Philipp Thomaneck , Marina Terlau , Ronald Eberl , Axel von Freyberg , Andreas Fischer
{"title":"In-process analysis of the dynamic deformation of a bionic lightweight gear","authors":"Philipp Thomaneck , Marina Terlau , Ronald Eberl , Axel von Freyberg , Andreas Fischer","doi":"10.1016/j.ymssp.2025.112446","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"228 ","pages":"Article 112446"},"PeriodicalIF":7.9000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechanical Systems and Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0888327025001475","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
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.
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