CN104624519A - Material and shape-based scraped car part sorting method and system - Google Patents
Material and shape-based scraped car part sorting method and system Download PDFInfo
- Publication number
- CN104624519A CN104624519A CN201410850023.1A CN201410850023A CN104624519A CN 104624519 A CN104624519 A CN 104624519A CN 201410850023 A CN201410850023 A CN 201410850023A CN 104624519 A CN104624519 A CN 104624519A
- Authority
- CN
- China
- Prior art keywords
- sorting
- shape
- parts
- abandoned car
- chosen
- 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.)
- Granted
Links
Landscapes
- Analysing Materials By The Use Of Radiation (AREA)
- Sorting Of Articles (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a material and shape-based scraped car part sorting method and system. The material and shape-based scraped car part sorting method and system are characterized by achieving rapid automatic recognition, sorting and logic classification of car parts and facilitating the realization of braking and intelligence of the whole dismantling process of a scraped car. The sorting system disclosed by the invention comprises an X-ray detection-based material sorting system and a part size feature-based shape sorting system, wherein scraped car parts are sequentially selected according to material and shape features. The part material X ray data sorting system is used for sorting the parts into nonmetal parts and metal parts according to materials, then the metal parts are continuously selected so that steel parts, aluminum alloy parts, copper parts, magnesium alloy parts and other parts are respectively obtained. Different scraped car parts are obtained based on part size and shape data and image recognition-based intelligent sorting. According to the material and shape-based scraped car part sorting method and system, the intelligent selection of the scraped car parts is realized, and the production efficiency is improved.
Description
Technical field
The present invention relates to abandoned car and disassemble recovery, belong to recycling economy technical field.A kind of automatic sorting method and system based on material and shape facility logic analysis disclosed by the invention, achieves the intellectuality of abandoned car part, the efficient separation of automation.
Background technology
China's automobile volume of production and marketing and automobile pollution sharply increase, and abandoned car quantity presents blowout formula and increases.Within 2014, China's abandoned car amount reaches 4,000,000, estimates that the year two thousand twenty reaches 8,000,000.It is extremely urgent that abandoned car disassembles recycling.China's abandoned car is disassembled recovery technology and is mainly manually disassembled and sorting, and efficiency is low, and operating environment is poor, and labour intensity is large, and it is high that rate falsely dropped by material and part, there is certain potential safety hazard.
Disassembling recovery technology level for improving China's abandoned car, being badly in need of the abandoned car componentselected technology that exploitation is advanced.The present invention discloses the separation system based on abandoned car part material and shape, efficiently can automatically sort metal and non-metal workpiece, and metal parts can be classified.
Summary of the invention
Separation system disclosed by the invention comprises based on material X-ray separation system with based on accessory size shape sorting system, and abandoned car part carries out sorting by material and shape facility successively.Based on the separation system of part material X-ray data, be first non-metal workpiece and metal parts by part by quality of material separator, judge that TNM >=90% is as non-metal workpiece, judge that TM > 10% is as metal parts; Then sorting is carried out to metal parts, judge that TFe >=70% is as steel-iron components; Judge that TAl >=70% is as aluminum alloy part; Judge that TCu >=30% is as copper part; Judge that TMg >=70% is as magnesium alloy parts; If above condition does not meet, be judged to be other part.Based on the intelligent sorting of accessory size shape data and image recognition, ccd video camera is adopted to gather part shape feature data, and by after machine vision process with the comparison of auto parts database, when character shape data and reference part error σ > 10%, continue retrieval contrast, when σ≤10%, be judged to be this reference part.Present invention achieves the sorting of abandoned car part intelligence, improve production efficiency.
A kind of abandoned car componentselected method and system based on material and shape provided by the invention comprises the following steps:
(1) conveyer belt abandoned car part being placed in separation system carries out X-ray detection material;
(2) sorting is carried out to abandoned car part, TNM >=90% according to material characteristic, be chosen to be nonmetallic materials part; TM > 10%, is chosen to be metal material part;
(3) metal material part is carried out x-ray fluorescence analysis, TFe >=70%, be chosen to be steel-iron components; TAl >=70%, is chosen to be aluminum alloy part; TCu >=30%, is chosen to be copper or copper alloy parts; TMg >=70%, is chosen to be magnesium alloy parts; Otherwise be chosen to be other metal material part;
(4) ccd video camera is adopted to carry out picture catching to often kind of metal parts and carry out Computer Image Processing obtaining character shape data, then logic analysis is carried out with components database, if σ > 10%, then continue retrieval coupling, until error σ≤10%, be chosen to be this reference part; If all search complete σ > 10%, be chosen to be unknown part.
