The multi-component coupling horizontal vibration modeling technology of the high-speed elevator and analysis of its influencing factors

电梯 振动 摄动(天文学) 结构工程 加速度 运动学 工程类 控制理论(社会学) 计算机科学 物理 声学 经典力学 控制(管理) 量子力学 人工智能
作者
Huifang Zhou,Shuyou Zhang,Lemiao Qiu,Zili Wang,Heng Li
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science [SAGE]
卷期号:236 (11): 5850-5869 被引量:13
标识
DOI:10.1177/09544062211063100
摘要

Horizontal vibration of a high-speed elevator can seriously influence the safety, stability, and ride comfort of the elevator during the operation. The construction of an accurate and robust dynamic model for horizontal vibration is the key to vibration control and suppression. In this article, the modeling and influencing factor analysis of the horizontal vibration of the high-speed elevator car are performed considering multi-component coupling. The rigid flexible coupling of the traction ropes and the elevator car system, the rigid irregularity perturbation generated by the manufacturing and installation errors of the guide rails, and the vibration inconsistency between the elevator car and car frame are considered in the modeling process. Based on the coupling system of the traction rope, elevator car, elevator car frame, guide rails, and rolling guide shoes, the kinematic horizontal vibration equation is established by using the generalized Hamilton’s principle. The solution of the horizontal vibration of the elevator car is derived based on the Galerkin method and MATLAB/Simulink software, and the influence of the perturbation frequency, irregularity perturbation type, and operating velocity on the horizontal vibration of the elevator car is analyzed. The KLK2 high-speed elevator is taken as a case study. Compared with the measured data, the mean absolute percentage error (MAPE) of the proposed model for maximum peak-to-peak (max [Formula: see text]) and [Formula: see text] peak-to-peak ([Formula: see text] [Formula: see text]) of the horizontal vibration acceleration is 6.08% and 5.16%, respectively, while the MAPE of a four degree-of-freedom model for the two is 16.74% and 7.35% and the MAPE of a distributed-parameter model for the two is 10.66% and 6.97%, respectively. The effectiveness of the proposed model is verified.
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