CN106680293A - Machine vision based motor rotor gib defect detection system and method - Google Patents
Machine vision based motor rotor gib defect detection system and method Download PDFInfo
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- CN106680293A CN106680293A CN201710020905.9A CN201710020905A CN106680293A CN 106680293 A CN106680293 A CN 106680293A CN 201710020905 A CN201710020905 A CN 201710020905A CN 106680293 A CN106680293 A CN 106680293A
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- 238000001514 detection method Methods 0.000 title claims abstract description 50
- 230000007547 defect Effects 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 title claims abstract description 11
- 230000007246 mechanism Effects 0.000 claims abstract description 30
- 239000000284 extract Substances 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 3
- 238000003709 image segmentation Methods 0.000 claims description 3
- 230000002950 deficient Effects 0.000 claims description 2
- 238000007781 pre-processing Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 3
- 239000000047 product Substances 0.000 description 7
- 238000004519 manufacturing process Methods 0.000 description 3
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000006227 byproduct Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000008187 granular material Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
Classifications
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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
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
-
- 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
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined
- G01N2021/8924—Dents; Relief flaws
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- Engineering & Computer Science (AREA)
- Textile Engineering (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention relates to a machine vision based motor rotor gib defect detection system and method. The system comprises a feed mechanism, a grabbing and conveying mechanism, a gib defect detection mechanism and a product sorting mechanism, which are sequentially connected, wherein the gib defect detection mechanism comprises a mechanical rotation module, a light source module, an image collection module and a gib defect detection module. A motor rotor rotates through a rotating mechanical structure, a side gib image of the motor rotor is collected by using an industrial linear array camera and a linear array light source; image pretreatment is carried out by using a machine vision technology to obtain a side gib area; defect characteristics are extracted; and defect information is highlighted and effectively identified and located to achieve the target of extracting the defect characteristics of the gib. The machine vision based motor rotor gib defect detection system has the advantages of high precision, high detection speed and high applicability and practicability, and online detection can be achieved.
Description
Technical field
The present invention relates to the technical field of electromechanical equipment detection, more particularly to a kind of rotor based on machine vision
Hook and slot defect detecting system and detection method.
Background technology
Motor, indispensable important basic equipment in industry, traffic, national defence and daily life.Rotor is used as electricity
One of core devices of machine, its quality directly influences the quality of motor.The appearance quality detection of rotor, particularly rotor
Hook and slot defects detection is an important operation in motor production line.At present, rotor hook and slot defects detection is still using artificial inspection
Survey mode, but there is the tiny granule such as copper wire, copper scale, copper-surfaced in rotor hook and slot, and the presence of these factors all lacks to hook and slot
Sunken on-line checking increased detection difficulty.Additionally, manual detection needs substantial amounts of labour force, high cost, and manual detection to hold
Easily there is fatigue, there are problems that low efficiency, higher false drop rate and.
The content of the invention
Present invention aim to overcome that prior art is not enough, there is provided a kind of accuracy of detection is high, loss is low, detection speed
Hurry up, the suitability with it is practical, and the rotor hook and slot defect detecting system of manual detection mode can be replaced, the system
The non-contact vision on-line checking of rotor hook and slot is realized, and according to testing result automatic sorting faulty goods, can be significantly
Improve enterprises production efficiency.
For achieving the above object, technical scheme provided by the present invention is：Including feed mechanism, gripping conveyor structure, hook
Groove defects detection mechanism and product sorting mechanism, each mechanism is linked in sequence, wherein, described hook and slot defects detection mechanism is by machine
Tool rotating module, light source module, image capture module and hook and slot defects detection module composition；
The mechanical rotation module, drive motor rotor rotation；
The light source module, cooperative mechanical rotating module, projection rotor side hook and slot is to two dimensional surface；
Described image acquisition module, collection rotor side hook and slot image, and give hook and slot defects detection image transmitting
Module；
The hook and slot defects detection module, using hook and slot defects detection algorithm, detects and positions defective locations, finally exports
Classification results.
For achieving the above object, present invention also offers a kind of rotor hook and slot defects detection side based on machine vision
Method：It is comprised the following steps：
1) mechanical rotating mechanism is utilized, with reference to line-scan digital camera, by way of line is scanned, collection rotor side hook and slot
Image；
2) Preprocessing Technique is utilized, is adjusted through brightness of image, opening and closing operation filters noise jamming；
3) location hook groove location, extracts area-of-interest and rotor hook and slot profile；
4) using image similarity algorithm, the hook and slot profile for extracting is differentiated by calculating rectangle similarity；
5) being differentiated with reference to gray value using gaussian filtering carries out image segmentation process to hook and slot region, extracts defect area.
