CN2723993Y - Automatic image identification magnetic powder flaw detector for train wheel shaft - Google Patents
Automatic image identification magnetic powder flaw detector for train wheel shaft Download PDFInfo
- Publication number
- CN2723993Y CN2723993Y CN 200420016605 CN200420016605U CN2723993Y CN 2723993 Y CN2723993 Y CN 2723993Y CN 200420016605 CN200420016605 CN 200420016605 CN 200420016605 U CN200420016605 U CN 200420016605U CN 2723993 Y CN2723993 Y CN 2723993Y
- Authority
- CN
- China
- Prior art keywords
- wheel shaft
- flaw detector
- flaw detection
- utility
- model
- 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.)
- Expired - Fee Related
Links
Images
Landscapes
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The utility model relates to an automatic image identification magnetic powder flaw detector for a train wheel shaft, which comprises a flaw detector body, a track arranged inside the flaw detector body, a wheel rotating device which can drive a wheel shaft to rotate, and an ultraviolet lamp arranged on the flaw detector body. The utility model is characterized in that a flaw detector body is provided with five or more than five CCD cameras arranged in a line and connected with a computer device at one side of the wheel shaft, and the CCD cameras are provided with moveable focusing devices. The utility model can automatically detect whether a train wheel shaft has cracks or not, avoid ultraviolet hurting human body, keep civilized production, eliminate human factors and objectively reflect the true quality status of a checked product.
Description
Technical field
The utility model relates to a kind of train axle automated graphics identification magnaflux.
Technical background
Present rolling stock section axle inspection device 3000 type magnafluxs that adopt must be under ultraviolet light when using this equipment flaw detection more, is examined by human eye and can find out just whether this axletree has crackle.Operation may produce following problem like this: 1, ultraviolet long-term irradiation is harmful to health; 2, people observe with eyes has tired the time unavoidably, causes breaking axis owing to distraction may bring to judge by accident.
Summary of the invention
Technical problem to be solved in the utility model provides in a kind of use the injury of the person and surveys a kind of accurately train axle automated graphics identification magnaflux.
The utility model adopts following technical scheme: the utility model comprises flaw detection organism, be arranged on track in the flaw detection organism, can drive the runner device that wheel shaft rotates and be arranged on ultraviolet light on the flaw detection organism, it is characterized in that a side at the flaw detection organism upper whorl axial is word row and is provided with the ccd video camera more than 5 or 5 that is connected with computer installation.
The utility model ccd video camera is provided with mobile focus control.
The utility model good effect is as follows: use the utility model camera that train axle is all taken, make the crackle clear picture as seen by Computer Analysis.The utility model adopts a plurality of cameras, makes it can cover the surface of axletree comprehensively, and it is clear to adopt autofocus system that all cameras can both be taken.Utilize the technology of computer picture recognition crackle to carry out analysis and judgement behind the input computing machine.Using the utility model to detect train axle automatically has flawless, stops the injury of ultraviolet ray to the person, accomplishes to carry out production strictly in line with rules and regulations, and gets rid of human factor, objectively responds detected material real quality situation.
Description of drawings
Accompanying drawing 1 is the utility model structural representation
Accompanying drawing 2 is that accompanying drawing 1A-A is to cut-open view
In the accompanying drawings: 1 flaw detection organism, 2 tracks, 3 wheel shafts, 4 runner devices, 5 ultraviolet lights, 6 video cameras, 7 computer installations, 8 move focus control
Embodiment
The utility model comprises flaw detection organism 1, be arranged on track 2 in the flaw detection organism 1, can drive the runner device 4 that wheel shaft 3 rotates and be arranged on ultraviolet light 5 on the flaw detection organism 1, the utility model is word order in a side of flaw detection organism 1 upper whorl axial 3 and is provided with 14 ccd video cameras 6 that are connected with computer installation 7.Tested wheel shaft 3 is driven on track 2 by runner device 4 and rotates, 6 pairs of wheel shafts of 14 video cameras 3 carry out integral body and take, utilize the technology of computer picture recognition crackle to carry out analysis and judgement behind the input computer installation 7, the promptly mobile focus control 8 of the utility model application machine device is regulated a plurality of ccd video cameras 6 in one line automatically, make the surface of it and detected wheel shaft 3 remain certain distance, in case ccd video camera 6 focus regulators are clear like this, just can photograph distinct image to any wheel shaft, and these images are sent into computing machine, utilize computer picture can automatically identify the crackle part of wheel shaft 3, make the crackle clear picture as seen by Computer Analysis to the special software of Identification of Cracks.The utility model adopts a plurality of cameras, make it can cover the surface of axletree comprehensively, it is clear to adopt the promptly mobile focus control 8 of autofocus system that all cameras can both be taken, utilize the technology of computer picture recognition crackle to carry out analysis and judgement behind the input computing machine, and report to the police, use the utility model can detect train axle 3 automatically flawless is arranged, in testing process, stopped the injury of ultraviolet ray like this to the person, accomplish to carry out production strictly in line with rules and regulations, and the eliminating human factor, objectively respond detected material real quality situation.
Claims (2)
1, a kind of train axle automated graphics identification magnaflux, it comprises flaw detection flaw detection organism (1), be arranged on track (2) in flaw detection flaw detection organism (1), can drive the runner device (4) that wheel shaft (3) rotates and be arranged on ultraviolet light (5) on the flaw detection flaw detection organism (1), it is characterized in that a side at flaw detection flaw detection organism (1) upper whorl axial (3) is word row and is provided with the ccd video camera more than 5 or 5 (6) that is connected with computer installation (7).
2, the magnaflux of a kind of train axle automated graphics identification according to claim 1 is characterized in that described ccd video camera (6) is provided with mobile focus control (8).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200420016605 CN2723993Y (en) | 2004-08-05 | 2004-08-05 | Automatic image identification magnetic powder flaw detector for train wheel shaft |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200420016605 CN2723993Y (en) | 2004-08-05 | 2004-08-05 | Automatic image identification magnetic powder flaw detector for train wheel shaft |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN2723993Y true CN2723993Y (en) | 2005-09-07 |
Family
ID=35037617
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200420016605 Expired - Fee Related CN2723993Y (en) | 2004-08-05 | 2004-08-05 | Automatic image identification magnetic powder flaw detector for train wheel shaft |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN2723993Y (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101915734A (en) * | 2010-07-22 | 2010-12-15 | 北京交通大学 | Line scanning collecting method and device for magnetic trace images in magnetic particle inspection |
| CN101275918B (en) * | 2007-03-30 | 2012-02-22 | 加特可株式会社 | Apparatus for appearance check of workpiece |
| CN102590330A (en) * | 2011-12-29 | 2012-07-18 | 南京理工大学常熟研究院有限公司 | Image processing-based magnetic particle inspection defect intelligent identification detection system |
| CN103063739A (en) * | 2012-12-21 | 2013-04-24 | 射阳县无损检测技术研究所 | Automatic image acquiring magnetic particle flaw detector for train axles |
| CN103235035A (en) * | 2013-03-28 | 2013-08-07 | 射阳县无损检测技术研究所 | Double-row comb-shaped electrode folding coil wheel pair magnetic particle flaw detector |
| CN103412042A (en) * | 2013-08-27 | 2013-11-27 | 北京磁通设备制造有限公司 | Axle magnetic powder diagnostic machine with image display function |
| CN107238657A (en) * | 2017-06-06 | 2017-10-10 | 北京博力加机电技术有限公司 | Railway wheel shaft automation imaging magnaflux and method |
| CN109085239A (en) * | 2018-07-24 | 2018-12-25 | 成都铁安科技有限责任公司 | A kind of wheel shaft comprehensive diagnos platform |
| CN109374630A (en) * | 2018-09-28 | 2019-02-22 | 新兴铸管股份有限公司 | Ductile iron pipe casting flaw intelligent detecting method |
| CN110426448A (en) * | 2019-08-01 | 2019-11-08 | 捷航设备制造股份有限公司 | A kind of magnetic powder inspection trolley for taking into account axle flaw detection function for axle inspection machine |
-
2004
- 2004-08-05 CN CN 200420016605 patent/CN2723993Y/en not_active Expired - Fee Related
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101275918B (en) * | 2007-03-30 | 2012-02-22 | 加特可株式会社 | Apparatus for appearance check of workpiece |
| CN101915734A (en) * | 2010-07-22 | 2010-12-15 | 北京交通大学 | Line scanning collecting method and device for magnetic trace images in magnetic particle inspection |
| CN102590330A (en) * | 2011-12-29 | 2012-07-18 | 南京理工大学常熟研究院有限公司 | Image processing-based magnetic particle inspection defect intelligent identification detection system |
| CN103063739A (en) * | 2012-12-21 | 2013-04-24 | 射阳县无损检测技术研究所 | Automatic image acquiring magnetic particle flaw detector for train axles |
