GA-Based Optimization Method for Mobile Crane Repositioning Route Planning

Gwak, Han-Seong; Lee, Hong-Chul; Choi, Byoung-Yoon; Yirong, Mi

doi:10.3390/app11136010

Cited by 7 publications

(3 citation statements)

References 22 publications

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“…Yoon et al [15], [16] conducted simulation testing to evaluate mobile crane lift operations using various software platforms. Besides, the latest research proposed optimization of crane operation to improve the performance of cranes [17]- [19]. While the other researchers are focusing on improving the LoRa protocol [20]-[23].…”

Section: Introductionmentioning

confidence: 99%

Crane monitoring system based on internet of things using long range

Jun

Hashim

Idris

et al. 2023

IJECE

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<span lang="EN-US">The four main causes of crane accidents are overturned, falls, mechanical failure, and contact with power lines. It is important to keep track of the crane’s health and condition as it is always too late when a failure of the crane was found. Any abrupt accidents will interrupt or delay the work progress and cause the operational costs to increase. Crane monitoring system is developed using long range (LoRa) technology due to its long range of detections making it suitable for monitoring machines that require large space including the dock area. It also consumes low power and is suitable for battery-operated systems. This paper discusses the design and development crane monitoring system using Arduino Uno together with NodeMCU ESP8266 as the hardware for this project. Temperature, power consumption, lifting activities, and total operating hours will be measured using appropriate sensors. The data will then be sent to the database where users can monitor each crane from a developed Android application using a mobile phone. This project allows users to view, monitor, and analyze real-time or past data in a graph or table view. Experimental results prove the proposed system is applicable and effective.</span>

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Section: Introductionmentioning

confidence: 99%

Crane monitoring system based on internet of things using long range

Jun

Hashim

Idris

et al. 2023

IJECE

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“…For example, in the selection of lifting equipment, crane operation simulation can be used for automatic selection [4], or an artificial neural network can be used to establish a predictive analysis framework for crane configuration selection [5]. In terms of lifting technology, the integral lifting technology is usually adopted for the lifting of steel structures [6][7][8][9][10], combined with genetic algorithms to derive the optimal working condition combination [11,12], optimize the position of the lifting points based on the principle of minimum potential energy [13], and use computer control to lift and lower during construction [14]. Structural monitoring can also be used to output real-time parameters such as deflection, stress, strain, wind, and temperature of the large-span spatial steel structure to ensure safety during the lifting process [15].…”

Section: Introductionmentioning

confidence: 99%

Time-Varying Mechanical Analysis of Long-Span Spatial Steel Structures Integral Lifting during Construction Process

Yang¹,

Du²,

Yao³

et al. 2023

Preprint

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Improper lifting measures of long-span spatial steel structures during construction process may delay the construction period and even cause safety accidents. Few studies on long-span spatial steel structures considered time-varying mechanical characteristic during construction process. In order to achieve safe and efficient installation in a long-span spatial steel structure, this research presents a time-varying mechanical analysis of the synchronous and asynchronous integral lifting and a single and interlaced point’s asynchronous integral lifting analysis method of a long-span spatial steel structure. The results showed that in the case of asynchronous lifting of single point, the displacement influence on other members is related to the distance. The closer the distance from the lifting point, the greater the influence. In asynchronous integral lifting, the lifting point with large lifting force is first installed to the specified position, and the lifting point with small lifting force is installed to the specified position.

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“…Now days, just few studies talking about safety technology, especially regarding LMI on mobile cranes. In [9], an analysis of the occurrence of mobile crane overturns has been carried out but the overall analysis is carried out on the causes of mobile crane overturns and is carried out in a simulation using the Genetic Algorithms (GA) method. The stability of the mobile crane has also been carried out by [10] during the lifting load process, but only focused on ground contact stability analysis.…”

Section: Introductionmentioning

confidence: 99%

Design of Prototype Load Moment Indicator on Mobile Crane using Microcontroller based on Lifting Load Chart

Fahruzi

Lamanele

Wati

2022

Inf. J. Ilm. Bid. Teknol. Inf. dan Komun.

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A load moment indicator (LMI) is an electronic device on heavy equipment cranes that can provide information and a warning system to operators in the event of an overload during the lifting load process. This tool has a very important role because it provides accessible information to the operator about the safe working load (SWL) that the crane can lift. Mobile cranes have a high accident potential when compared to tower cranes, and this is because mobile cranes have high mobility. In this paper, a prototype LMI has been made on a mobile crane based on a microcontroller that can provide value. The method used is an algorithm to find the closest value from the lifting load chart of a crane car. The programming algorithm is still manual, namely by equating and comparing boom crane conditions such as boom length, boom angle, and radius contained in the lifting load chart with the results of measuring boom crane conditions by sensors. The nearest value search algorithm follows the rules of how to read the mobile crane lifting load chart. The test results show that the sensors used to measure boom length, boom angle, and actual load each have a maximum relative error of 0.92%, 8%, and 4%, respectively. Meanwhile, to find the SWL value, the comparison scanning method can provide the SWL value according to the lifting load chart of the mobile crane. It can provide accurate information on whether the lifting load process is safe or overloaded.

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GA-Based Optimization Method for Mobile Crane Repositioning Route Planning

Cited by 7 publications

References 22 publications

Crane monitoring system based on internet of things using long range

Crane monitoring system based on internet of things using long range

Time-Varying Mechanical Analysis of Long-Span Spatial Steel Structures Integral Lifting during Construction Process

Design of Prototype Load Moment Indicator on Mobile Crane using Microcontroller based on Lifting Load Chart

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