Part shape of the present invention comprises cuboid, annular etc., but is not limited thereto.
Accompanying drawing explanation
Fig. 1 abandoned car part automatic sorting system.
1-X-ray detector; 2-character shape data Acquire and process unit; 3-sorting connecting gear; 4-the part that sub-elects; P1-metal and non-metallic material separation unit; P2-iron, aluminium, copper, magnesium quality of material separator unit; P3-shape facility separation unit.
Fig. 2 abandoned car part image identifying logical flow chart
Detailed description of the invention
Below in conjunction with embodiment, the invention will be further described, but the present invention is not only confined to following examples.
See Fig. 1, be abandoned car part automatic sorting system, X-ray detector is the spectrometer collecting chemical element characteristic X-ray contained by part material, and the characteristic X-ray collected according to this detector can carry out quality of material separator.Character shape data Acquire and process unit comprises CCD camera and CPU, can carry out shape data collection, computation and analysis.Sorting transmission mechanism is the mechanical device of the transport of abandoned car part and sorting, comprises conveyer belt, manipulator, various motors etc.
Embodiment 1
(1) detect by the material of x-ray fluorescence analysis to certain abandoned car part that conveying is come in, the chemical element composition and the component content data that obtain this abandoned car part are: TFe=94.7%, total carbon content (TC)=3.0%, total Fe content (TMn)=1.1%, TM=95.8%, therefore meet the condition of total metal content TM >=10%, this part selected is metal parts and is delivered on next step sorting line of metal parts.The chemical composition of further this metal parts of analysis and content data, by calculating and comparing, detect TFe=94.7%>70% in data, and this part steel-iron components selected is also delivered on next step sorting line of steel-iron components;
(2) this steel-iron components image is gathered with ccd video camera, the image transmitting collected to Computerized image processing system is carried out part length, width, highly, diameter, thickness shape characteristic extract, its characteristic is: cuboid part all directions size (length 47.2cm, width 34.5cm, height 11.6cm), perforate coordinate (11.4,19.0), aperture 4.1cm;
(3) reference part shape feature data in above-mentioned part shape feature data and database are compared, calculate the error amount σ of each character shape data; The character shape data of reference part cylinder head is: cuboid part all directions size (length 48cm, width 34cm, height 12cm), position of opening coordinate (12,20), aperture 4cm;
(4) be respectively with the error amount comparing each character shape data obtained through calculating: error in length is σ
length=1.7%, width error is σ
width=1.4%, height error is σ
highly=3.6%, perforate error of coordinate is σ
perforate coordinate=5%, open pore size is σ
aperture=2.5%.According to the decision condition preset, each character shape data all meet σ≤10% with the error amount σ of reference part shape feature data, this steel-iron components selected is cylinder head.
Embodiment 2
(1) detect by the material of x-ray fluorescence analysis to certain abandoned car part that conveying is come in, the chemical element composition and the component content data that obtain this abandoned car part are: TAl=88.5%, TCu=4.0%, total silicone content (TSi)=7.5%, TM=92.5%; Therefore meet the condition of total metal content TM >=10%, this part selected is metal parts and is delivered on next step sorting line of metal parts.The chemical composition of further this metal parts of analysis and content data, by calculating and comparing, detect TAl=88.5%>70% in data, and this part selected is aluminum alloy part and is delivered on next step sorting line of aluminum alloy part.
(2) this aluminum alloy part image is gathered with ccd video camera, the image transmitting collected to Computerized image processing system is carried out the extraction of part shape feature data, its characteristic is: part shape (annular), part all directions size (external diameter 35.5cm, internal diameter 16cm, thickness 28.7cm), number of aperture 5, aperture 4cm and part image.
(3) reference part shape feature data in above-mentioned part shape feature data and database are compared, calculate the error amount σ of each character shape data; The character shape data of reference part wheel hub is: part shape (annular), part all directions size (external diameter 35.2cm, internal diameter 16.4cm, thickness 28cm), number of aperture 5, aperture=4.2cm;
(4) be respectively with the error amount comparing each character shape data obtained through calculating: detector for outer diameter error is σ
external diameter=0.8%, internal diameter error is σ
internal diameter=2.5%, width error is σ
width=2.5%, number of aperture error is σ
number of aperture=0, open pore size is σ
aperture=4.7%.According to the decision condition preset, each character shape data all meet σ≤10% with the error amount σ of reference part shape feature data, this aluminum alloy part selected is wheel hub.
Embodiment 3
(1) detect by the material of x-ray fluorescence analysis to certain abandoned car part that conveying is come in, the chemical element composition and the component content data that obtain this abandoned car part are: TCu=71.0%, TAl=5.5%, TFe=2.0%, TMn=3.0%, total Zn content (TZn)=11.0%, total silicone content (TSi)=2.5%, can obtain TM=92.5%; Therefore meet the condition of total metal content TM >=10%, this part selected is metal parts and is delivered on next step sorting line of metal parts.The chemical composition of further this metal parts of analysis and content data, by calculating and comparing, detect TCu=71.0>30% in data, and this part selected is copper alloy parts and is delivered on next step sorting line of copper alloy parts.
(2) this copper alloy parts image is gathered with ccd video camera, the image transmitting collected to Computerized image processing system is carried out the extraction of part shape feature data, its characteristic is: part shape (annular), part all directions size (external diameter 12.2cm, internal diameter 9.4cm, thickness 2.9cm).
(3) reference part shape feature data in above-mentioned part shape feature data and database are compared, calculate the error amount σ of each character shape data; The character shape data of reference part synchronization device cone ring is: part shape (annular), part all directions size (external diameter 12.0cm, internal diameter 9.0cm, thickness 3.0cm).
(4) be respectively with the error amount comparing each character shape data obtained through calculating: detector for outer diameter error is σ
external diameter=1.7%, internal diameter error is σ
internal diameter=4.4%, thickness error is σ
thickness=3.3%.According to the decision condition preset, each character shape data all meet σ≤10% with the error amount σ of reference part shape feature data, this aluminium copper part selected is synchronization device cone ring.
Present invention achieves the intelligent sorting fast of abandoned car, achieve by material and shape sorting, not only increase sharpness of separation, reduce the rate of falsely dropping, and protect part integrity, improve recycle value.The present invention can the abandoned car part of any shape of sorting, does not limit to the annular in embodiment and cuboid, only needs the character shape data input database of auto parts just can compare sorting.
Claims (6)
1. the abandoned car componentselected method based on material and shape, it is characterized in that: first carry out a sorting according to the abandoned car part material characteristic of X-ray detection instrument collection, then carry out secondary sorting according to the abandoned car part shape feature data of CCD camera acquisition process.
2. a kind of abandoned car componentselected method based on material and shape according to claim 1, it is characterized in that: a sorting is quality of material separator, be judged to be non-metal workpiece as nonmetal total amount (TNM) >=90% that X-ray detection instrument calculates; Metal parts is judged to be as total metal content (TM) > 10%; For metal parts, time total iron (TFe) >=70%, be judged to be steel-iron components; Aluminum alloy part is judged to be time whole alumiunum amount (TAl) >=70%; Copper part is judged to be time total copper amount (TCu) >=30%; Magnesium alloy parts is judged to be time total magnesium amount (TMg) >=70%; If above condition does not meet, be judged to be other part.
3. a kind of abandoned car componentselected method based on material and shape according to claim 1, it is characterized in that: secondary sorting is shape sorting, ccd video camera is adopted to gather part shape feature data, and by after machine vision process with the comparison of auto parts database, when all character shape datas and reference part error σ > 10%, continue retrieval contrast, when σ≤10%, be judged to be this reference part.
4. a kind of abandoned car componentselected method based on material and shape according to claim 1, it is characterized in that, described method for separating comprises following steps:
(1) conveyer belt abandoned car part being placed in separation system carries out the detection of X-ray material;
(2) sorting is carried out to abandoned car part, TNM >=90% according to material characteristic, be chosen to be nonmetallic materials part; TM > 10%, is chosen to be metal material part;
(3) metal material part is carried out x-ray fluorescence analysis, TFe >=70%, be chosen to be steel-iron components; TAl >=70%, is chosen to be aluminum alloy part; TCu >=30%, is chosen to be copper or copper alloy parts; TMg >=70%, is chosen to be magnesium alloy parts; Otherwise be chosen to be other metal material part;
(4) ccd video camera is adopted to carry out picture catching to often kind of metal parts and carry out Computer Image Processing obtaining character shape data, then logic analysis is carried out with components database, if σ > 10%, then continue retrieval coupling, until error σ≤10%, be chosen to be this reference part; If all search complete σ > 10%, be chosen to be unknown part.
5. the abandoned car componentselected system based on material and shape, described separation system comprises X-ray detection instrument, ccd video camera, CPU, sorting transmission mechanism, wherein, separation unit is provided with in described CPU, it is characterized in that, described separation unit comprises a separation unit and secondary sorting unit, a described separation unit carries out a sorting according to the abandoned car part material characteristic of X-ray detection instrument collection, and described secondary sorting unit carries out secondary sorting according to the abandoned car part shape feature data of CCD camera acquisition process.
6. the abandoned car componentselected system based on material and shape according to claim 1, is characterized in that, described sorting transmission mechanism is the mechanical device of the transport of abandoned car part and sorting, comprises conveyer belt, manipulator and motor etc.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410850023.1A CN104624519B (en) | 2014-12-31 | 2014-12-31 | A kind of abandoned car componentselected method and system based on material and shape |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410850023.1A CN104624519B (en) | 2014-12-31 | 2014-12-31 | A kind of abandoned car componentselected method and system based on material and shape |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104624519A true CN104624519A (en) | 2015-05-20 |
| CN104624519B CN104624519B (en) | 2017-07-18 |
Family
ID=53204034
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410850023.1A Active CN104624519B (en) | 2014-12-31 | 2014-12-31 | A kind of abandoned car componentselected method and system based on material and shape |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104624519B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105944978A (en) * | 2016-05-16 | 2016-09-21 | 武汉理工大学 | Inclined plate type stainless steel broken material pneumatic sorting device and method |
| CN107488798A (en) * | 2017-07-12 | 2017-12-19 | 华东理工大学 | A kind of manufacture method of environment-friendly aluminum alloy Automobile Plate |
| CN107737735A (en) * | 2017-09-30 | 2018-02-27 | 沈阳知行科技有限公司 | The fusion of abandoned car recovery metal perceives online separation system and method for separating |
| CN108136445A (en) * | 2015-07-16 | 2018-06-08 | Uhv技术股份有限公司 | Materials sorting system |
| CN109570057A (en) * | 2017-12-07 | 2019-04-05 | 贺州学院 | Tableware automatic letter sorting machine |
| CN110201899A (en) * | 2019-04-19 | 2019-09-06 | 深圳市金洲精工科技股份有限公司 | It is a kind of for sorting the method and device of hard alloy cutter |
| CN110788024A (en) * | 2019-11-13 | 2020-02-14 | 苏州大成有方数据科技有限公司 | Automatic sorting system for intelligent manufacturing and working method thereof |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0815493A (en) * | 1994-06-29 | 1996-01-19 | Nippon Isotope Kyokai | Waste disposal method |
| JPH10216651A (en) * | 1997-02-13 | 1998-08-18 | Ishikawajima Harima Heavy Ind Co Ltd | Metal sorting method and metal sorter using the method |
| CN102892521A (en) * | 2010-03-23 | 2013-01-23 | 技术资源有限公司 | Sorting mined material on the basis of two or more properties of material |
| CN103052451A (en) * | 2010-08-04 | 2013-04-17 | 技术资源有限公司 | Sorting mined material |
-
2014
- 2014-12-31 CN CN201410850023.1A patent/CN104624519B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0815493A (en) * | 1994-06-29 | 1996-01-19 | Nippon Isotope Kyokai | Waste disposal method |
| JPH10216651A (en) * | 1997-02-13 | 1998-08-18 | Ishikawajima Harima Heavy Ind Co Ltd | Metal sorting method and metal sorter using the method |
| CN102892521A (en) * | 2010-03-23 | 2013-01-23 | 技术资源有限公司 | Sorting mined material on the basis of two or more properties of material |
| CN103052451A (en) * | 2010-08-04 | 2013-04-17 | 技术资源有限公司 | Sorting mined material |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108136445A (en) * | 2015-07-16 | 2018-06-08 | Uhv技术股份有限公司 | Materials sorting system |
| CN105944978A (en) * | 2016-05-16 | 2016-09-21 | 武汉理工大学 | Inclined plate type stainless steel broken material pneumatic sorting device and method |
| CN107488798A (en) * | 2017-07-12 | 2017-12-19 | 华东理工大学 | A kind of manufacture method of environment-friendly aluminum alloy Automobile Plate |
| CN107737735A (en) * | 2017-09-30 | 2018-02-27 | 沈阳知行科技有限公司 | The fusion of abandoned car recovery metal perceives online separation system and method for separating |
| CN109570057A (en) * | 2017-12-07 | 2019-04-05 | 贺州学院 | Tableware automatic letter sorting machine |
| CN110201899A (en) * | 2019-04-19 | 2019-09-06 | 深圳市金洲精工科技股份有限公司 | It is a kind of for sorting the method and device of hard alloy cutter |
| CN110201899B (en) * | 2019-04-19 | 2021-11-23 | 深圳市金洲精工科技股份有限公司 | Method and device for sorting hard alloy cutters |
| CN110788024A (en) * | 2019-11-13 | 2020-02-14 | 苏州大成有方数据科技有限公司 | Automatic sorting system for intelligent manufacturing and working method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104624519B (en) | 2017-07-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104624519A (en) | Material and shape-based scraped car part sorting method and system | |
| Mneymneh et al. | Automated hardhat detection for construction safety applications | |
| CN103984951B (en) | A kind of Magnetic testing defect inspection method and system | |
| Gundupalli et al. | Multi-material classification of dry recyclables from municipal solid waste based on thermal imaging | |
| CN110532564B (en) | On-line identification method for application layer protocol based on CNN and LSTM hybrid model | |
| CN102682305A (en) | Automatic screening system and automatic screening method using thin-prep cytology test | |
| CN104156951B (en) | A kind of white blood cell detection method for BAL fluid smear | |
| CN109101976B (en) | Method for detecting surface defects of arc-extinguishing grid plate | |
| CN104951553B (en) | A kind of accurate content of data processing is collected and data mining platform and its implementation | |
| CN103984939A (en) | Sample visible component classification method and system | |
| CN106126680A (en) | A kind of video image reconnaissance method and system | |
| CN112614105B (en) | Depth network-based 3D point cloud welding spot defect detection method | |
| CN105447514A (en) | Metal identification method based on information entropy | |
| CN101639941B (en) | Method for extracting binuclear lymphocyte accurately and quickly in CB method micronucleated cell image | |
| CN113012179A (en) | Coal dust image identification method for coal mine underground explosion-proof detection | |
| Liu et al. | Image-based method for measuring pellet size distribution in the stable area of disc pelletizer | |
| CN112733882A (en) | Cylinder sleeve surface defect detection method, system and equipment based on deep learning | |
| Hu et al. | Accurate identification strategy of coal and gangue using infrared imaging technology combined with convolutional neural network | |
| CN116452506A (en) | Underground gangue intelligent visual identification and separation method based on machine learning | |
| Devereux et al. | A new approach for crack detection and sizing in nuclear reactor cores | |
| CN110889435A (en) | Insulator evaluation classification method and device based on infrared image | |
| Hassan et al. | Cascaded structure tensor framework for robust identification of heavily occluded baggage items from multi-vendor X-ray scans | |
| CN113566704A (en) | Bearing assembly ball size detection method based on machine vision | |
| AT518767A2 (en) | Coin recognition and removal from a material stream | |
| CN105404682A (en) | Digital image content based book retrieval method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |