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- 저자 : Ruipeng Yang (검색결과 2 건)
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An Assessment Model of Owner Safety Management and its Application to Real Estate Projects
Ruipeng Tong,Chunlin Wu,Yang Li,Dongping Fang 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.5
Establishing a scientific and applicative safety management assessment system is crucial in improving safety performance oforganizations. Currently, there are few studies on owners’ safety management assessment systems. Based on the behavioral-basedsafety theory, this paper explores the links among safety management system, safety management behavior, safety management stateand safety performance, which constitute an assessment model that characterizes the features of safety management. It then proposesa safety management indicator system that applies to real estate owners. The applicability and effectiveness of the system is verifiedby a four-year case study with a real estate owner. Relationships between safety management system, safety management behavior,safety management state, and their main impacting factors are obtained. Results indicate that the assessment model makes safetyevaluation clearer and demonstrates significant correlations between different safety management issues. Owners’ safetymanagement system is established and implemented favorably under the safety management assessment indicator system. This paperpresents a profound understanding of safety management assessment, in which the safety management assessment model and theindicator system is applied effectively in practice. To improve safety management level, specific theoretical and practicalimplications lead researchers and practitioners to pay more attention to safety management assessment.
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Remote control system based on the internet and machine vision for tracked vehicles
Shuai Wang,Shubing Zhang,Ruoding Ma,E. Jin,Xinhui Liu,He Tian,Ruipeng Yang 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.3
A remote control system based on the Internet and machine vision is designed in this study for tracked vehicles. The system consists of remote monitoring, remote control, and visual navigation subsystems. The on-board computer receives control commands issued by the monitoring center and controls the speed and steering angle of the tracked vehicles. The front camera collects navigation line information, and the collected image is processed by filtering, gray processing, binarization processing, and interference elimination to obtain the center point coordinates of the navigation line. Proportional-integral-derivative (PID), fuzzy PID, and neural network control algorithms are compared based on the distance and angle deviations of the preview point to control the operation of tracked vehicles through simulation. The Internet remote control system with the fuzzy PID control algorithm is then tested on a tracked vehicle. Experimental results indicate that the trajectory of the tracked vehicle fits the navigation path well.
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