves material, may be implemented that traditional handicraft is difficult to or the manufacture of labyrinth that can not process etc. is excellent
Point is used widely in the important industry such as space flight and aviation, medical treatment.But at the same time, increasing material manufacturing exists by technological parameter control
Improper caused defect is made, main hole, buckling deformation, nodularization, there are no cofusing particles etc..These defects can seriously affect structure
The performance of part constrains the practical application in industry of increases material manufacturing technology.
Product quality is improved in order to which defect is effectively detected, offline or online non-destructive testing technology can be used.Offline inspection
Technology is only used for the finished product detection after the completion of manufacture, and such as 104597125 A of application publication number CN, date of publication is May 6 in 2015
The patent document of day discloses a kind of ultrasound detection control method and device for 3D printing part, is set by controlling ultrasound detection
Standby probe is scanned according to the incidence angle of the corresponding test position of each measuring point to be checked, can improve the detection letter of 3D printing part
Number signal-to-noise ratio and defect detection rate.But it is complicated for operation, it need to determine measuring point to be checked, and it can only detect product after shaping
Defect adjusting parameter cannot control product manufacturing quality in time.
On-line checking can find defect and automatic or manual intervention manufacturing process in time, improve increasing material manufacturing component quality.
During existing increasing material manufacturing, online test method mainly has laser-ultrasound method, infrared thermography, CCD imaging methods etc..Wherein
Laser-ultrasound has the advantages such as non-contact, high sensitivity, detectable complex shaped components, particularly suitable for increasing material manufacturing process
On-line real-time measuremen, such as application publication number CN106018288A, date of publication is that the patent document on October 12nd, 2016 discloses
A kind of method of the online non-destructive testing increasing material manufacturing part of laser-ultrasound, but this method uses point-by-point scanning so that number of scan points
Excessively, scan path is complicated, when check fee, reduces the detection efficiency of practical increasing material manufacturing.
Invention content
To improve detection efficiency of laser-ultrasound during increasing material manufacturing, the quick identification and positioning of defect are realized.This
Invention proposes a kind of increasing material manufacturing component online test method based on signal correlation analysis.
In order to achieve the above technical purposes, the technical scheme is that,
A kind of increasing material manufacturing component online test method based on signal correlation analysis, includes the following steps：
Step 1：Laser-ultrasound automatic checkout system is built, the system comprises movement scanning and searching mechanism, two sets of laser-ultrasounds
Detection device, data acquisition and processing system.Wherein movement scanning and searching mechanism includes X/Z axis automatic scannings frame, Y/Z axis automatic scannings
Frame, motion control device；Two sets of laser ultrasonic detection devices include pulse laser and laser interferometer；Data acquire and processing
System includes data collecting card and computer.
Step 2：The excitation of laser ultrasonic signal and signal acquisition are carried out to the component during increasing material manufacturing, with substrate
Centre of surface is origin, and substrate surface is the faces XOY, establishes rectangular coordinate system in space OXYZ, and pulse laser is arranged and laser is dry
The initial position of interferometer.According to the whole height H of the components three-dimensional model and thickness deltat H of slicing layer, pulse laser is determined
And the moving step pitch of laser interferometer in z-direction.According to the width of components three-dimensional model and length and accuracy of detection demand
Determine the moving step pitch of pulse laser and laser interferometer in the x, y direction.Ultrasonic signal is encouraged by pulse laser,
Laser interferometer receives signal, and data acquisition and processing system acquires ultrasound data and preserves to computer.
Step 3：The different coefficient of ultrasonic signal calculates and defect recognition positioning, first in extraction step two in X-direction and
The ultrasound data acquired in Y-direction each time after the completion of laser ultrasonic detection, first calculates different location point in X-direction
Covariance, standard deviation between signal collected and signal collected different coefficient between any two, then calculate in Y-direction
Covariance, standard deviation between different location point is signal collected and signal collected different coefficient between any two.Then
The sum of the different coefficient that X-direction adds up with different location test point in Y-direction can be obtained according to different coefficient, further according to given
Threshold value obtains the region of existing defects, finally as the position where the common region judgement defect of existing defects on X and Y-direction.
