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An automatic alignment method for discharge arm of mobile crushing station based on binocular vision and fuzzy control
Guan,Wei1; Wang,Shuai2; Chen,Zeren1; Wang,Guoqiang1; Huang,Tingting1; Liu,Zhengbin1; Guo,Jianbo1
2023-04
Source PublicationTransactions of the Institute of Measurement and Control
ISSN0142-3312
Volume45Issue:6Pages:1001-1020
Abstract

The mobile crushing station is one of the main equipment of the semi-continuous open-pit mining system. The discharge arm and the receiving equipment are manually aligned, which has the problems of long alignment time and low alignment accuracy, which affects the working efficiency of the mining system. According to the development and application of space rendezvous and docking technology at home and abroad, the advantages and disadvantages of different measurement methods are compared and analysed, and the method of applying binocular measurement technology to system positioning in the automatic alignment system of the discharge arm is determined. There are three movements in the mechanical part of the designed discharge arm alignment control system, including the rotary motion of the visual measurement mechanism and the horizontal rotation and telescopic motion of the discharge arm. According to the kinematic analysis and binocular vision measurement theory, the deviation model of the alignment control of the discharge arm is established. A binocular vision measurement and localization method based on the combination of stereo calibration and template matching is proposed, which achieves surprising measurement accuracy. An automatic alignment method of the discharge arm of the mobile crushing station is proposed based on the binocular vision and fuzzy control method. Its validity is verified by simulation and experiment. The strategy of motion decomposition is applied to the alignment system to avoid unnecessary motion of the discharge arm. The research results all show that the alignment method can achieve the angle deviation within ±0.5 degrees, the distance deviation within ±15 mm, and the test alignment time is about 5 minutes, which is better than other alignment control models; the alignment accuracy and the alignment time are improved by more than 50%. The method can control the discharge arm to complete the alignment task quickly and smoothly, which lays a foundation for the further automatic research of the discharge arm.

KeywordAlignment Binocular Vision Discharge Arm Fuzzy Control Mobile Crushing Station
DOI10.1177/01423312221136992
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Instruments & Instrumentation
WOS IDWOS:000895473800001
PublisherSAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
Scopus ID2-s2.0-85144454758
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Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorWang,Shuai; Chen,Zeren
Affiliation1.School of Mechanical and Aerospace Engineering,Jilin University,China
2.State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering,University of Macau,China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Guan,Wei,Wang,Shuai,Chen,Zeren,et al. An automatic alignment method for discharge arm of mobile crushing station based on binocular vision and fuzzy control[J]. Transactions of the Institute of Measurement and Control, 2023, 45(6), 1001-1020.
APA Guan,Wei., Wang,Shuai., Chen,Zeren., Wang,Guoqiang., Huang,Tingting., Liu,Zhengbin., & Guo,Jianbo (2023). An automatic alignment method for discharge arm of mobile crushing station based on binocular vision and fuzzy control. Transactions of the Institute of Measurement and Control, 45(6), 1001-1020.
MLA Guan,Wei,et al."An automatic alignment method for discharge arm of mobile crushing station based on binocular vision and fuzzy control".Transactions of the Institute of Measurement and Control 45.6(2023):1001-1020.
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