CN111054640A - Automatic change mechanical detection device - Google Patents
Automatic change mechanical detection device Download PDFInfo
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- CN111054640A CN111054640A CN202010015205.2A CN202010015205A CN111054640A CN 111054640 A CN111054640 A CN 111054640A CN 202010015205 A CN202010015205 A CN 202010015205A CN 111054640 A CN111054640 A CN 111054640A
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- 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
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- 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
- B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
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- 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
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- 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
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
-
- 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
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
- B07C5/362—Separating or distributor mechanisms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
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- 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
- B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
- B07C2501/0063—Using robots
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/028—Material parameters
- G01N2291/0289—Internal structure, e.g. defects, grain size, texture
Abstract
The invention discloses an automatic mechanical detection device, which comprises an image acquisition module, a dismounting manipulator, a belt conveyor, an infrared measurement light curtain group, an ultrasonic flaw detector and a sorting manipulator, wherein the PC is communicated with the PC; the image acquisition module, the infrared measurement light curtain group and the ultrasonic flaw detector are respectively used for acquiring a mechanical whole image, a mechanical part shape parameter and a mechanical part internal defect parameter and respectively transmitting the acquired data to the PC, and the PC is internally provided with a data post-processing system which comprises a data local storage module, a mechanical part identification and positioning module, a mechanical part shape identification module, a mechanical part internal defect evaluation module, a mechanical part classification module and a control command generation module. The automatic and comprehensive continuous detection and classification of mechanical parts can be realized, the error of the detection process is small, the detection efficiency is improved, and the labor cost is greatly saved.
Description
Technical Field
The invention relates to a mechanical part detection system, in particular to an automatic mechanical detection device.
Background
In the installation and maintenance process of mechanical equipment, the integrity detection of parts is an extremely important process which needs to be carried out by people, the detection of whether the parts are intact not only affects the maintenance quality of the people, but also affects the cost required by the mechanical maintenance.
In the current mechanical detection process, people generally use manpower to confirm the geometric shapes of the parts, the generated errors are large, the detection efficiency is greatly reduced, the accident probability of the machine is increased, meanwhile, the current mechanical detection device cannot continuously detect a plurality of parts, and a good classification method does not exist in the sorting process of the scrapped parts.
Disclosure of Invention
The invention aims to provide an automatic mechanical detection device, which can realize automatic and all-dimensional continuous detection and classification of mechanical parts, has small error in a detection process, improves the detection efficiency and greatly saves the labor cost.
In order to achieve the purpose, the invention adopts the technical scheme that:
an automatic mechanical detection device comprises an image acquisition module, a dismounting manipulator, a belt conveyor, an infrared measurement light curtain group, an ultrasonic flaw detector and a sorting manipulator, wherein the PC is communicated with the PC; the system comprises an image acquisition module, an infrared measurement light curtain group and an ultrasonic flaw detector, wherein the image acquisition module, the infrared measurement light curtain group and the ultrasonic flaw detector are respectively used for acquiring a mechanical integral image, a mechanical part shape parameter and a mechanical part internal defect parameter and respectively transmitting the acquired data to a PC (personal computer), the PC is internally provided with a data post-processing system which is composed of a data local storage module, a mechanical part identification and positioning module, a mechanical part shape identification module, a mechanical part internal defect evaluation module, a mechanical part classification module and a control command generation module, and the mechanical part identification and positioning module is used for identifying and positioning the mechanical part in the mechanical integral image; the mechanical part shape recognition module is used for outputting a corresponding mechanical part shape recognition result according to the mechanical part shape parameters collected by the infrared measurement light curtain group; the mechanical part internal defect evaluation module is used for realizing the evaluation of the internal defects of the mechanical part according to the internal defect parameters of the mechanical part collected by the ultrasonic flaw detector; the mechanical part classification module is used for realizing the classification of the mechanical parts according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module; the control command generation module is used for outputting corresponding control commands to the disassembling and assembling manipulator and the sorting manipulator according to processing results of the mechanical part identification and positioning module and the mechanical part classification module; the mechanical part disassembling and assembling device comprises a mechanical part classifying module, a disassembling and assembling mechanical arm and a sorting mechanical arm, wherein the disassembling and assembling mechanical arm is used for realizing the disassembling and assembling operation of mechanical parts according to the result of the mechanical part recognizing and positioning, and the sorting mechanical arm is used for scraping the mechanical parts into corresponding mechanical part collecting frames according to the classifying result of the mechanical part classifying module.
Furthermore, the infrared measurement light curtain groups are three groups and are respectively arranged on the upper side, the lower side, the left side, the right side, the front side and the rear side of the belt conveyor to form a cube infrared light curtain.
Furthermore, dismouting manipulator includes serpentine manipulator, installs assembly and disassembly tools and binocular vision sensor at serpentine manipulator operating end, and this serpentine manipulator comprises a plurality of mechanical unit that are end to end connection and the steering wheel subassembly that is located between the mechanical unit, all installs a three-dimensional digital compass in every mechanical unit.
Further, the mechanical part identification and positioning module respectively performs image denoising and image enhancement preprocessing by adopting bilateral filtering and piecewise linear transformation algorithms; the image binarization processing is carried out by adopting an iterative adaptive threshold segmentation method, small-area noise is removed based on the morphological region characteristics of the connected components, the detection of mechanical parts in the image is realized, the shape recognition of the mechanical parts is carried out based on the length-width ratio of the connected component circumscribed rectangle, then a coordinate system is constructed by taking the center point of the machine as the center of a circle, and the coordinates of the mechanical parts are output.
Further, after the disassembly operation of all mechanical parts in the current image is completed, the image acquisition module automatically starts to acquire a new mechanical overall image, and the mechanical part identification and positioning module identifies and positions the mechanical parts in the overall image until no mechanical parts exist in the acquired mechanical overall image.
Further, the mechanical part classification module realizes the classification of the mechanical parts according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module based on the LSSVM.
Further, the sorting manipulator is arranged at the outlet end of the belt conveyor and adopts a snake-shaped manipulator.
The invention has the following beneficial effects:
the automatic disassembly machine is based on a machine vision technology and an image processing and recognition technology, realizes the automatic disassembly of mechanical parts, realizes the automatic measurement of the external shape and the internal defects of the mechanical parts based on a light curtain method and an ultrasonic detection technology, and realizes the automatic classification of the mechanical parts based on the LSSVM and the sorting manipulator.
Drawings
Fig. 1 is a block diagram of an automated mechanical inspection apparatus according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, an embodiment of the present invention provides an automatic mechanical detection apparatus, which includes an image acquisition module, a disassembly and assembly manipulator, a belt conveyor, an infrared measurement light curtain set, an ultrasonic flaw detector, and a sorting manipulator, where the image acquisition module and the disassembly and assembly manipulator are in communication with each other; the system comprises an image acquisition module, an infrared measurement light curtain group and an ultrasonic flaw detector, wherein the image acquisition module, the infrared measurement light curtain group and the ultrasonic flaw detector are respectively used for acquiring a mechanical integral image, a mechanical part shape parameter and a mechanical part internal defect parameter and respectively transmitting the acquired data to a PC (personal computer), the PC is internally provided with a data post-processing system which is composed of a data local storage module, a mechanical part identification and positioning module, a mechanical part shape identification module, a mechanical part internal defect evaluation module, a mechanical part classification module and a control command generation module, and the mechanical part identification and positioning module is used for identifying and positioning the mechanical part in the mechanical integral image; the mechanical part shape recognition module is used for outputting a corresponding mechanical part shape recognition result according to the mechanical part shape parameters collected by the infrared measurement light curtain group; the mechanical part internal defect evaluation module is used for realizing the evaluation of the internal defects of the mechanical part based on a BP neural network model according to the internal defect parameters of the mechanical part collected by the ultrasonic flaw detector; the mechanical part classification module is used for realizing the classification of the mechanical parts according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module; the control command generation module is used for outputting corresponding control commands to the disassembling and assembling manipulator and the sorting manipulator according to processing results of the mechanical part identification and positioning module and the mechanical part classification module; the mechanical part disassembling and assembling device comprises a mechanical part classifying module, a disassembling and assembling mechanical arm and a sorting mechanical arm, wherein the disassembling and assembling mechanical arm is used for realizing the disassembling and assembling operation of mechanical parts according to the result of the mechanical part recognizing and positioning, and the sorting mechanical arm is used for scraping the mechanical parts into corresponding mechanical part collecting frames according to the classifying result of the mechanical part classifying module.