The method in the step two, carries out component the step of the excitation of laser ultrasonic signal and signal acquisition
Suddenly include：
Step 1：Pulse laser and the initial position of laser interferometer are set, and wherein pulse laser is apart from substrate surface
Distance be d1, distance of the laser interferometer apart from substrate surface be d2, adjust pulse laser and laser interferometer orientation,
Ensure laser light incident point apart from substrate boundaries distance d3, it is maximum value to make the ultrasonic signal that laser interferometer receives at this time.
Step 2：According to the whole height H of the components three-dimensional model and thickness deltat H of slicing layer, determine pulse laser and
Distance h value ranges [d1, the h that laser interferometer moves in the Z-axis directionz], wherein hzH is divided into K equal portions, i.e., by=H+d1
The laser ultrasonic energized position for choosing K Z-direction, determines the movement on pulse laser and laser interferometer Z-direction
Step pitch Δ Z；Δ Z is determined according to the specific height of component and accuracy of detection demand.
Step 3：According to the width of components three-dimensional model and length and accuracy of detection demand, by model kth time detection
Two dimensional surface is divided into M equal portions in X direction, and N equal portions are divided into along Y-direction, determines pulse laser and laser interferometer in X
Moving step pitch Δ X on direction and moving step pitch Δ Y in the Y direction, two sets of laser ultrasonic detection devices of control are in X/Y plane
Interior priority is moved with Y-direction along the X direction, while pulse laser realizes that the excitation of laser ultrasonic signal, laser interferometer are real
Existing signal receives.When detecting for the first time, computer is in real time by the ultrasonic signal of each test point position in X-direction and Y-direction
It is preserved, the signal of acquisition is denoted as S1,m、E1,n, after signal preserves, pulse laser and laser interferometer rise along the Z direction
One step delta Z starts second and detects after the completion of the set new time processing number of plies, pulse laser and laser
Interferometer continues to encourage and receive the ultrasonic signal in X and Y-direction, obtains new signal S2,m、E2,n, it is similar, i.e., successively
Obtain the signal S of X-direction1,m,S2,m,…,Sk,m, Y-direction signal E1,n,E2,n,…,Ek,n, until component machines, wherein
M=1,2 ..., M, n=1,2 ..., N.
The method, in the step three, the different coefficient of ultrasonic signal calculates and defect recognition positioning step packet
It includes：
Step 1：The different coefficient of ultrasonic signal calculates, when acquisition signal is Sk,mWhen (m=1,2 ..., M), S is first found outK,i
And SK,j(wherein i, j ∈ [1, M], and i ≠ j) related coefficient：
S is found out againK,iAnd SK,jDifferent coefficient：
αK,i,j=1- ρK,i,j
When acquisition signal is EK,nWhen (n=1,2 ..., N), E is first found outk,iAnd Ek,j(wherein i, j ∈ [1, N], and i ≠ j)
Related coefficient：
E is found out againK,iAnd EK,jDifferent coefficient：
βk,i,j=1- δk,i,j
Step 2：Defect recognition positions, stored different factor alpha in extraction step threek,i,jAnd βk,i,j, respectively to its into
Row read group total,
Given threshold ε, works as γk,i>When ε, exist on the scan path in kth time detection at this time in X-direction corresponding to i points
Defect works as σk,j>When ε, existing defects on the scan path in kth time detection at this time in Y-direction corresponding to j points, in conjunction with X, the side Y
To the path of defect present in different location point, it may be determined that the specific location (S of defectk,i, Ek,j)。
The technical effects of the invention are that by component surface detection zone gridding, examined automatically using laser-ultrasound
Examining system obtains in X direction and the ultrasonic signal propagated of Y-direction, and carries out different coefficient calculating, realize increasing material manufacturing structure
Part defect quickly positions online, is effectively improved detection efficiency.
