基于气液主动导向鞋的高速电梯水平振动智能控制

IF 1.2 4区工程技术 Q3 ENGINEERING, MECHANICAL

Mechanics & Industry Pub Date : 2021-01-01 DOI:10.1051/MECA/2020100

Qin He, P. Zhang, Shunxin Cao, Ruijun Zhang, Qing Zhang

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引用次数: 3

摘要

针对高速电梯实际运行中轿厢和轿架的振动与导轨粗糙度激励引起的水平振动不一致的问题，设计了气液主动导向鞋，建立了分离轿厢和轿架的8自由度高速电梯轿厢系统的水平振动模型。然后，通过实验验证了模型的正确性。在此基础上，设计了基于Mamdani模型的模糊神经网络智能减振控制器，并用MATLAB进行了仿真。结果表明，采用模糊神经网络控制方法后，振动加速度的均方根值、均值和最大值降低了55%以上，抑制效果优于BP神经网络控制。因此，本研究所设计的智能吸振控制器可以有效抑制高速电梯的水平振动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Intelligent control of horizontal vibration of high-speed elevator based on gas–liquid active guide shoes

Aiming at the inconsistency between the vibration of the car and the car frame in the actual operation of a high-speed elevator and the horizontal vibration caused by the roughness excitation of the guide rail, this study designs a gas–liquid active guide shoe and establishes a horizontal vibration model of the 8-DOF high-speed elevator car system separated from the car and the car frame. Then, the correctness of the model is verified by experiments. Based on this, a fuzzy neural network intelligent vibration reduction controller based on the Mamdani model is designed and simulated by MATLAB. The results show that the root mean square value, mean value, and maximum value of vibration acceleration are reduced by more than 55% after using the fuzzy neural network control method, and the suppression effect is better than that of BP neural network control. Therefore, the intelligent vibration absorption controller designed by this research institute can effectively suppress the horizontal vibration of high-speed elevators.

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来源期刊

Mechanics & Industry ENGINEERING, MECHANICAL-MECHANICS

CiteScore

2.80

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： An International Journal on Mechanical Sciences and Engineering Applications With papers from industry, Research and Development departments and academic institutions, this journal acts as an interface between research and industry, coordinating and disseminating scientific and technical mechanical research in relation to industrial activities. Targeted readers are technicians, engineers, executives, researchers, and teachers who are working in industrial companies as managers or in Research and Development departments, technical centres, laboratories, universities, technical and engineering schools. The journal is an AFM (Association Française de Mécanique) publication.