CN108872252A - A kind of girder steel flaw detection system - Google Patents
A kind of girder steel flaw detection system Download PDFInfo
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- CN108872252A CN108872252A CN201810882961.8A CN201810882961A CN108872252A CN 108872252 A CN108872252 A CN 108872252A CN 201810882961 A CN201810882961 A CN 201810882961A CN 108872252 A CN108872252 A CN 108872252A
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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Abstract
The present invention provides a kind of girder steel flaw detection system, which includes：Girder steel image capture module, for acquiring the original image of girder steel to be detected；Girder steel image processing module, for being denoised to the original image of acquisition, edge detection and enhancing processing, obtain the target image of girder steel to be detected；Girder steel extracting thermal crack module, for extracting the characteristic of girder steel to be detected from target image；Girder steel crack identification module judges girder steel to be detected with the presence or absence of crackle for matching the characteristic of the girder steel for the flawless being pre-stored in the characteristic of girder steel to be detected and database.The present invention can quickly and accurately extract the characteristic of girder steel to be detected, and identify girder steel to be detected with the presence or absence of crackle, in favor of rapidly and accurately being excluded to failure, improve the economic benefit of factory and the personal safety of safeguard work personnel.
Description
Technical field
The present invention relates to fault diagnosis technologies and information process analysis technical field, and in particular to a kind of girder steel crack detection
System.
Background technique
The girder steel that industry and enterprise use is once cracked on surface, will produce to it and cause great economic loss
With cause serious human safety issues, the guide rail at top especially in production line, in by the operation of hanger idler wheel upwards or
Downward extruding component, stress accumulation will lead to destruction fracture and occur again and again.And shop personnel are only capable of at present by visual
Change and check crackle, detection heavy workload, low efficiency, time-consuming.Therefore, there is an urgent need to a kind of effective automatic checkout systems can
Steel beam surface is accurately detected.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of girder steel flaw detection system
The purpose of the present invention is realized using following technical scheme：
A kind of girder steel flaw detection system, the girder steel flaw detection system include girder steel image capture module, girder steel image
Processing module, girder steel crack extraction module and girder steel crack identification module.Girder steel image capture module, for acquiring
The original image of girder steel to be detected；Girder steel image processing module, for being denoised to the original image of acquisition, edge detection and
Enhancing processing, obtains the target image of girder steel to be detected；Girder steel extracting thermal crack module, it is to be detected for being extracted from target image
The characteristic of girder steel；Girder steel crack identification module, for will be prestored in the characteristic of girder steel to be detected and database
The characteristic of the girder steel of the flawless of storage is matched, and judges girder steel to be detected with the presence or absence of crackle.
Beneficial effects of the present invention are：The present invention can quickly and accurately extract the characteristic of girder steel to be detected, and know
Not Chu girder steel to be detected with the presence or absence of crackle in favor of rapidly and accurately being excluded to failure improve the economic benefit of factory
And the personal safety of safeguard work personnel.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the structure chart of girder steel flaw detection system；
Fig. 2 is the frame construction drawing of girder steel image processing module.
Appended drawing reference：Girder steel image capture module 1；Girder steel image processing module 2；Girder steel crack extraction module 3；Steel
Beam crack identification module 4；Warning module 5；Denoise unit 6；Edge detection unit 7；Enhancement unit 8.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of girder steel flaw detection system, the girder steel flaw detection system include girder steel image capture module 1,
Girder steel image processing module 2, girder steel crack extraction module 3 and girder steel crack identification module 4.Girder steel Image Acquisition mould
Block 1, for acquiring the original image of girder steel to be detected；Girder steel image processing module 2, for being gone to the original image of acquisition
It makes an uproar, edge detection and enhancing processing, obtains the target image of girder steel to be detected；Girder steel extracting thermal crack module 3 is used for from target figure
The characteristic of girder steel to be detected is extracted as in；Girder steel crack identification module 4, for by the characteristic of girder steel to be detected
It is matched with the characteristic of the girder steel for the flawless being pre-stored in database, judges girder steel to be detected with the presence or absence of crackle.
Beneficial effect：The present invention can quickly and accurately extract the characteristic of girder steel to be detected, and identify to be detected
Girder steel whether there is crackle, in favor of rapidly and accurately being excluded to failure, improve the economic benefit and safeguard work of factory
The personal safety of personnel.
Preferably, which further includes warning module 5, and warning module 5 and girder steel crack identify
Module 4 is connected, for show girder steel to be detected there are when crackle, by warning module 5 to service personnel's sending when matching result
Warning information.
Preferably, girder steel image capture module 1 is industrial camera.