The invention will be further described below in conjunction with the accompanying drawings.
Description of the drawings
Fig. 1 is detecting system schematic diagram of the present invention；
Fig. 2 is the structural schematic diagram of laser ultrasonic detection system scanning and searching mechanism of the present invention；
Fig. 3 is laser-ultrasound scan path schematic diagram of the present invention；
Fig. 4 is flow diagram of the present invention；
Fig. 5 is laser-ultrasound scan path schematic diagram in the specific embodiment of the invention；
1 it is X/Z axis automatic scannings frame in wherein Fig. 2,2 be Y/Z axis automatic scannings frame, 3 be pulse laser, 4 is laser
Interferometer, 5 be substrate, 6 be component.
Specific implementation mode
Referring to Fig. 1, to build a laser-ultrasound automatic checkout system as step 1, including movement scanning and searching mechanism, two sets
Laser ultrasonic detection device, data acquisition and processing system.Movement scanning and searching mechanism includes that X/Z axis automatic scannings frame, Y/Z axis are automatic
Scanning frame, supporting rack, motion control device；Wherein X/Z axis automatic scanning frame, Y/Z axis automatic scanning framves by Serve Motor Control,
X/Y, Y/Z axis realize the transmission of movement, kinematic accuracy 0.05mm by ball screw assembly,；Supporting rack can be respectively along X-direction and Y
Axis direction realizes that the rotation of certain angle, 0.1 degree of rotary motion precision realize X/Z by computer and motion control device
With the motion control of Y/Z；Pulse laser and laser interferometer are mounted on supporting rack, laser and laser interferometer it is specific
Model can do corresponding adjustment according to practical tested component, in this detection example, select Nd：YAG laser, F-P laser are dry
Interferometer, the PCIe9852 data collecting cards that sample frequency is 200MHz acquire ultrasonic signal data.
Step 2: the excitation of laser ultrasonic signal and signal acquisition
(1) initial position of pulse laser and laser interferometer is set, and wherein pulse laser is apart from substrate surface
Distance is d1, distance d2 of the laser interferometer apart from substrate surface, adjusts the orientation of pulse laser and laser interferometer, is ensured
For laser light incident point apart from substrate boundaries distance d3, it is maximum value to make the ultrasonic signal that laser interferometer receives at this time.Adjustment branch
The angle of support makes pulse laser Laser emission line and the normal angle θ of component surface change within the scope of 0 degree to 90 degree.
In this example, d1=d2=10mm, d3=5mm.
(2) it according to the whole height H of the components three-dimensional model and thickness deltat H of slicing layer, determines pulse laser and swashs
Distance h value ranges [d1, the h that optical interferometer moves in the Z-axis directionz], wherein hzH is divided into K equal portions, that is, selected by=H+d1
The laser ultrasonic energized position for taking K Z-direction determines the mobile step on pulse laser and laser interferometer Z-direction
Away from Δ Z；Δ Z is determined according to the specific height of component and accuracy of detection demand.H=80mm in this example, Δ H=0.05mm, k=
160, Δ Z=0.5mm.
(3) according to the width of components three-dimensional model and length and accuracy of detection demand, by the two dimension of the 1st detection of model
Plane is divided into 1700 equal portions in X direction, is divided into 1500 equal portions along Y-direction, determines pulse laser and laser interferometer
Moving step pitch Δ X in the X direction and moving step pitch Δ Y in the Y direction, two sets of laser ultrasonic detection devices of control are flat in XY
It is successively moved along the X direction with Y-direction in face, while pulse laser realizes the excitation of laser ultrasonic signal, laser interferometer
Realize that signal receives.Δ X=0.05mm, Δ Y=0.05mm are set in this example.
