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Economical Auto Moment Limiter for Preventing Mobile Cargo Crane Overload

Title
Economical Auto Moment Limiter for Preventing Mobile Cargo Crane Overload
Authors
Noh, Soo-HoonLee, Yong-SeokKim, Sang-HoCho, Jae-SangHan, Chang-SooLee, SeungyeolLee, Dong-Eun
DGIST Authors
Kim, Sang-Ho; Lee, Seungyeol
Issue Date
2020-11
Citation
Sensors, 20(21), 6355
Type
Article
Article Type
Article
Author Keywords
auto moment limiterrollover preventioncost effectivenessmathematical model of cargo crane
Keywords
DYNAMIC-RESPONSESCONSTRUCTIONSAFETYMOTIONSYSTEM
ISSN
1424-8220
Abstract
This study presents a computational method called economical auto moment limiter (eAML) that prevents a mobile cargo crane from being overloaded. The eAML detects and controls, in real time, crane overload without using boom stroke sensors and load cells, which are expensive items inevitable to existing AML systems, hence, being competitive in price. It replaces these stroke sensors and load cells that are used for the crane overload measurement with a set of mathematical formula and control logics that calculates the lifting load being handled under crane operation and the maximum lifting load. By calculating iterative them using only a pressure sensor attached under the derrick cylinder and the boom angle sensor, the mathematical model identifies the maximum descendible angle of the boom. The control logic presents the control method for preventing the crane overload by using the descendible angle obtained by the mathematical model. Both the mathematical model and the control logic are validated by rigorous simulation experiments using MATLAB on two case instances each of which eAML is used and not used, while changing the pressures on the derrick cylinder and the boom angle. The effectiveness and validity of the method are confirmed by comparing the outputs obtained by the controlled experiments performed by using a 7.6 ton crane on top of SCS887 and a straight-type maritime heavy-duty crane along with eAML. The effects attributed to the load and the wind speed are quantified to verify the reliability of eAML under the changes in external variables. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/20.500.11750/12771
DOI
10.3390/s20216355
Publisher
MDPI AG
Related Researcher
Files:
There are no files associated with this item.
Collection:
Division of Intelligent Robotics1. Journal Articles


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