CN203688459U - On-line fabric quality detection system based on image recognition - Google Patents
On-line fabric quality detection system based on image recognition Download PDFInfo
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- CN203688459U CN203688459U CN201320665541.7U CN201320665541U CN203688459U CN 203688459 U CN203688459 U CN 203688459U CN 201320665541 U CN201320665541 U CN 201320665541U CN 203688459 U CN203688459 U CN 203688459U
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Abstract
The utility model discloses an on-line fabric quality detection system based on image recognition and relates to image processing equipment. The on-line fabric quality detection system comprises a fabric support, a cloth guide roller, a workbench, an image collecting and processing module, a fabric defect feedback module, a bar-code scanner, a visual system support, a track and a track wheel, wherein the image collecting and processing module is provided with an electromotor, a camera, an LED light source and a control panel; the fabric defect feedback module is provided with an encoder and an alertor; the cloth guide roller is installed on the fabric support, one end of a fabric placed on the cloth guide roller is arranged under the bar-code scanner, and the other end of the fabric is arranged on the encoder; the camera and the LED light source are fixed on the lower surfaces of the track and the track wheel, and the track and the track wheel are installed on the visual system support; the control panel is arranged on the workbench, and the online collecting grey fabric image output end of the camera is connected with the input end of the control panel; the output end of the control panel is connected with the input end of the alertor, and the output end of the bar-code scanner is connected with the input end of the control panel.
Description
Technical field
The utility model relates to a kind of image processing equipment, relates in particular to a kind of fabric quality on-line detecting system based on image recognition.
Background technology
Textile Industry dog-eat-dog, fabric quality quality is very large on the income impact of textile industry.But most domestic enterprise still adopts the method for manual detection to detect fabric quality.This have open defect by macroscopic method, and the quality inspection workman of this respect need to be on duty through strict training ability simultaneously, and human cost is higher relatively; On the other hand, along with scientific and technological development, the needed philosophy and technique means of fabric quality automatic checkout system are ripe already.In this case, the exploitation of the fabric defects on-line automatic monitoring system based on image recognition just has very important researching value with application.
Summary of the invention
The purpose of this utility model be to provide a kind of automatically, the fabric quality on-line detecting system based on image recognition based on Digital Image Processing accurately and rapidly.
The utility model is provided with fabric support, fabric guide roll, worktable, image acquisition and processing module, fabric defects feedback module, bar code scanner, vision system support, crawler belt and Athey wheel;
Described image acquisition and processing module are provided with motor, camera, LED light source and DSP+ARM control panel; Fabric defects feedback module is provided with scrambler and alarm; Described fabric guide roll is arranged on fabric support, is positioned over fabric one end on fabric guide roll and is located at the below of bar code scanner, and the fabric other end is located on scrambler, and is recorded the movable length of fabric by scrambler; Described camera and LED light source are located at fabric top, and camera and LED light source are fixed on crawler belt and Athey wheel lower surface, and crawler belt and Athey wheel are installed on vision system support, and crawler belt and Athey wheel are connected with motor and are driven by motor; Crawler belt and Athey wheel drive camera and LED light source to move; DSP+ARM control panel is located on worktable, the online acquisition fabric embryo cloth output end of image of camera connects the input end of DSP+ARM control panel, the output terminal of DSP+ARM control panel is connected with the input end of alarm, the input end of the output termination DSP+ARM control panel of bar code scanner; Fabric face under the visual angle aligning of camera and LED light source, LED light source is fixed on a side of camera.
The utility model adopts and obtains grey cloth surface image and carry out digital figure processing and detect grey quality, and to fault identify, classification, record, testing result is accurately, efficient, cost is low, automaticity is high.Adopt camera to obtain grey cloth surface image and process, judge, and feedback processing result in time, thereby realize online, in real time fabric grey quality detected, and realize the identification of grey cloth fault and record.