(4) when detecting for the first time, computer is in real time by the ultrasonic signal of each test point position in X-direction and Y-direction
It is preserved, the signal of acquisition is denoted as S1,m、E1,n, after signal preserves, pulse laser and laser interferometer are along in Z-direction
Rise a step-length 0.5mm, after the completion of set 10 layers of new machined layer number, start second and detect, pulse laser and
Laser interferometer continues to encourage and receive the ultrasonic signal in X and Y-direction, obtains new signal S2,m、E2,n, it is similar, i.e.,
The signal S of X-direction is obtained successively1,m,S2,m,…,S160,m, Y-direction signal E1,n,E2,n,…,E160,n, until component processes
At, wherein m=1,2 ..., M, n=1,2 ..., N.In this example, the signal that the 1st detection obtains X-direction is
S1,1,S1,2,…,S1,1700, Y-direction signal be E1,1,E1,2,…,E1,1500。
Step 3: the different coefficient of ultrasonic signal calculates and defect recognition location Calculation
The ultrasound data that is acquired in X-direction and in Y-direction first in extraction step two, each time laser ultrasonic detection
After the completion, covariance between different location point is signal collected in X-direction, standard deviation and signal collected two are first calculated
Different coefficient between two, then calculate covariance, standard deviation and institute between different location point is signal collected in Y-direction
Acquire the different coefficient of signal between any two.Then X-direction and different location test point in Y-direction can be obtained according to different coefficient
The sum of different coefficient to add up obtains the region of existing defects further according to given threshold value, is finally lacked by existing on X and Y-direction
Position where sunken common region judgement defect.
Wherein, the different coefficient of ultrasonic signal calculates and the step of defect recognition positions includes：
When acquisition signal is Sk,mWhen (m=1,2 ..., M), S is first found outK,iAnd SK,j(wherein i, j ∈ [1, M], and i ≠ j)
Related coefficient：
S is found out againK,iAnd SK,jDifferent coefficient：
αK,i,j=1- ρK,i,j
When acquisition signal is EK,nWhen (n=1,2 ..., N), E is first found outK,iAnd EK,j(wherein i, j ∈ [1, N], and i ≠ j)
Related coefficient：
E is found out againK,iAnd EK,jDifferent coefficient：
βk,i,j=1- δk,i,j
Stored different factor alpha in extraction step threek,i,jAnd βk,i,j, read group total is carried out to it respectively,
Given threshold ε=0.6, works as γk,i>When ε, on the scan path in kth time detection at this time in X-direction corresponding to i points
Existing defects work as σk,j>When ε, existing defects on the scan path in kth time detection at this time in Y-direction corresponding to j points, in conjunction with X,
The path of defect present in Y-direction different location point, it may be determined that the specific location (S of one of defect1,10, E1,20)。
Claims (3)
1. a kind of increasing material manufacturing component online test method based on signal correlation analysis, which is characterized in that include the following steps：
Step 1：Laser-ultrasound automatic checkout system is built, the system comprises movement scanning and searching mechanism, two sets of laser ultrasonic detections
Device, data acquisition and processing system；Wherein movement scanning and searching mechanism include X/Z axis automatic scannings frame, Y/Z axis automatic scannings frame,
Motion control device, two sets of laser ultrasonic detection devices include pulse laser and laser interferometer, and data acquire and processing system
System includes data collecting card and computer；
Step 2：The excitation of laser ultrasonic signal and signal acquisition are carried out to the component during increasing material manufacturing, with substrate surface
Center is origin, and substrate surface is the faces XOY, establishes rectangular coordinate system in space OXYZ, and pulse laser and laser interferometer is arranged
Initial position；According to the whole height H of the components three-dimensional model and thickness deltat H of slicing layer, determine pulse laser and
The moving step pitch of laser interferometer in z-direction；According to the width of components three-dimensional model, length and accuracy of detection demand, determine
The moving step pitch of pulse laser and laser interferometer in the x, y direction；Ultrasonic signal, laser are encouraged by pulse laser
Interferometer receives signal, and data acquisition and processing system acquires ultrasound data and preserves to computer；
Step 3：The different coefficient of ultrasonic signal calculates and defect recognition positioning, in the X-direction and side Y first in extraction step two
The ultrasound data acquired upwards each time after the completion of laser ultrasonic detection, first calculates different location point in X-direction and is adopted
Collect covariance, standard deviation and the signal collected different coefficient between any two between signal, then calculates different in Y-direction
Covariance, standard deviation between location point is signal collected and signal collected different coefficient between any two, then basis
Different coefficient can obtain the sum of the different coefficient that X-direction adds up with different location test point in Y-direction, further according to given threshold value
The region of existing defects is obtained, finally as the position where the common region judgement defect of existing defects on X and Y-direction.