Compared with prior art, this programme develops rotor comprehensively using optical, mechanical and electronic integration and machine vision technique
Hook and slot defect on-line detecting system, the system adopts mechanical rotating mechanism, and by the frame for movement for rotating rotor is rotated,
Using industrial line-scan digital camera and array light source collection rotor side hook and slot image；Then machine vision is utilized, figure is carried out
As pretreatment, side hook and slot region is obtained, extract defect characteristic, prominent defect information and effectively identification positioning reach extraction hook
The purpose of groove defect characteristic.System can replace existing manual detection pattern, and certainty of measurement is high, and high degree of automation reduces life
Produce cost, detection is stable, solve that the product that manual detection brought is unstable, testing cost is high, inefficiency the problems such as.
Description of the drawings
Fig. 1 is system construction drawing in the embodiment of the present invention；
Fig. 2 is hook and slot defects detection algorithm flow chart in the embodiment of the present invention；
In figure：1- feed mechanisms, 2- gripping conveyor structures, 3- hook and slot defects detections mechanism, 4- product sortings mechanism, 5- machines
Tool rotating module, 6- light source modules, 7- image capture modules, 8- hook and slot defects detection modules.
Specific embodiment
With reference to specific embodiment, the invention will be further described：
Referring to a kind of rotor hook and slot defects detection based on machine vision shown in attached Fig. 1 and 2, described in the present embodiment
System and detection method, system includes feed mechanism 1, gripping conveyor structure 2, hook and slot defects detection mechanism 3 and product point
Mechanism 4 is picked, each mechanism is linked in sequence, wherein, hook and slot defects detection mechanism 3 is adopted by mechanical rotation module 5, light source module 6, image
Collection module 7, hook and slot defects detection module 8 are constituted；
During work, the auto-sequencing of feed mechanism 1 simultaneously conveys product to be checked to gripping conveyor structure 2, then by gripping conveyor
Product to be checked is captured one by one and is transported to hook and slot defects detection mechanism 3 by structure 2, and the motor for reaching hook and slot defects detection mechanism 3 turns
Son rotates in mechanical rotation module 5, and now light source module 6 and image capture module 7 coordinate, with reference to line-scan digital camera, by line
The mode of scanning, collection rotor side hook and slot image, the image that hook and slot defects detection module 8 pairs is collected carries out pretreatment
Technology, adjusts brightness of image, and opening and closing operation filters noise jamming, then extracts area-of-interest and rotor hook and slot wheel
Exterior feature, is differentiated by calculating rectangle similarity to the hook and slot profile for extracting, and is sentenced with reference to gray value using gaussian filtering afterwards
It is other to carry out image segmentation process to hook and slot region, extract defect area, output category result, finally according to testing result, then by
Product sorting mechanism is sorted.
The present embodiment comprehensively using optical, mechanical and electronic integration and machine vision technique, by the frame for movement for rotating motor is turned
Son is rotated, using industrial line-scan digital camera and array light source collection rotor side hook and slot image；Then machine vision is utilized,
Image semantic classification is carried out, side hook and slot region is obtained, defect characteristic is extracted, prominent defect information and effectively identification positioning reach
Extract the purpose of hook and slot defect characteristic.The present embodiment can replace existing manual detection pattern, and certainty of measurement is high, automaticity
Height, reduces production cost, and detection is stable, solves that the product that manual detection brought is unstable, testing cost is high, work efficiency
Low problem.
The examples of implementation of the above are only the preferred embodiments of the invention, not limit the enforcement model of the present invention with this
Enclose, therefore the change that all shapes according to the present invention, principle are made, all should cover within the scope of the present invention.
Claims (2)
1. a kind of rotor hook and slot defect detecting system based on machine vision, it is characterised in that：It include feed mechanism,
Gripping conveyor structure, hook and slot defects detection mechanism and product sorting mechanism, each mechanism is linked in sequence, wherein, described hook and slot
Defects detection mechanism is made up of mechanical rotation module, light source module, image capture module and hook and slot defects detection module；
The mechanical rotation module, drive motor rotor rotation；
The light source module, cooperative mechanical rotating module, projection rotor side hook and slot is to two dimensional surface；
Described image acquisition module, collection rotor side hook and slot image, and give hook and slot defects detection module image transmitting；
The hook and slot defects detection module, using hook and slot defects detection algorithm, detects and positions defective locations, last output category
As a result.
