CN109255785A - A kind of bearing open defect detection system - Google Patents
A kind of bearing open defect detection system Download PDFInfo
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- CN109255785A CN109255785A CN201811126357.9A CN201811126357A CN109255785A CN 109255785 A CN109255785 A CN 109255785A CN 201811126357 A CN201811126357 A CN 201811126357A CN 109255785 A CN109255785 A CN 109255785A
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- 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
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8806—Specially adapted optical and illumination features
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- 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
- G01N21/84—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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
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Abstract
The present invention provides a kind of bearing open defect detection system, which includes: the infrared polarization image and infrared intensity image that image capture module obtains bearing image to be detected;Image denoising module carries out denoising to infrared polarization image and infrared intensity image respectively;Image co-registration module to after denoising infrared polarization image and infrared intensity image merge, obtain the blending image of bearing to be detected;Bearing external appearance characteristic extraction module extracts the external appearance characteristic information of bearing to be detected from blending image, obtains the external appearance characteristic vector of bearing to be detected;The standard external appearance characteristic vector for the corresponding bearing that bearing open defect identification module is prestored according to the external appearance characteristic vector sum of bearing to be detected judges bearing to be detected with the presence or absence of open defect.The present invention realizes the intelligence of bearing open defect detection, improves the removal rate of defect recognition rate, unqualified bearing products, also improves the overall quality of factory product.
Description
Technical field
The present invention relates to Bearing testing technical fields, and in particular to a kind of bearing open defect detection system.
Background technique
The defects of a small amount of bearing outside surface has corrosion, scratches is had during Production of bearing and becomes waste product, substandard products,
These waste products, substandard products must be identified before factory, eliminate and.Traditional bearing surface defects detection is mainly carried out using artificial
Detection, it is easy to appear erroneous detection and missing inspection, not only low efficiency, shortage accuracy and standardization for artificial detection, and cannot will examine
Measured data classification is sent into computer in real time and carries out quality management.
Summary of the invention
In view of the above-mentioned problems, the present invention provides a kind of bearing open defect detection system.
The purpose of the present invention is realized using following technical scheme:
A kind of bearing open defect detection system, the detection system include image capture module, image denoising module, image
Fusion Module, bearing external appearance characteristic extraction module and bearing open defect identification module;Image capture module, it is to be checked for obtaining
Survey the infrared polarization image and infrared intensity image of bearing image;Image denoising module, for respectively to infrared polarization image and
Infrared intensity image carries out denoising, infrared polarization image and infrared intensity image after being denoised;Image co-registration module,
For to after denoising infrared polarization image and infrared intensity image merge, obtain the blending image of bearing to be detected;Axis
External appearance characteristic extraction module is held, for extracting the external appearance characteristic information of bearing to be detected from blending image, obtains axis to be detected
The external appearance characteristic vector held;Bearing open defect identification module, for being prestored according to the external appearance characteristic vector sum of bearing to be detected
Corresponding bearing standard external appearance characteristic vector, judge bearing to be detected with the presence or absence of open defect.
The invention has the benefit that the present invention realizes the intelligence of bearing open defect detection, defect knowledge is improved
Not rate, unqualified bearing products removal rate, also improve factory product overall quality;Simultaneously to the intelligence of bearing open defect
Energyization detection, also significantly reduces cost of labor, improves yield and efficiency.
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 bearing open defect detection system of the present invention;
Fig. 2 is the frame construction drawing of image co-registration module;
Fig. 3 is the frame construction drawing of high-frequency sub-band coefficient integrated unit.