2. according to the method described in claim 1, it is characterized in that, in the step two, laser ultrasonic is carried out to component
Signal encourages and the step of signal acquisition includes：
Step 1：Pulse laser and the initial position of laser interferometer be set, wherein pulse laser apart from substrate surface away from
From for d1, distance of the laser interferometer apart from substrate surface is d2, adjusts the orientation of pulse laser and laser interferometer, is ensured
For laser light incident point apart from substrate boundaries distance d3, it is maximum value to make the ultrasonic signal that laser interferometer receives at this time；
Step 2：According to the whole height H of the components three-dimensional model and thickness deltat H of slicing layer, pulse laser and laser are determined
Distance h value ranges [d1, the h that interferometer moves in the Z-axis directionz], wherein hzH is divided into K equal portions, that is, chosen by=H+d1
The laser ultrasonic energized position of K Z-direction determines the moving step pitch Δ Z on pulse laser and laser interferometer Z-direction,
Δ Z is determined according to the specific height of component and accuracy of detection demand；
Step 3：According to the width of components three-dimensional model, length and accuracy of detection demand, by the two dimensional surface mould of kth time detection
Type is divided into M equal portions in X direction, is divided into N equal portions along Y-direction, determines pulse laser and laser interferometer in the X direction
Moving step pitch Δ X and moving step pitch Δ Y in the Y direction, two sets laser ultrasonic detection devices of control priority in X/Y plane
It is moved along the X direction with Y-direction, while pulse laser realizes that signal is realized in the excitation of laser ultrasonic signal, laser interferometer
It receives；When detecting for the first time, computer in real time protects the ultrasonic signal of each test point position in X-direction and Y-direction
It deposits, the signal of acquisition is denoted as S1,m、E1,n, after signal preserves, pulse laser and laser interferometer rise a step along the Z direction
Long Δ Z starts second and detects after the completion of the set new time processing number of plies, pulse laser and laser interferometer
Continue to encourage and receive the ultrasonic signal in X and Y-direction, obtains new signal S2,m、E2,n, it is similar, i.e., the side X is obtained successively
To signal S1,m,S2,m,…,Sk,m, Y-direction signal E1,n,E2,n,…,Ek,n, until component machines, wherein m=1,
2 ..., M, n=1,2 ..., N.