In the embodiment, the infrared measurement light curtain groups are three groups which are respectively arranged on the upper side, the lower side, the left side, the right side, the front side and the rear side of the belt conveyor to form a cube infrared light curtain,
in the embodiment, the disassembling and assembling manipulator comprises a serpentine manipulator, a disassembling and assembling tool and a binocular vision sensor, the disassembling and assembling tool and the binocular vision sensor are installed at an operating end of the serpentine manipulator, the serpentine manipulator is composed of a plurality of mechanical units which are connected end to end and a steering engine component which is positioned between the mechanical units, a three-dimensional digital compass is installed in each mechanical unit, a PC end outputs a motion track of the serpentine manipulator according to current position information and attitude information of the serpentine manipulator, current mechanical positioning information and part identification result information, the serpentine manipulator realizes obstacle avoidance and obstacle crossing through the binocular vision sensor and the three-dimensional digital compass in the motion process, after reaching a designated position, the PC end outputs a corresponding disassembling and assembling tool/part collecting disc motion track according to the identification result of a part at the position, the serpentine manipulator receives a command to drive the disassembling and assembling tool to move to realize the disassembling of the part, whole process needs the cooperation of two serpentine manipulator, and one of them dismantles the operation, and another carries out spare part receiving operation, welds a spare part catch tray promptly on this serpentine manipulator, is equipped with a film pressure sensor on the spare part catch tray, judges whether to have the spare part of receiving based on the instantaneous pressure of the production that the spare part dropped, and this serpentine manipulator is after receiving spare part, directly places spare part on belt conveyor.
In the embodiment, the mechanical part identification and positioning module respectively performs image denoising and image enhancement preprocessing by adopting bilateral filtering and piecewise linear transformation algorithms; the method comprises the steps of performing image binarization processing by adopting an iterative adaptive threshold segmentation method, removing small-area noise based on morphological region characteristics of connected components, detecting mechanical parts in an image, identifying the shapes of the mechanical parts based on the length-width ratio of a rectangle externally connected with the connected components, constructing a coordinate system by taking a center point of machinery as a circle center, and outputting coordinates where the mechanical parts are located, wherein the identification of the shapes of the parts is to configure corresponding disassembling tools, and the acquisition of the coordinates of the parts is to generate a subsequent movement track of a disassembling manipulator.
In this embodiment, after the operation of detaching all the mechanical parts in the current image is completed, the image acquisition module automatically starts to acquire a new mechanical overall image, the mechanical part identification and positioning module identifies and positions the mechanical parts in the overall image until no mechanical parts exist in the acquired mechanical overall image, the PC end automatically locks a task after each mechanical part detachment is completed, and all the parts corresponding to the overall image are detached and completed until all the tasks are locked.
In this embodiment, the mechanical part classification module realizes classification of mechanical parts according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module based on the LSSVM.