2. it is a kind of for described in claim 1 based on machine vision rotor hook and slot defect detecting system method, it is special
Levy and be：Comprise the following steps：
1) mechanical rotating mechanism is utilized, with reference to line-scan digital camera, by way of line is scanned, collection rotor side hook and slot figure
Picture；
2) Preprocessing Technique is utilized, is adjusted through brightness of image, opening and closing operation filters noise jamming；
3) location hook groove location, extracts area-of-interest and rotor hook and slot profile；
4) using image similarity algorithm, the hook and slot profile for extracting is differentiated by calculating rectangle similarity；
5) being differentiated with reference to gray value using gaussian filtering carries out image segmentation process to hook and slot region, extracts defect area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710020905.9A CN106680293A (en) | 2017-01-11 | 2017-01-11 | Machine vision based motor rotor gib defect detection system and method |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710020905.9A CN106680293A (en) | 2017-01-11 | 2017-01-11 | Machine vision based motor rotor gib defect detection system and method |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107436307A (en) * | 2017-07-07 | 2017-12-05 | 柳州杰诺瑞汽车电器系统制造有限公司 | Vision automatic checkout system and its detection method |
| CN108508027A (en) * | 2018-04-18 | 2018-09-07 | 江门市科业电器制造有限公司 | A kind of stator detection method and detection device |
| CN109085173A (en) * | 2018-06-25 | 2018-12-25 | 盐城工学院 | A kind of carrying out flaw detection anthropomorphic robot and its detection method |
| CN109738363A (en) * | 2019-02-22 | 2019-05-10 | 深圳精创视觉科技有限公司 | Product side defect detecting device |
| CN110011492A (en) * | 2019-04-09 | 2019-07-12 | 江门市维凯智能装备有限公司 | A kind of rotor automatically processing device |
| CN110044909A (en) * | 2019-05-05 | 2019-07-23 | 桂林电子科技大学 | A kind of rotor welding point defect detection device and method based on image procossing |
| CN111729870A (en) * | 2020-07-17 | 2020-10-02 | 成都卓识维景科技有限公司 | Automatic detection device and method for air duct defects of brake disc based on machine vision |
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| CN104280406A (en) * | 2014-09-16 | 2015-01-14 | 中国科学院广州能源研究所 | Machine vision system for detecting surface defects of copper part |
| CN104690000A (en) * | 2013-12-06 | 2015-06-10 | 刘扬 | Gear appearance defect detection and sorting system based on machine vision |
| CN105973912A (en) * | 2016-06-12 | 2016-09-28 | 合肥汉重智能装备有限公司 | Leather surface defect detecting system and method based on machine vision |
| CN206505028U (en) * | 2017-01-11 | 2017-09-19 | 广东工业大学 | A kind of rotor hook and slot defect detecting system based on machine vision |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104690000A (en) * | 2013-12-06 | 2015-06-10 | 刘扬 | Gear appearance defect detection and sorting system based on machine vision |
| CN104280406A (en) * | 2014-09-16 | 2015-01-14 | 中国科学院广州能源研究所 | Machine vision system for detecting surface defects of copper part |
| CN105973912A (en) * | 2016-06-12 | 2016-09-28 | 合肥汉重智能装备有限公司 | Leather surface defect detecting system and method based on machine vision |
| CN206505028U (en) * | 2017-01-11 | 2017-09-19 | 广东工业大学 | A kind of rotor hook and slot defect detecting system based on machine vision |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107436307A (en) * | 2017-07-07 | 2017-12-05 | 柳州杰诺瑞汽车电器系统制造有限公司 | Vision automatic checkout system and its detection method |
| CN108508027A (en) * | 2018-04-18 | 2018-09-07 | 江门市科业电器制造有限公司 | A kind of stator detection method and detection device |
| CN108508027B (en) * | 2018-04-18 | 2023-10-20 | 江门市科业电器制造有限公司 | Stator detection method and detection device |
| CN109085173A (en) * | 2018-06-25 | 2018-12-25 | 盐城工学院 | A kind of carrying out flaw detection anthropomorphic robot and its detection method |
| CN109085173B (en) * | 2018-06-25 | 2021-04-16 | 盐城工学院 | Humanoid robot for flaw detection and detection method thereof |
| CN109738363A (en) * | 2019-02-22 | 2019-05-10 | 深圳精创视觉科技有限公司 | Product side defect detecting device |
| CN110011492A (en) * | 2019-04-09 | 2019-07-12 | 江门市维凯智能装备有限公司 | A kind of rotor automatically processing device |
| CN110011492B (en) * | 2019-04-09 | 2024-05-14 | 江门市维凯智能装备有限公司 | Automatic processing equipment for motor rotor |
| CN110044909A (en) * | 2019-05-05 | 2019-07-23 | 桂林电子科技大学 | A kind of rotor welding point defect detection device and method based on image procossing |
| CN110044909B (en) * | 2019-05-05 | 2023-08-01 | 桂林电子科技大学 | Motor rotor welding spot defect detection device and method based on image processing |
| CN111729870A (en) * | 2020-07-17 | 2020-10-02 | 成都卓识维景科技有限公司 | Automatic detection device and method for air duct defects of brake disc based on machine vision |
| CN111729870B (en) * | 2020-07-17 | 2020-11-17 | 成都卓识维景科技有限公司 | Automatic detection device and method for air duct defects of brake disc based on machine vision |
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Application publication date: 20170517 |