3. according to the method described in claim 1, it is characterized in that, in the step three, the different coefficient meter of ultrasonic signal
It calculates and defect recognition positioning step includes：
Step 1：The different coefficient of ultrasonic signal calculates, when acquisition signal is Sk,mWhen (m=1,2 ..., M), S is first found outK,iWith
SK,j(wherein i, j ∈ [1, M], and i ≠ j) related coefficient：
S is found out againk,iAnd Sk,jDifferent coefficient：
αK,i,j=1- ρK,i,j
When acquisition signal is Ek,nWhen (n=1,2 ..., N), E is first found outk,iAnd Ek,j(wherein i, j ∈ [1, N], and i ≠ j) is related
Coefficient：
E is found out againK,iAnd EK,jDifferent coefficient：
βk,i,j=1- δk,i,j
Step 2：Defect recognition positions, and extracts different factor alpha stored in the claim 3k,i,jAnd βk,i,j, respectively to it
Carry out read group total：
Given threshold ε, works as γk,i>When ε, existing defects on the scan path in kth time detection at this time in X-direction corresponding to i points,
Work as σk,j>When ε, existing defects on the scan path in kth time detection at this time in Y-direction corresponding to j points are different in conjunction with X, Y-direction
The path of defect present in location point, it may be determined that the specific location (S of defectk,i, Ek,j)。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810224121.2A CN108444921B (en) | 2018-03-19 | 2018-03-19 | Additive manufacturing component online detection method based on signal correlation analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810224121.2A CN108444921B (en) | 2018-03-19 | 2018-03-19 | Additive manufacturing component online detection method based on signal correlation analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108444921A true CN108444921A (en) | 2018-08-24 |
| CN108444921B CN108444921B (en) | 2021-02-26 |
Family
ID=63195143
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810224121.2A Active CN108444921B (en) | 2018-03-19 | 2018-03-19 | Additive manufacturing component online detection method based on signal correlation analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108444921B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269986A (en) * | 2018-09-28 | 2019-01-25 | 东南大学 | Phased-array laser ultrasonic testing system |
| CN110465661A (en) * | 2019-07-30 | 2019-11-19 | 武汉大学深圳研究院 | A kind of SLM metal increasing material manufacturing defect real-time detection method and detection device |
| CN110954542A (en) * | 2019-12-11 | 2020-04-03 | 深圳先进技术研究院 | Defect detection device, defect detection system and defect detection method for additive manufacturing |
| CN112415011A (en) * | 2020-10-23 | 2021-02-26 | 武汉理工大学 | Robot laser ultrasonic detection device and method for defects of electric arc additive part |
| CN117269311A (en) * | 2023-09-19 | 2023-12-22 | 湖南安卓特种设备科技有限公司 | Pressure vessel defect detection device and method based on surface wave signal correlation analysis |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090290783A1 (en) * | 2008-05-23 | 2009-11-26 | Kaoru Sakai | Defect Inspection Method and Apparatus Therefor |
| US20100106431A1 (en) * | 2008-10-29 | 2010-04-29 | Hitachi, Ltd. | Apparatus and method for ultrasonic testing |
| US20110311126A1 (en) * | 2009-01-27 | 2011-12-22 | Kaoru Sakai | Defect inspecting apparatus and defect inspecting method |
| CN103018341A (en) * | 2012-11-29 | 2013-04-03 | 北京理工大学 | High-rigidity three-coordinate scanning frame for scanning sound field of ultrasonic phased array transducer |
| CN103283002A (en) * | 2010-10-26 | 2013-09-04 | 株式会社尼康 | Inspection apparatus, inspection method, exposure method, and method for manufacturing semiconductor device |
| US20130329039A1 (en) * | 2010-09-15 | 2013-12-12 | Kaoru Sakai | Defect inspection method and device thereof |
| US20140055774A1 (en) * | 2012-08-23 | 2014-02-27 | Nuflare Technology, Inc. | Defect detection method |