Compare with existing fabric defects surface inspecting method, the utlity model has following apparent outstanding substantive distinguishing features and remarkable advantage:
1, design easy: adopt single camera, when detection, camera lens is near fabric and do reciprocal transverse shifting, and accuracy of detection is high, without omitting; Monitoring device entirety can directly be contained on loom, is convenient to safeguard and dismounting;
2, applicability is strong: have stronger applicability, abstract to different faults is one group of fault parameter, can adapt to different fabric grey cloth detections by revising simply environmental parameter, make the range of application of system become wide, with the variation of detected object, can carry out Sample Storehouse more for novel bad point
3, highly-efficient treatment: adopt double-core processing, ARM and DSP dual processor combine, the accuracy of identification of fabric defects is high, scope is wide, and speed is fast;
4, detect in real time: with Mk system and warning system, can real-time mark bad point position record, when serious, give the alarm and the anxious device of shutting down;
5, robotization level is high: the utility model can replace manual operation, reduces labour's expense, raises the efficiency.
Brief description of the drawings
Fig. 1 is the structure composition schematic diagram of the utility model embodiment.
In Fig. 1, be respectively labeled as: 1. fabric support, 2. fabric guide roll, 3. worktable, 4.DSP+ARM control panel, 5. alarm, 6. camera, 7.LED light source, 8. vision system support, 9. bar code scanner, 10. scrambler, 11. motor, 12. crawler belts and Athey wheel.
Embodiment
Below in conjunction with drawings and Examples, the utility model is described in further detail.
Referring to Fig. 1, the utility model embodiment is provided with fabric support 1, fabric guide roll 2, worktable 3, image acquisition and processing module, fabric defects feedback module, bar code scanner 9, vision system support 8, crawler belt and Athey wheel 12.Described image acquisition and processing module are provided with motor 11, camera 6, LED light source 7 and DSP+ARM control panel 4; Fabric defects feedback module is provided with scrambler 10 and alarm 5; Described fabric guide roll 2 is arranged on fabric support 1, is positioned over fabric one end on fabric guide roll 2 and is located at the below of bar code scanner 9, and the fabric other end is located on scrambler 10, and is recorded the movable length of fabric by scrambler 10; Described camera 6 and LED light source 7 are located at fabric top, camera 6 and LED light source 7 are fixed on crawler belt and Athey wheel 12 lower surfaces, crawler belt and Athey wheel 12 are installed on vision system support 8, and crawler belt and Athey wheel 12 are connected with motor 11 and are driven by motor 11; Crawler belt and Athey wheel 12 drive camera 6 and LED light source 7 to move; DSP+ARM control panel 4 is located on worktable 3, the online acquisition fabric embryo cloth output end of image of camera 6 connects the input end of DSP+ARM control panel 4, the output terminal of DSP+ARM control panel 4 is connected with the input end of alarm 5, the input end of the output termination DSP+ARM control panel 4 of bar code scanner 9; Fabric face under the visual angle aligning of camera 6 and LED light source 7, LED light source 7 is fixed on a side of camera 6.
Camera is fixed on to crawler belt lower surface above fabric, controlling lighting device LED light source 7 by DSP+ARM control panel 4 works and controls motor 11 with specific speed drive crawler belt and Athey wheel 12, ensure that camera 6 and LED light source 7 move carrying out back and forth repeatedly rectilinear motion on perpendicular to fabric translational speed direction above fabric, camera 6 is taken with specific frequency simultaneously, the pictorial information that camera is collected sends DSP+ARM control panel 4 to, by writing corresponding program bonded fabric graphics standard storehouse, the digital picture of having obtained is carried out to pre-service, feature extraction, discriminator, the work such as preservation.System run duration scrambler 10 will record the movable length of fabric, coordinates the position of cam lens to determine the exact position of each fault on fabric, is stored in DSP+ARM control panel 4.If find during monitoring there are serious problems in fabric, and DSP+ARM control panel 4 gives the alarm control alarm 5, and the operation of Break-Up System.After after the detection in a stage finishes, DSP+ARM control panel 4 carries out control bar code scanner 9 scanning the mark of bar code in corresponding place, store the information of fault, after fabric has detected, need to read bar code information and just can obtain the quality condition of this batch of fabric.
In the time serious fault being detected, by DSP+ARM control panel control warning circuit give the alarm and Break-Up System move, staff can be repaired immediately; In addition the angle that while using the scrambler measuring and calculating fabric being installed in loom rotating shaft to occur fault in fabrication processes, machine tool chief axis turns over, converse the particular location that occurs fault on whole fabric, and the distributed intelligence on fabric is stored by fault by algorithm.After fabric has detected, every fabric is sticked to bar code, by bar code scanner, the coding of bar code is read into disposal system simultaneously.After this, disposal system is by by corresponding the production informations such as the defect position of this bar code and this fabric, and it feeds back to administrative center in order to use the most at last.
The effect of system critical piece:
Motor 11: drive camera and LED light source rectilinear motion back and forth.
Camera 6: online acquisition fabric grey cloth image, and be connected to DSP+ARM control panel.
7: one groups of LED light sources of LED light source can provide illumination even, low reflection, provide light source on the one hand to photographed scene, prevent that on the other hand uneven illumination from affecting picture quality.
Crawler belt and Athey wheel 12: drive camera to prolong with fabric movement direction vertical direction and move back and forth with low speed, prevent from omitting.
DSP+ARM control panel 4: mainly the image collecting is analyzed, obtained fault information, carry out fault classification and control alarm.
Bar code scanner 9: scanning bar code storing information.
Scrambler 10: by the measuring and calculating of the rotation number of turns to loom main shaft, in the hope of fault particular location.
System is as follows to fabric quality detecting step:
1, camera collection image;
2, picture signal converts digital signal to and is sent to DSP+ARM control panel;
3, DSP+ARM control panel carries out the processing such as color conversion, filtering, threshold segmentation, morphology processing, feature extraction to view data;
4, DSP+ARM control panel is according to the different actions of fabric quality control, as reports to the police, halt system running etc. when serious;
5, defect position information is fed back to DSP+ARM control panel by scrambler, and DSP+ARM control panel is integrated fabric information store.
This detection system repeats above-mentioned steps in fabrication processes always, to realize the online detection to fabric quality.
Claims (1)
1. the fabric quality on-line detecting system based on image recognition, is characterized in that being provided with fabric support, fabric guide roll, worktable, image acquisition and processing module, fabric defects feedback module, bar code scanner, vision system support, crawler belt and Athey wheel;
Described image acquisition and processing module are provided with motor, camera, LED light source and DSP+ARM control panel; Fabric defects feedback module is provided with scrambler and alarm; Described fabric guide roll is arranged on fabric support, is positioned over fabric one end on fabric guide roll and is located at the below of bar code scanner, and the fabric other end is located on scrambler, and is recorded the movable length of fabric by scrambler; Described camera and LED light source are located at fabric top, and camera and LED light source are fixed on crawler belt and Athey wheel lower surface, and crawler belt and Athey wheel are installed on vision system support, and crawler belt and Athey wheel are connected with motor and are driven by motor; Crawler belt and Athey wheel drive camera and LED light source to move; DSP+ARM control panel is located on worktable, the online acquisition fabric embryo cloth output end of image of camera connects the input end of DSP+ARM control panel, the output terminal of DSP+ARM control panel is connected with the input end of alarm, the input end of the output termination DSP+ARM control panel of bar code scanner; Fabric face under the visual angle aligning of camera and LED light source, LED light source is fixed on a side of camera.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201320665541.7U CN203688459U (en) | 2013-10-25 | 2013-10-25 | On-line fabric quality detection system based on image recognition |
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| CN201320665541.7U CN203688459U (en) | 2013-10-25 | 2013-10-25 | On-line fabric quality detection system based on image recognition |
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| CN203688459U true CN203688459U (en) | 2014-07-02 |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106556604A (en) * | 2016-11-21 | 2017-04-05 | 电子科技大学中山学院 | Cloth inspection machine capable of inspecting and marking flaws and use method thereof |
| CN108318496A (en) * | 2018-05-09 | 2018-07-24 | 海宁市科威工业电子科技有限公司 | One kind being used for the online fabric defects detection device of tricot machine |
| WO2018214661A1 (en) * | 2017-05-24 | 2018-11-29 | 香港纺织及成衣研发中心 | Method and system for automatic detection of fabric defect, and computer readable storage medium |
| CN108951077A (en) * | 2018-08-10 | 2018-12-07 | 平湖市新保纺织科技有限公司 | A kind of fabric detection device |
| TWI644095B (en) * | 2016-12-20 | 2018-12-11 | 財團法人紡織產業綜合研究所 | Fabric package apparatus |
| CN109752378A (en) * | 2017-11-01 | 2019-05-14 | 香港理工大学 | Mobile Automatic Detection of Fabric Defects system and its control method |
| CN111556232A (en) * | 2020-04-30 | 2020-08-18 | 西安工程大学 | Non-contact type cut pile fabric thickness shooting device |
| CN113322654A (en) * | 2021-07-06 | 2021-08-31 | 常州宏大智能装备产业发展研究院有限公司 | Fabric weft straightening method |
| CN117740814A (en) * | 2024-02-21 | 2024-03-22 | 泉州市纳通智能科技有限公司 | Online detection device and detection method in textile knitting forming based on machine vision |
-
2013
- 2013-10-25 CN CN201320665541.7U patent/CN203688459U/en not_active Expired - Fee Related
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106556604A (en) * | 2016-11-21 | 2017-04-05 | 电子科技大学中山学院 | Cloth inspection machine capable of inspecting and marking flaws and use method thereof |
| CN106556604B (en) * | 2016-11-21 | 2019-02-22 | 电子科技大学中山学院 | Cloth inspection machine capable of inspecting and marking flaws and use method thereof |
| TWI644095B (en) * | 2016-12-20 | 2018-12-11 | 財團法人紡織產業綜合研究所 | Fabric package apparatus |
| US10942133B2 (en) | 2017-05-24 | 2021-03-09 | The Hong Kong Research Institute Of Textiles And Apparel Limited | Method and system for automatically detecting fabric defect, and computer readable storage medium |
| WO2018214661A1 (en) * | 2017-05-24 | 2018-11-29 | 香港纺织及成衣研发中心 | Method and system for automatic detection of fabric defect, and computer readable storage medium |
| CN109752378A (en) * | 2017-11-01 | 2019-05-14 | 香港理工大学 | Mobile Automatic Detection of Fabric Defects system and its control method |
| CN108318496A (en) * | 2018-05-09 | 2018-07-24 | 海宁市科威工业电子科技有限公司 | One kind being used for the online fabric defects detection device of tricot machine |
| CN108951077A (en) * | 2018-08-10 | 2018-12-07 | 平湖市新保纺织科技有限公司 | A kind of fabric detection device |
| CN111556232A (en) * | 2020-04-30 | 2020-08-18 | 西安工程大学 | Non-contact type cut pile fabric thickness shooting device |
| CN111556232B (en) * | 2020-04-30 | 2021-08-27 | 西安工程大学 | Non-contact type cut pile fabric thickness shooting device |
| CN113322654A (en) * | 2021-07-06 | 2021-08-31 | 常州宏大智能装备产业发展研究院有限公司 | Fabric weft straightening method |
| CN113322654B (en) * | 2021-07-06 | 2022-04-08 | 常州宏大智能装备产业发展研究院有限公司 | Fabric weft straightening method |
| CN117740814A (en) * | 2024-02-21 | 2024-03-22 | 泉州市纳通智能科技有限公司 | Online detection device and detection method in textile knitting forming based on machine vision |
| CN117740814B (en) * | 2024-02-21 | 2024-05-03 | 泉州市纳通智能科技有限公司 | Online detection device and detection method in textile knitting forming based on machine vision |
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