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Article type: Research Article
Authors: Lu, Xiangyanga; * | Li, Hengyib | Li, Xiaoquana | Xu, Juncaic; d; *
Affiliations: [a] School of Electrical and Information Engineering, Zhongyuan University of Technology, Zhengzhou, China | [b] Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan | [c] Department of Civil Engineering, Case Western Reserve University, Cleveland, OH, USA | [d] Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education, Chongqing Jiaotong University, Chongqing, China
Correspondence: [*] Corresponding author. Juncai Xu, Department of Civil Engineering, Case Western Reserve University, Cleveland, OH 44106, USA. E-mail: [email protected] and Xiangyang Lu, School of Electrical and Information Engineering, Zhongyuan University of Technology, Zhengzhou, China.
Abstract: The security of a train becomes a more critical issue as the train’s speed and the complexity of the railway conditions increases. It is especially true when the train runs on a curved radius rail when the lateral force between the train and the rail is less stable. The rail’s side grinding is a significant problem that affects the train’s safety, especially when the train passes through small radial sections in mountainous areas. The intelligent rail lubrication system is critical to enhancing rails’ safety and efficiency and reducing grease pollution along rail lines. This system is modeled with a force analysis of train curve motion and numerical simulation of wear power. The lubrication system is constructed with hardware and software. Based on fuzzy group analysis, this system and the adaptive Proportional Integration Differential (PID) controller is presented to improve the lubricative effects. The system test results show that the quality of lubrication control using this system is efficacious; the control convergence is more reliable than the conventional PID controller.
Keywords: Security, curve rail, adaptive PID, lubrication system
DOI: 10.3233/JIFS-201398
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1137-1146, 2021
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