| CN104483330A (en) * | 2014-11-11 | 2015-04-01 | 浙江大学 | Concrete surface crack real-time monitoring system and cracking risk dynamic assessment method |
| CN104597125A (en) * | 2014-12-26 | 2015-05-06 | 奥瑞视（北京）科技有限公司 | Ultrasonic detection control method and ultrasonic detection control device for 3D printed piece |
| CN104766335A (en) * | 2015-04-21 | 2015-07-08 | 中国矿业大学 | Geotechnical material deformation digital image correlation analysis and optimization method |
| CN105689719A (en) * | 2016-02-17 | 2016-06-22 | 西南交通大学 | Method for calculating alloy droplet deposition cooling rate |
| CN106018288A (en) * | 2016-06-17 | 2016-10-12 | 中国航空工业集团公司北京航空材料研究院 | Laser ultrasonic online nondestructive material-increase manufacturing part detection method |
| CN106003726A (en) * | 2016-06-27 | 2016-10-12 | 中海清华（河南）智能科技发展有限公司 | Intelligent laser 3D printing device and method |
| US20170059529A1 (en) * | 2015-08-24 | 2017-03-02 | Siemens Energy, Inc. | Adaptive additive manufacturing process using in-situ laser ultrasonic testing |
| CN107402044A (en) * | 2017-07-28 | 2017-11-28 | 华中科技大学 | A kind of online nondestructive detection system of metal increasing material manufacturing component quality and method |
-
2018
- 2018-03-19 CN CN201810224121.2A patent/CN108444921B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090290783A1 (en) * | 2008-05-23 | 2009-11-26 | Kaoru Sakai | Defect Inspection Method and Apparatus Therefor |
| US20100106431A1 (en) * | 2008-10-29 | 2010-04-29 | Hitachi, Ltd. | Apparatus and method for ultrasonic testing |
| US20110311126A1 (en) * | 2009-01-27 | 2011-12-22 | Kaoru Sakai | Defect inspecting apparatus and defect inspecting method |
| US20130329039A1 (en) * | 2010-09-15 | 2013-12-12 | Kaoru Sakai | Defect inspection method and device thereof |
| CN103283002A (en) * | 2010-10-26 | 2013-09-04 | 株式会社尼康 | Inspection apparatus, inspection method, exposure method, and method for manufacturing semiconductor device |
| US20140055774A1 (en) * | 2012-08-23 | 2014-02-27 | Nuflare Technology, Inc. | Defect detection method |
| CN103018341A (en) * | 2012-11-29 | 2013-04-03 | 北京理工大学 | High-rigidity three-coordinate scanning frame for scanning sound field of ultrasonic phased array transducer |
| CN104483330A (en) * | 2014-11-11 | 2015-04-01 | 浙江大学 | Concrete surface crack real-time monitoring system and cracking risk dynamic assessment method |
| CN104597125A (en) * | 2014-12-26 | 2015-05-06 | 奥瑞视（北京）科技有限公司 | Ultrasonic detection control method and ultrasonic detection control device for 3D printed piece |
| CN104766335A (en) * | 2015-04-21 | 2015-07-08 | 中国矿业大学 | Geotechnical material deformation digital image correlation analysis and optimization method |
| US20170059529A1 (en) * | 2015-08-24 | 2017-03-02 | Siemens Energy, Inc. | Adaptive additive manufacturing process using in-situ laser ultrasonic testing |
| CN105689719A (en) * | 2016-02-17 | 2016-06-22 | 西南交通大学 | Method for calculating alloy droplet deposition cooling rate |
| CN106018288A (en) * | 2016-06-17 | 2016-10-12 | 中国航空工业集团公司北京航空材料研究院 | Laser ultrasonic online nondestructive material-increase manufacturing part detection method |
| CN106003726A (en) * | 2016-06-27 | 2016-10-12 | 中海清华（河南）智能科技发展有限公司 | Intelligent laser 3D printing device and method |
| CN107402044A (en) * | 2017-07-28 | 2017-11-28 | 华中科技大学 | A kind of online nondestructive detection system of metal increasing material manufacturing component quality and method |
Non-Patent Citations (4)
| Title |
|---|
| D. LÉVESQUE ET AL.: "Inspection of additive manufactured parts using laser ultrasonics", 《AIP CONFERENCE PROCEEDINGS》 * |
| RAINA CEPEL ET AL.: "Spatial Correlation Coefficient Images for Ultrasonic Detection", 《IEEE TRANSACTIONS ON ULTRASONICS，PERROELECTRICS,AND FREQUENCY CONTROL》 * |
| 任明照等: "基于多幅连续相关法的超声检测信号的缺陷识别技术", 《无损检测》 * |