Appended drawing reference: image capture module 1;Image denoising module 2;Image co-registration module 3;Bearing external appearance characteristic extracts mould
Block 4;Bearing open defect identification module 5;Alarm module 6;NSCT converter unit 7;Low frequency sub-band coefficient integrated unit 8;High frequency
Sub-band coefficients integrated unit 9;NSCT inverse transformation unit 10;Liveness computation subunit 11;Collocation degree computation subunit 12;Decision
Merge subelement 13.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of bearing open defect detection system, the detection system includes image capture module 1, image denoising
Module 2,5. image capture module of image co-registration module 3, bearing external appearance characteristic extraction module 4 and bearing open defect identification module
1, for obtaining the infrared polarization image and infrared intensity image of bearing image to be detected;Image denoising module 2, for right respectively
Infrared polarization image and infrared intensity image carry out denoising, infrared polarization image and infrared plot of light intensity after being denoised
Picture;Image co-registration module 3, for after denoising infrared polarization image and infrared intensity image merge, obtain to be detected
The blending image of bearing;Bearing external appearance characteristic extraction module 4, for extracting the external appearance characteristic of bearing to be detected from blending image
Information obtains the external appearance characteristic vector of bearing to be detected;Bearing open defect identification module 5, for according to bearing to be detected
The standard external appearance characteristic vector for the corresponding bearing that external appearance characteristic vector sum prestores judges that bearing to be detected is lacked with the presence or absence of appearance
It falls into.
The utility model has the advantages that realizing the intelligence of bearing open defect detection, defect recognition rate is improved, unqualified bearing produces
The removal rate of product also improves the overall quality of factory product;Simultaneously to the intellectualized detection of bearing open defect, also subtract significantly
Small cost of labor, improves yield and efficiency.
Preferably, which further includes warning module 6, warning module 6 and 5 phase of bearing open defect identification module
Even, for passing through mould of alarming when the judging result of bearing open defect identification module 5 is that bearing to be detected has open defect
Block 6 is sounded an alarm to staff, and staff is reminded to reject the bearing for having open defect.
Preferably, image capture module 1 includes infrared polarization camera and thermal infrared imager, and infrared polarization camera is for obtaining
The infrared polarization image of bearing to be detected, thermal infrared imager are used to obtain the infrared intensity image of bearing to be detected.
Preferably, described that denoising is carried out to infrared polarization image and infrared intensity image, it is infrared after being denoised
Polarization image and infrared intensity image, specifically:
(1) the attenuation degree value of each pixel gray value in the infrared polarization image is calculated using attenuation function,
In, the attenuation function are as follows:
In formula, h (x, y) is attenuation function, and indicates coordinate is the attenuation degree value of the pixel p gray value of (x, y), and θ is
The lower limit value of attenuation function, α, ε are the shape control constant of attenuation curve,For centered on pixel p (x, y), size M
The mean value of all pixels point gray value, g (x, y) are the gray values of pixel p (x, y) in × M rectangular window;
(2) according to the gray value attenuation degree value of obtained each pixel, each pixel is calculated using following formula and is denoised
Gray value afterwards, the set that all denoising pixel gray values are constituted are the infrared polarization image after denoising;Wherein, pixel
Gray value after p (x, y) denoising are as follows:
In formula,For the gray value at the pixel p (x, y) after denoising, gp(x, y) is the infrared polarization figure
Gray value as at pixel p (x, y);hp(x, y) is the attenuation degree value of pixel p gray value;
(3) the infrared intensity image is denoised using step 1 and step 2, the infrared light after denoising can be obtained
Strong image.
The utility model has the advantages that successively calculating each pixel gray value in infrared polarization image and intensity image using attenuation function
Attenuation degree value, before which not only allows for denoising in image pixel gray value, while having also contemplated its square
Other pixels filter out random noise to that need to denoise this influence factor of pixel so as to adaptive in shape window,
To which it is high to obtain clarity while retaining the marginal information in infrared polarization image and infrared intensity image, texture information
Denoising after infrared polarization image and infrared intensity image.
Preferably, as shown in Fig. 2, image co-registration module 3 includes NSCT converter unit 7, low frequency sub-band coefficient integrated unit
8, high-frequency sub-band coefficient integrated unit 9 and NSCT inverse transformation unit 10.