Preferably, referring to fig. 2, girder steel image processing module 2 includes denoising unit 6, edge detection unit 7 and enhancement unit
8.Denoising unit 6 is used to remove the random noise in the original image；Edge detection unit 7 is used for the original graph after denoising
As carrying out edge detection, the benchmark image of girder steel to be detected is obtained；Enhancement unit 8 is used to carry out enhancing processing to benchmark image,
Obtain the target image of girder steel to be detected.
Preferably, the random noise in the removal original image, specifically：The original image is carried out at gray processing
Reason, and successively the original image after gray processing is denoised point by point, obtain the denoising of each pixel in the original image
Estimated value, and using denoising estimated value as new gray value, the set that all pixels point is constituted at this time is original after denoising
Image；Wherein, the denoising estimated value of pixel p (i, j) is calculated using following formula in the original image：
In formula,For the denoising estimated value of pixel p (i, j), be pixel p denoising after gray value, i, j points
Not Wei pixel p abscissa and ordinate, Z is regularization parameter, W be centered on pixel p (i, j), size be M × M
Search window, q is any pixel point in search window,Europe is weighted for the Gauss of pixel p and pixel q
Formula distance, α are the standard deviation of Gaussian function, and h is smoothing parameter, and G (q) is the gray value of pixel q, and G (p) is pixel p's
Gray value,For the average gray value of all pixels point in search window.
Beneficial effect：The denoising estimated value of each pixel in above-mentioned solution original image, the solution procedure are mainly benefit
It is denoised with the redundancy in original image, by searching for pixel similar with target pixel points in a search window
Point, and then replace with the gray value of these similar pixel points the gray value of current pixel point.The denoising method is simple, denoising is fast
Degree is fast, not only allow for the Gauss weighted euclidean distance information between pixel, it is also contemplated that residual pixel point in search window
It is improved with the relationship of target pixel points gray value to farthest remain the edge and minutia of original image
Effect is denoised, while being also beneficial to accurate detection of the subsequent acquisition to girder steel to be detected, improves detection accuracy.
Preferably, the original image after described pair of denoising carries out edge detection, obtains the benchmark image of girder steel to be detected, has
Body is：
(1) taking the central pixel point in the sliding window that size is 3 × 3 is edge measuring point to be checked, according to lateral inspection
It surveys direction and 3 × 3 sliding window is divided into three regions：L, M, R, wherein L is located on the left of sliding window, M is located at sliding window
Mouth is intermediate, R is located on the right side of sliding window, judges whether edge measuring point to be checked is marginal point using edge discrimination formula, wherein institute
Stating edge discrimination formula is：
In formula, H (x) is the characteristic value of edge measuring point x to be checked, GLIt (i) is the gray value of ith pixel point in the L of region, GM
It (i) is the gray value of ith pixel point in the M of region, GRIt (i) is the gray value of ith pixel point in the R of region, and i=1,2,3；
G (x) is the gray value of edge measuring point x to be checked；
As H (x) >=T, then edge measuring point x to be checked is marginal point, conversely, edge measuring point x to be checked is not marginal point,
In, T is the threshold value of setting；
(2) all pixels point in the original image after traversal denoising, and using the method that non-extreme value inhibits to obtained side
Edge point carries out edge positioning, and the set of the final marginal point of girder steel to be detected can be obtained；
(3) original image after denoising is split according to the set for the final marginal point for obtaining girder steel to be detected, i.e.,
The benchmark image of girder steel to be detected can be obtained.
Beneficial effect：By setting a sliding window, judge whether the central pixel point in sliding window is to be detected
The marginal point of girder steel, and all pixels point in the original image after denoising is successively traversed using sliding window, which can be certainly
It whether is adaptively that marginal point differentiates to each pixel, not only details is special in retaining girder steel image border point to be detected
While sign, it is also able to detect that clearly marginal information, while in order to further increase edge detection precision, utilizing non-extreme value
The method of inhibition repositions the marginal point detected, can further remove non-edge point, so that extract
It is edge clear, complete, accurate, it is more advantageous to the accurate segmentation to girder steel image to be detected, obtains the reference map of girder steel to be detected
Picture, convenient for subsequent extraction and identification to steel beam surface feature to be detected.