| 杨平华等: "金属增材制造技术发展动向及无损检测研究进展", 《材料工程》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109269986A (en) * | 2018-09-28 | 2019-01-25 | 东南大学 | Phased-array laser ultrasonic testing system |
| CN110465661A (en) * | 2019-07-30 | 2019-11-19 | 武汉大学深圳研究院 | A kind of SLM metal increasing material manufacturing defect real-time detection method and detection device |
| CN110954542A (en) * | 2019-12-11 | 2020-04-03 | 深圳先进技术研究院 | Defect detection device, defect detection system and defect detection method for additive manufacturing |
| CN112415011A (en) * | 2020-10-23 | 2021-02-26 | 武汉理工大学 | Robot laser ultrasonic detection device and method for defects of electric arc additive part |
| CN117269311A (en) * | 2023-09-19 | 2023-12-22 | 湖南安卓特种设备科技有限公司 | Pressure vessel defect detection device and method based on surface wave signal correlation analysis |
| CN117269311B (en) * | 2023-09-19 | 2024-03-26 | 湖南安卓特种设备科技有限公司 | Pressure vessel defect detection device and method based on surface wave signal correlation analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108444921B (en) | 2021-02-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108426839A (en) | A kind of increasing material manufacturing component detection method based on manipulator scanning laser ultrasound signal correlation analysis | |
| CN108444921A (en) | A kind of increasing material manufacturing component online test method based on signal correlation analysis | |
| CN108801914B (en) | Method and system for detecting forming defects of multi-groove profile plate | |
| CN107598163B (en) | A kind of quality lossless audio coding equipment and method suitable for powdering formula increasing material manufacturing | |
| CN104567679B (en) | A kind of system of turbo blade vision-based detection | |
| US7508971B2 (en) | Inspection system using coordinate measurement machine and associated method | |
| US8240210B2 (en) | Method and system for multimodal inspection with a coordinate measuring device | |
| CN109211110A (en) | A kind of flat-type workpiece size detection system and method based on machine vision | |
| Kapłonek et al. | Laser methods based on an analysis of scattered light for automated, in-process inspection of machined surfaces: A review | |
| CN113566735B (en) | Laser in-situ measurement method for rocket engine nozzle cooling channel line | |
| CN109738337B (en) | Testing device and method for testing 3D contact angle value of solid material by top view method | |
| Ma et al. | Research on an ultrasonic NDT system for complex surface parts | |
| CN103170877A (en) | Method of accurate location of diamond turning tool in micro-turning process | |
| CN115752300A (en) | Method and system for detecting flatness of planar workpiece through online laser vision | |
| CN212419634U (en) | Metal vibration material disk's on-line measuring system and metal vibration material disk manufacturing device | |
| CN110428408B (en) | Flaw detection method based on ELM-in-ELM | |
| Li et al. | Research on straightness detection of steel strip edge based on machine vision | |
| CN108372122B (en) | Automatic detection and sorting method and device for sheet grinding wheel | |
| Brunke | Fully-automated 3D metrology and defect analysis with high-resolution 300 kV microfocus computed tomography | |
| Spierings et al. | Direct part density inspection in laser powder bed fusion using eddy current testing | |
| Liu et al. | Sealing Test of Gas Valve Cover of Gas Meter Based on Line Laser Triangulation Method | |
| Wang et al. | Machine vision based roundness and cylindricity detection of bearing rollers | |
| CN109212039A (en) | The non-destructive measuring method of reinforcement content in particles reiforced metal-base composition | |
| Sa et al. | Design and realization of counterbore inspection system based on machine vision | |
| Song et al. | Machine vision inspection of roughness defects in opaque board surface |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |