In-process analysis of the dynamic deformation of a bionic lightweight gear

IF 7.9 1区 工程技术 Q1 ENGINEERING, MECHANICAL Mechanical Systems and Signal Processing Pub Date : 2025-02-19 DOI:10.1016/j.ymssp.2025.112446
Philipp Thomaneck , Marina Terlau , Ronald Eberl , Axel von Freyberg , Andreas Fischer
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Abstract

Lightweight gears enable the weight reduction of frequently used mechanical engineering parts, but require an in-depth understanding of their mechanical load capacity. Therefore, the dynamic load behavior of a holistic bionic lightweight gear with a weight reduction of 61 % compared to a conventional solid gear is investigated. An in-process measuring system consisting of strain gauges and a telemetry system for recording the strain condition during dynamic tooth meshing is used. Based on finite element simulation data, four gear positions with biaxial strain fields on the gear surface were identified to position and align the strain gauges with high sensitivity. As a result, the sensors are capable of resolving the local material load during the gear revolutions over time, since the experimental results agree with theoretical considerations. For instance, regions of single-tooth contact and double-tooth contact are detectable during meshing, as well as the load due the meshing of a neighboring tooth. Furthermore, the observed gear deformations for the different transmission torques are proven to be elastic, and a biaxial strain measurement is demonstrated and verified by the simulation data. Thus, the in-process deformation behavior of a holistic bionic gear can be monitored over time, opening up structural health monitoring applications in future.
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来源期刊
Mechanical Systems and Signal Processing
Mechanical Systems and Signal Processing 工程技术-工程:机械
CiteScore
14.80
自引率
13.10%
发文量
1183
审稿时长
5.4 months
期刊介绍: Journal Name: Mechanical Systems and Signal Processing (MSSP) Interdisciplinary Focus: Mechanical, Aerospace, and Civil Engineering Purpose:Reporting scientific advancements of the highest quality Arising from new techniques in sensing, instrumentation, signal processing, modelling, and control of dynamic systems
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