基于分布根应力的局部动态齿轮啮合力测量

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Pan Zhang;Rui Wang;Liming Wang;Qiang Zeng;Wenbin Huang
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引用次数: 0

摘要

齿轮动啮合力的获取有助于研究齿轮系统的动态响应,也能指导齿轮传动系统的强度设计和减振设计。目前,齿轮动啮合力的获取主要基于物理模型的计算或仿真,在实际应用中缺乏有效的实验测量方法。针对传统应变/应力信号法的缺点,提出了一种基于分布应力的局部动态啮合力测量方法,克服了穿孔布线、载荷分布系数计算、非线性等缺点。将啮合力、啮合位置和单牙根应力之间的映射关系改为啮合力和分布牙根应力之间的映射关系。首先,建立一个实验平台,收集准静态条件下不同扭矩下的分布式齿根应力,用于训练径向基函数神经网络(RBFNN)模型。最后,利用训练好的模型测量任意工况下的动态啮合力。结果表明,测得的动态啮合力能有效反映平均啮合力水平,其动态行为与动态模拟结果相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measurement of Localized Dynamic Gear Meshing Forces Based on Distributed Root Stress
The acquisition of gear dynamic meshing force is helpful to study the dynamic response of gear system and can also guide the strength design and vibration reduction design of gear transmission system. At present, the acquisition of gear dynamic meshing force is mainly based on the calculation or simulation of physical model, and there is a lack of effective experimental measurement methods in practical application. In view of the shortcomings of the traditional strain/stress signal method, a local dynamic meshing force measurement method based on distributed stress is proposed, which overcomes the shortcomings of perforated wiring, calculation of load distribution coefficient, and nonlinearity. The mapping relationship between meshing force, meshing position, and single-tooth root stress is changed to the mapping relationship between meshing force and distributed tooth root stress. First, an experimental platform was built to collect distributed root stresses under different torques under quasistatic conditions, which was used to train radial basis function neural network (RBFNN) models. Finally, the trained model is used to measure the dynamic meshing force under any working condition. The results show that the measured dynamic meshing force can effectively reflect the average meshing force level, and the dynamic behavior is similar to the dynamic simulation results.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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