NSCT converter unit 7 is used to the infrared polarization image after denoising and infrared intensity image carrying out NSCT change respectively
It changes, the sub-band coefficients of infrared polarization image and infrared intensity image after respectively obtaining denoising, which includes low frequency
Band coefficient and high-frequency sub-band coefficient;
Low frequency sub-band coefficient integrated unit 8 is used for the low frequency according to infrared polarization image and infrared intensity image after denoising
Sub-band coefficients calculate the low frequency sub-band coefficient of blending image using average weighted algorithm;
High-frequency sub-band coefficient integrated unit 9 is used for the high frequency according to infrared polarization image and infrared intensity image after denoising
Sub-band coefficients calculate the high-frequency sub-band coefficient of blending image based on Algorithm of Multi-scale Fusion;
NSCT inverse transformation unit 10 is used for according to low frequency sub-band coefficient integrated unit 8 and high-frequency sub-band coefficient integrated unit 9
The low frequency sub-band coefficient and high-frequency sub-band coefficient of resulting blending image carry out NSCT inverse transformation, obtain blending image.
Preferably, according to the low frequency sub-band coefficient of infrared polarization image and infrared intensity image after denoising, using average
Weighting algorithm calculates the low frequency sub-band coefficient of blending image, specifically being calculated using average weighted algorithm every in blending image
The low frequency sub-band coefficient of a pixel, wherein the low frequency sub-band coefficient of pixel (m, n) in blending imageIt is as follows:
In formula,It is the low frequency sub-band coefficient of the infrared polarization image after denoising,It is after denoising
The low frequency sub-band coefficient of infrared intensity image.
Preferably, as shown in figure 3, high-frequency sub-band coefficient integrated unit 9 includes liveness computation subunit 11, collocation degree meter
Operator unit 12 and Decision fusion subelement 13.
Liveness computation subunit 11, for high frequency according to infrared polarization image and infrared intensity image after denoising
Band coefficient, the high-frequency sub-band coefficient of each pixel of infrared polarization image and infrared intensity image after calculating denoising enliven
Angle value, wherein for the infrared polarization image and each pixel of infrared intensity image after denoising, calculate each picture according to the following formula
Each high-frequency sub-band coefficient of vegetarian refreshments enlivens angle value:
In formula,High-frequency sub-band coefficient for pixel (a, b) in the infrared polarization image after denoising enlivens
Angle value,High-frequency sub-band coefficient for pixel (a, b) in the infrared intensity image after denoising enlivens angle value, N × Q
For the Size of Neighborhood of preset pixel (a, b), P is the neighborhood of pixel (a, b), and (a ', b ') is the neighborhood of pixel (a, b)
Interior any pixel point, wpol(a ', b ') be denoising after infrared polarization image in weight of the pixel (a ', b ') in neighborhood,
wint(a ', b ') is weight of the pixel (a ', b ') in neighborhood in infrared intensity image after denoising, wherein wpol(a′,b′)
=wint(a ', b '), and meet ∑(a′,b′)∈Pwpol(a ', b ')=1,For picture in the infrared polarization image after denoising
High-frequency sub-band coefficient of the vegetarian refreshments (a ', b ') on j scale, the direction k,For picture in the infrared intensity image after denoising
High-frequency sub-band coefficient of the vegetarian refreshments (a ', B ') on j scale, the direction k.
The utility model has the advantages that enlivening angle value by calculating high-frequency sub-band coefficient, this, which enlivens angle value, can measure corresponding high frequency
Significance degree with coefficient, while solving when enlivening angle value of each high-frequency sub-band coefficient, it is contemplated that position (a, b) in image
Neighborhood window in influence of the high-frequency sub-band coefficient to high-frequency sub-band coefficient liveness at position (a, b) at other positions, make
Obtaining each high-frequency sub-band coefficient adaptive can be adjusted, and can more accurately describe the aobvious of each high-frequency sub-band coefficient
Work degree is conducive to the subsequent high-frequency sub-band coefficient for solving blending image.