| CN103063739B (en) * | 2012-12-21 | 2016-02-10 | 射阳县无损检测技术研究所 | Train axle automated graphics picked-up magnaflux |
| CN103235035A (en) * | 2013-03-28 | 2013-08-07 | 射阳县无损检测技术研究所 | Double-row comb-shaped electrode folding coil wheel pair magnetic particle flaw detector |
| CN103412042A (en) * | 2013-08-27 | 2013-11-27 | 北京磁通设备制造有限公司 | Axle magnetic powder diagnostic machine with image display function |
| CN107238657A (en) * | 2017-06-06 | 2017-10-10 | 北京博力加机电技术有限公司 | Railway wheel shaft automation imaging magnaflux and method |
| CN107238657B (en) * | 2017-06-06 | 2021-04-13 | 北京博力加机电技术有限公司 | Automatic imaging magnetic powder flaw detector for railway wheel axle and method |
| CN109085239A (en) * | 2018-07-24 | 2018-12-25 | 成都铁安科技有限责任公司 | A kind of wheel shaft comprehensive diagnos platform |
| CN109374630A (en) * | 2018-09-28 | 2019-02-22 | 新兴铸管股份有限公司 | Ductile iron pipe casting flaw intelligent detecting method |
| CN110426448A (en) * | 2019-08-01 | 2019-11-08 | 捷航设备制造股份有限公司 | A kind of magnetic powder inspection trolley for taking into account axle flaw detection function for axle inspection machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN2723993Y (en) | Automatic image identification magnetic powder flaw detector for train wheel shaft | |
| CN111014079B (en) | Bearing defect detection device and bearing defect detection method | |
| CN112945972B (en) | Steel wire rope state detection device and method based on machine vision | |
| US10209200B2 (en) | High-speed, 3-D method and system for optically inspecting parts | |
| CN110403232B (en) | Cigarette quality detection method based on secondary algorithm | |
| CN201555812U (en) | Visual surface blemish detecting instrument of steel balls | |
| CN110420882B (en) | Automatic line system and method for crankshaft magnetic powder inspection based on intelligent manufacturing mode | |
| CN204924983U (en) | Lens defect automatic checkout device of grating modulation | |
| CN109142509B (en) | Round steel magnetic powder flaw detection method and device | |
| CN104483320A (en) | Digitized defect detection device and detection method of industrial denitration catalyst | |
| CN106353336A (en) | Lens coating automatic detection system | |
| CN108562592A (en) | A kind of bottled medicinal liquor Impurity Detection System | |
| CN111530765A (en) | Online intelligent defective product identification and removal device | |
| CN201331508Y (en) | Automatic detection device for flaw detection of magnetic powder on metal shaft part surface | |
| CN113566704A (en) | Bearing assembly ball size detection method based on machine vision | |
| JP2013156173A (en) | Inspection method for turbine blade and device therefor | |
| CN107121266A (en) | LCD and LCM automatic optical detection device | |
| CN2598822Y (en) | Train wheel shaft surface crack automatic detecting device | |
| TWI788175B (en) | Leather defect detection system | |
| CN105784718A (en) | Finished cable appearance inspection equipment | |
| CN115170493A (en) | Identification method and system for micro-defect of sterile package and storage medium | |
| EP3757939A1 (en) | Method and apparatus for checking the production quality of cables that are provided with a protective sheath, in particular electrical cables | |
| CN209198334U (en) | A kind of bearing roller unfolded surface and detection device | |
| CN111780674A (en) | Visual detection system based on image processing and machine learning | |
| JPH07209197A (en) | Method and apparatus for inspecting cylindrical roll bearing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C19 | Lapse of patent right due to non-payment of the annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |