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.

Authors

Institutions

Publication Details

Journal
IEEE Sensors Journal
Published
2025-01-16
DOI
https://doi.org/10.1109/jsen.2025.3528004
Primary Topic
Gear and Bearing Dynamics Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Measurement of Localized Dynamic Gear Meshing Forces Based on Distributed Root Stress

Pan Zhang, Wenbing Huang, Qiang Zeng, Rui Wang et al.
2 links
IEEE Sensors Journal
Gear and Bearing Dynamics Analysis
article

Measurement of Localized Dynamic Gear Meshing Forces Based on Distributed Root Stress

Pan Zhang, Wenbing Huang, Qiang Zeng, Rui Wang, Liming Wang
article en

Abstract

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.

IEEE Sensors JournalVol. 25(5)
Chongqing University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 99%
Gear and Bearing Dynamics Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.