Matching degree computation subunit 12, for high frequency according to infrared polarization image and infrared intensity image after denoising
Band coefficient calculates matching of the high-frequency sub-band coefficient in each pixel of infrared polarization image and infrared intensity image after denoising
Angle value, whereinWithThe calculating formula of matching angle value at pixel (a, b) are as follows:
In formula, mj,k(a, b) is indicated at pixel (a, b)WithMatching angle value.
The utility model has the advantages that the matching degree computation subunit 12 considers in two images high-frequency sub-band coefficient at same position
Matching degree, the way more remain marginal information and texture information in two images, while being conducive in subsequent
The useful letter in infrared polarization image and infrared intensity image while being merged, after capable of effectively integrating denoising
Breath, improves subsequent syncretizing effect.
Decision fusion subelement 13, based on being obtained to liveness computation subunit 11 and matching degree computation subunit 12
It calculates result and carries out comprehensive analysis and judgement, and to the high-frequency sub-band coefficient of infrared polarization image and infrared intensity image after denoising
It is merged, obtains the high-frequency sub-band coefficient of blending image, wherein pixel (a, b) is in j scale, the direction k in blending image
On high-frequency sub-band coefficient can be obtained using the fusion formula of lower section:
In formula,For the high-frequency sub-band system on j scale, the direction k in blending image at pixel (a, b)
Number,For the high-frequency sub-band coefficient on j scale, the direction k at the infrared polarization picture position (a, b) after denoising
Weight coefficient, ρ are the matching degree threshold value of setting.
The utility model has the advantages that by the matching degree threshold value of setting, to the infrared polarization image after the denoising of pending fusion treatment
Judged with the matching degree of infrared intensity image, when matching degree is greater than the threshold value of setting, further using active
Angle value further judges, the way can significant information in reserved high-frequency sub-band coefficients, while after further suppressing denoising
Infrared polarization image and infrared intensity image in residual noise bring interference.Improve to infrared polarization image after denoising and
The syncretizing effect of infrared intensity image improves the subsequent discrimination identified to bearing open defect, unqualified bearing products
Removal rate, also improve factory product overall quality.
Preferably, the standard external appearance characteristic of the corresponding bearing prestored according to the external appearance characteristic vector sum of bearing to be detected to
Amount judges that bearing to be detected whether there is open defect, specifically, ifThen bearing to be detected has appearance
Defect, conversely, then bearing to be detected is without open defect, whereinFor the external appearance characteristic vector of bearing to be detected,To prestore
Corresponding bearing standard external appearance characteristic vector,For the similarity factor of setting.
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 bearing open defect detection system, which is characterized in that including image capture module, image denoising module, image
Fusion Module, bearing external appearance characteristic extraction module and bearing open defect identification module;
Described image acquisition module, for obtaining the infrared polarization image and infrared intensity image of bearing image to be detected;
Described image denoises module, for carrying out denoising to the infrared polarization image and infrared intensity image respectively, obtains
Infrared polarization image and infrared intensity image after to denoising;
Described image Fusion Module, for after the denoising infrared polarization image and infrared intensity image merge, obtain
To the blending image of bearing to be detected;
The bearing external appearance characteristic extraction module, for extracting the external appearance characteristic of the bearing to be detected from the blending image
Information obtains the external appearance characteristic vector of the bearing to be detected;
The bearing open defect identification module, it is corresponding for being prestored according to the external appearance characteristic vector sum of the bearing to be detected
The standard external appearance characteristic vector of bearing judges bearing to be detected with the presence or absence of open defect.
2. bearing open defect detection system according to claim 1, which is characterized in that it further include warning module, it is described
Warning module is connected with the bearing open defect identification module, for working as the judgement knot of the bearing open defect identification module
When fruit is that the bearing to be detected has open defect, is sounded an alarm by the alarm module to staff, remind work
Personnel reject the bearing for having open defect.
3. bearing open defect detection system according to claim 1, which is characterized in that described image acquisition module includes
Infrared polarization camera and thermal infrared imager, the infrared polarization camera are used to obtain the infrared polarization image of bearing to be detected, institute
Thermal infrared imager is stated for obtaining the infrared intensity image of bearing to be detected.
4. bearing open defect detection system according to claim 1, which is characterized in that it is described to infrared polarization image and
Infrared intensity image progress denoising, infrared polarization image and infrared intensity image after being denoised, specifically:
(1) the attenuation degree value of each pixel gray value in the infrared polarization image is calculated using attenuation function, wherein institute
State attenuation function are as follows:
In formula, h (x, y) is attenuation function, and indicates coordinate is the attenuation degree value of the pixel p gray value of (x, y), and θ is decaying
The lower limit value of function, α, ε are the shape control constant of attenuation curve,For centered on pixel p (x, y), size is M × M square
The mean value of all pixels point gray value, g (x, y) are the gray values of pixel p (x, y) in shape window;
(2) according to the gray value attenuation degree value of obtained each pixel, after calculating each pixel denoising using following formula
Gray value, the set that all denoising pixel gray values are constituted are the infrared polarization image after denoising;Wherein, pixel p (x,
Y) gray value after denoising are as follows:
In formula,For the gray value at the pixel p (x, y) after denoising, gp(x, y) is picture in the infrared polarization image
Gray value at vegetarian refreshments p (x, y);hp(x, y) is the attenuation degree value of pixel p gray value;
(3) the infrared intensity image is denoised using step 1 and step 2, the infrared plot of light intensity after denoising can be obtained
Picture.
5. bearing open defect detection system according to claim 1, which is characterized in that described according to the axis to be detected
The standard external appearance characteristic vector for the corresponding bearing that the external appearance characteristic vector sum held prestores judges bearing to be detected with the presence or absence of appearance
Defect, specifically, ifThen bearing to be detected has open defect, conversely, then bearing to be detected is lacked without appearance
It falls into, whereinFor the external appearance characteristic vector of bearing to be detected,Standard external appearance characteristic vector for the corresponding bearing prestored,
For the similarity factor of setting.
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110132983A (en) * | 2019-05-28 | 2019-08-16 | 朱清 | A kind of online hierarchical detection device and method of injecting products |
CN110174408A (en) * | 2019-06-12 | 2019-08-27 | 复旦大学 | A kind of increasing material manufacturing process senses off-axis monitoring system more |
CN110441312A (en) * | 2019-07-30 | 2019-11-12 | 上海深视信息科技有限公司 | A kind of surface defects of products detection system based on multispectral imaging |
CN114612384A (en) * | 2022-01-30 | 2022-06-10 | 扬州长青树体育用品有限公司 | Method and system for detecting defects of appearance material of sport protector |
CN115493843A (en) * | 2022-11-18 | 2022-12-20 | 聊城市义和轴承配件有限公司 | Quality monitoring method and equipment based on bearing retainer |
-
2018
- 2018-09-26 CN CN201811126357.9A patent/CN109255785A/en not_active Withdrawn
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
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CN110132983A (en) * | 2019-05-28 | 2019-08-16 | 朱清 | A kind of online hierarchical detection device and method of injecting products |
CN110174408A (en) * | 2019-06-12 | 2019-08-27 | 复旦大学 | A kind of increasing material manufacturing process senses off-axis monitoring system more |
CN110441312A (en) * | 2019-07-30 | 2019-11-12 | 上海深视信息科技有限公司 | A kind of surface defects of products detection system based on multispectral imaging |
CN114612384A (en) * | 2022-01-30 | 2022-06-10 | 扬州长青树体育用品有限公司 | Method and system for detecting defects of appearance material of sport protector |
CN115493843A (en) * | 2022-11-18 | 2022-12-20 | 聊城市义和轴承配件有限公司 | Quality monitoring method and equipment based on bearing retainer |
CN115493843B (en) * | 2022-11-18 | 2023-03-10 | 聊城市义和轴承配件有限公司 | Quality monitoring method and equipment based on bearing retainer |
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