Preferably, described that enhancing processing is carried out to benchmark image, the target image of girder steel to be detected is obtained, is specifically utilized
Enhance formula and calculates all pixels point enhancing in the benchmark image treated gray value, the enhancing treated pixel
The set of composition is the target image of girder steel to be detected, wherein the enhancing formula is：
In formula, Ge(x, y) is the gray value of enhanced pixel r (x, y), and G (x, y) is pixel in the benchmark image
The gray value of point r (x, y), κ (x, y) are about control coefrficient of the pixel r (x, y) along gradient direction, μ in the benchmark image
For the constant greater than 0,For the second-order partial differential coefficient at pixel r (x, y) along gradient direction n,For pixel
Along the second-order partial differential coefficient of the tangential direction s orthogonal with gradient direction at point r (x, y)；
Wherein, pass through about pixel r (x, y) in the benchmark image along the control coefrficient κ (x, y) of gradient direction following
Mode obtain：
(1) local variance in the benchmark image at each pixel in 3 × 3 neighborhoods is calculated using following formula, wherein closing
It is in the formula of the local variance of pixel r (x, y)：
In formula, χ2(x, y) is the local variance of pixel r (x, y), and G (x+s, y+t) is the picture that coordinate is (x+s, y+t)
The gray value of vegetarian refreshments,For the gray value mean value of all pixels point in neighborhood；
(2) using normalization formula to obtained local variance χ2(x, y) is normalized, its local variance is returned
One changes into the region of 0-255, wherein normalization formula is：
In formula,For the local variance after the normalization of pixel r (x, y), Max χ2With Min χ2It is respectively described
The maximum value and minimum value of benchmark image local variance；
(3) according to obtained normalized value, pixel r (x, y) is calculated along the control coefrficient of gradient direction using following formula；
In formula, κ (x, y) is control coefrficient of the pixel r (x, y) along gradient direction,For the variance threshold values of setting.
Beneficial effect：Enhancing processing is carried out to the benchmark image using above-mentioned algorithm, the algorithm is in enhancing benchmark image
It while minutia, avoids edge and overshoot phenomenon occurs, while also restrained effectively residual in the benchmark image
Remaining noise enables enhanced benchmark image to highlight the surface details feature of girder steel to be detected, to be checked convenient for subsequent extracted
The surface characteristics parameter for surveying girder steel improves girder steel table to be detected in favor of accurately identifying to steel beam surface defect to be detected
The accuracy rate of planar defect detection.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (5)
1. a kind of girder steel flaw detection system, characterized in that the girder steel flaw detection system include girder steel image capture module,
Girder steel image processing module, girder steel crack extraction module and girder steel crack identification module；
The girder steel image capture module, for acquiring the original image of girder steel to be detected；
The girder steel image processing module, for being denoised to the original image of acquisition, edge detection and enhancing processing, obtain
The target image of girder steel to be detected；
The girder steel extracting thermal crack module, for extracting the characteristic of girder steel to be detected from the target image；
The girder steel crack identification module, for splitting the nothing being pre-stored in the characteristic of girder steel to be detected and database
The characteristic of the girder steel of line is matched, and judges girder steel to be detected with the presence or absence of crackle.
2. girder steel flaw detection system according to claim 1, characterized in that it further include warning module, the early warning mould
Block is connected with the girder steel crack identification module, for showing that girder steel to be detected there are when crackle, passes through when matching result
The warning module issues warning information to service personnel.
3. girder steel flaw detection system according to claim 1, characterized in that the girder steel image capture module is industry
Camera.
4. girder steel flaw detection system according to claim 3, characterized in that the girder steel image processing module includes going
It makes an uproar unit, edge detection unit and enhancement unit；
The denoising unit, for removing the random noise in the original image；
The edge detection unit obtains the benchmark of girder steel to be detected for carrying out edge detection to the original image after denoising
Image；
The enhancement unit obtains the target image of girder steel to be detected for carrying out enhancing processing to the benchmark image.
5. girder steel flaw detection system according to claim 4, characterized in that making an uproar in the removal original image at random
Sound, specifically：Gray processing processing is carried out to the original image, and successively the original image after gray processing is gone point by point
It makes an uproar, obtains the denoising estimated value of each pixel in the original image, and using denoising estimated value as new gray value, at this time
The set that all pixels point is constituted is the original image after denoising；Wherein, pixel p (i, j) is gone in the original image
Estimated value of making an uproar is calculated using following formula：
In formula,For the denoising estimated value of pixel p (i, j), i, j are respectively the abscissa and ordinate of pixel p, and Z is
Regularization parameter, W are centered on pixel p (i, j), the search window that size is M × M, and q is any pixel point in search window,For the Gauss weighted euclidean distance of pixel p and pixel q, α is the standard deviation of Gaussian function, and h is flat
Sliding parameter, G (q) are the gray value of pixel q, and G (p) is the gray value of pixel p,For in search window all pixels point it is flat
Equal gray value.
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Cited By (3)
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| CN111721361A (en) * | 2020-06-29 | 2020-09-29 | 杭州鲁尔物联科技有限公司 | Embankment monitoring system, method and equipment |
| CN116894832A (en) * | 2023-07-27 | 2023-10-17 | 山东明佳科技有限公司 | Method, system, equipment and storage medium for detecting bottleneck cracks of milk glass bottle |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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