In this embodiment, the sorting manipulator is arranged at the outlet end of the belt conveyor, and a serpentine manipulator is adopted, and it should be noted that the distance between two adjacent components needs to be greater than the operation range required by the sorting manipulator.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (7)
1. An automatic change mechanical testing device which characterized in that: the system comprises an image acquisition module, a dismounting manipulator, a belt conveyor, an infrared measurement light curtain group, an ultrasonic flaw detector and a sorting manipulator, wherein the PC is communicated with the PC; the system comprises an image acquisition module, an infrared measurement light curtain group and an ultrasonic flaw detector, wherein the image acquisition module, the infrared measurement light curtain group and the ultrasonic flaw detector are respectively used for acquiring a mechanical integral image, a mechanical part shape parameter and a mechanical part internal defect parameter and respectively transmitting the acquired data to a PC (personal computer), the PC is internally provided with a data post-processing system which is composed of a data local storage module, a mechanical part identification and positioning module, a mechanical part shape identification module, a mechanical part internal defect evaluation module, a mechanical part classification module and a control command generation module, and the mechanical part identification and positioning module is used for identifying and positioning the mechanical part in the mechanical integral image; the mechanical part shape recognition module is used for outputting a corresponding mechanical part shape recognition result according to the mechanical part shape parameters collected by the infrared measurement light curtain group; the mechanical part internal defect evaluation module is used for realizing the evaluation of the internal defects of the mechanical part according to the internal defect parameters of the mechanical part collected by the ultrasonic flaw detector; the mechanical part classification module is used for realizing the classification of the mechanical parts according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module; the control command generation module is used for outputting corresponding control commands to the disassembling and assembling manipulator and the sorting manipulator according to processing results of the mechanical part identification and positioning module and the mechanical part classification module; the mechanical part disassembling and assembling device comprises a mechanical part classifying module, a disassembling and assembling mechanical arm and a sorting mechanical arm, wherein the disassembling and assembling mechanical arm is used for realizing the disassembling and assembling operation of mechanical parts according to the result of the mechanical part recognizing and positioning, and the sorting mechanical arm is used for scraping the mechanical parts into corresponding mechanical part collecting frames according to the classifying result of the mechanical part classifying module.
2. An automated mechanical testing device according to claim 1, wherein: the infrared measurement light curtain sets are three sets and are respectively arranged on the upper side, the lower side, the left side, the right side, the front side and the rear side of the belt conveyor to form a cube infrared light curtain.
3. An automated mechanical testing device according to claim 1, wherein: the disassembly and assembly manipulator comprises a snake-shaped manipulator, a disassembly and assembly tool and a binocular vision sensor, wherein the disassembly and assembly tool and the binocular vision sensor are installed at the operation end of the snake-shaped manipulator, the snake-shaped manipulator is composed of a plurality of mechanical units which are connected end to end and steering engine components which are located between the mechanical units, and a three-dimensional digital compass is installed in each mechanical unit.
4. An automated mechanical testing device according to claim 1, wherein: the mechanical part identification and positioning module respectively performs image denoising and image enhancement preprocessing by adopting bilateral filtering and piecewise linear transformation algorithms; the image binarization processing is carried out by adopting an iterative adaptive threshold segmentation method, small-area noise is removed based on the morphological region characteristics of the connected components, the detection of mechanical parts in the image is realized, the shape recognition of the mechanical parts is carried out based on the length-width ratio of the connected component circumscribed rectangle, then a coordinate system is constructed by taking the center point of the machine as the center of a circle, and the coordinates of the mechanical parts are output.
5. An automated mechanical testing device according to claim 1, wherein: after the disassembly operation of all mechanical parts in the current image is completed, the image acquisition module automatically starts to acquire a new mechanical overall image, and the mechanical part identification and positioning module realizes the identification and positioning of the mechanical parts in the overall image until no mechanical part exists in the acquired mechanical overall image.
6. An automated mechanical testing device according to claim 1, wherein: and the mechanical part classification module realizes the classification of mechanical parts based on the LSSVM according to the processing results of the mechanical part shape recognition module and the mechanical part internal defect evaluation module.
7. An automated mechanical testing device according to claim 1, wherein: the sorting mechanical arm is arranged at the outlet end of the belt conveyor and adopts a snake-shaped mechanical arm.
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| CN202010015205.2A CN111054640A (en) | 2020-01-07 | 2020-01-07 | Automatic change mechanical detection device |
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| CN202010015205.2A CN111054640A (en) | 2020-01-07 | 2020-01-07 | Automatic change mechanical detection device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111558540A (en) * | 2020-05-27 | 2020-08-21 | 广东原点智能技术有限公司 | Quality inspection system of automobile crankshaft |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1806940A (en) * | 2006-01-23 | 2006-07-26 | 湖南大学 | Defective goods automatic sorting method and equipment for high-speed automated production line |
| CN2893701Y (en) * | 2006-05-18 | 2007-04-25 | 沈睿 | Metal long rod pieces heat treatment quality continuous non-destructive testing equipment |
| CN203745341U (en) * | 2014-04-02 | 2014-07-30 | 川渝中烟工业有限责任公司 | Image recognition technology-based tobacco aromatic bead quality rapid-detection device |
| CN104259108A (en) * | 2014-10-22 | 2015-01-07 | 大连富地机械制造有限公司 | Automatic picking method and device for shaft parts |
| CN105290785A (en) * | 2015-12-01 | 2016-02-03 | 长沙长泰机器人有限公司 | Workpiece sorting and assembling system based on vision |
| CN205318747U (en) * | 2015-12-07 | 2016-06-15 | 重庆英耐基科技发展有限公司 | Automatic real device of instructing is produced to metaplasia |
| CN105806849A (en) * | 2016-04-08 | 2016-07-27 | 广东工业大学 | Automobile seat surface defect detection system based on machine vision as well as detection method |
| CN107176432A (en) * | 2017-06-15 | 2017-09-19 | 西安科技大学 | A kind of anchor pole foreign matter and belt tearing detecting system based on machine vision |
| CN107398428A (en) * | 2017-09-08 | 2017-11-28 | 深圳市柯莱顿光电科技有限公司 | A kind of picking sensor |
| CN109499908A (en) * | 2018-11-10 | 2019-03-22 | 东莞理工学院 | A kind of vision detection system for machine components |
| CN109738460A (en) * | 2019-01-28 | 2019-05-10 | 西京学院 | A kind of evaluation detection system for civil engineering structure visual defects |
| CN110497416A (en) * | 2019-09-16 | 2019-11-26 | 吉林科创电力有限公司 | A kind of trouble-shooter of switchgear |
-
2020
- 2020-01-07 CN CN202010015205.2A patent/CN111054640A/en not_active Withdrawn
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1806940A (en) * | 2006-01-23 | 2006-07-26 | 湖南大学 | Defective goods automatic sorting method and equipment for high-speed automated production line |
| CN2893701Y (en) * | 2006-05-18 | 2007-04-25 | 沈睿 | Metal long rod pieces heat treatment quality continuous non-destructive testing equipment |
| CN203745341U (en) * | 2014-04-02 | 2014-07-30 | 川渝中烟工业有限责任公司 | Image recognition technology-based tobacco aromatic bead quality rapid-detection device |
| CN104259108A (en) * | 2014-10-22 | 2015-01-07 | 大连富地机械制造有限公司 | Automatic picking method and device for shaft parts |
| CN105290785A (en) * | 2015-12-01 | 2016-02-03 | 长沙长泰机器人有限公司 | Workpiece sorting and assembling system based on vision |
| CN205318747U (en) * | 2015-12-07 | 2016-06-15 | 重庆英耐基科技发展有限公司 | Automatic real device of instructing is produced to metaplasia |
| CN105806849A (en) * | 2016-04-08 | 2016-07-27 | 广东工业大学 | Automobile seat surface defect detection system based on machine vision as well as detection method |
| CN107176432A (en) * | 2017-06-15 | 2017-09-19 | 西安科技大学 | A kind of anchor pole foreign matter and belt tearing detecting system based on machine vision |
| CN107398428A (en) * | 2017-09-08 | 2017-11-28 | 深圳市柯莱顿光电科技有限公司 | A kind of picking sensor |
| CN109499908A (en) * | 2018-11-10 | 2019-03-22 | 东莞理工学院 | A kind of vision detection system for machine components |
| CN109738460A (en) * | 2019-01-28 | 2019-05-10 | 西京学院 | A kind of evaluation detection system for civil engineering structure visual defects |
| CN110497416A (en) * | 2019-09-16 | 2019-11-26 | 吉林科创电力有限公司 | A kind of trouble-shooter of switchgear |
Non-Patent Citations (3)
| Title |
|---|
| 姚金良: "一种基于连通分量的文本区域定位方法", 《模式识别与人工智能》 * |
| 徐春广等: "《回转体的结构光测量原理》", 31 January 2017, 国防工业出版社 * |
| 薄鑫涛等: "《实用热处理手册》", 30 April 2014, 国防工业出版社 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111558540A (en) * | 2020-05-27 | 2020-08-21 | 广东原点智能技术有限公司 | Quality inspection system of automobile crankshaft |
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Application publication date: 20200424 |