%0 Conference Paper %1 binanzer2023pitting %A Binanzer, Lisa %A Merkle, Lukas %A Dazer, Martin %A Nicola, Andreas %B Proceedings of the International Conference on Gears 2023 %C 13.-15.09.2023, Garching/Munich %D 2023 %K a_nicola antriebstechnik from:lisabinanzer gruebchen l_binanzer l_merkle m_dazer myown %P 97-108 %T Pitting Detection for Prognostics and Health Management in Gearbox Applications %X In critical industrial applications, gearboxes are already equipped with Condition Monitoring Systems (CMS) based on vibration sensors. However, these systems are only developing their full potential if damages can be detected early and if the accumulated sensor data can be assigned to a type of damage and a damage size. The aim of this investigation is a systematic evaluation of gear damages at different stages to use the CMS sensor data for Prognostics and Health Management (PHM). It is also the objective to evaluate different sensor concepts for data acquisition regarding damage detection in gearbox applications. To investigate the detection possibilities on the test bench, a single stage spur gearbox is developed. The test gearbox is used on a test bench, which is designed as electrical load unit consisting of two electric motors. The tooth flanks of the test gears are manufactured with artificial pitting dam-age with different sizes. The test gearbox is equipped with torque, speed and vibration sen-sors. The experiments are statistically designed by means of Design of Experiments (DOE). The factors pitting damage size, rotational speed, torque and viscosity are varied. This offers a valid basis for developing an empiric model that relates the damage size to the observed sen-sor data. Using machine learning approaches, the vibration signal data are analyzed. By means of anomaly detection, early damage stages can be identified during operation. A con-clusion from the acquired sensor data on the extent of damage is possible through the sys-tematic DOE. This enables PHM which allows a more reliable and sustainable operation of drivetrains in industrial plants and systems.

@inproceedings{binanzer2023pitting, abstract = {In critical industrial applications, gearboxes are already equipped with Condition Monitoring Systems (CMS) based on vibration sensors. However, these systems are only developing their full potential if damages can be detected early and if the accumulated sensor data can be assigned to a type of damage and a damage size. The aim of this investigation is a systematic evaluation of gear damages at different stages to use the CMS sensor data for Prognostics and Health Management (PHM). It is also the objective to evaluate different sensor concepts for data acquisition regarding damage detection in gearbox applications. To investigate the detection possibilities on the test bench, a single stage spur gearbox is developed. The test gearbox is used on a test bench, which is designed as electrical load unit consisting of two electric motors. The tooth flanks of the test gears are manufactured with artificial pitting dam-age with different sizes. The test gearbox is equipped with torque, speed and vibration sen-sors. The experiments are statistically designed by means of Design of Experiments (DOE). The factors pitting damage size, rotational speed, torque and viscosity are varied. This offers a valid basis for developing an empiric model that relates the damage size to the observed sen-sor data. Using machine learning approaches, the vibration signal data are analyzed. By means of anomaly detection, early damage stages can be identified during operation. A con-clusion from the acquired sensor data on the extent of damage is possible through the sys-tematic DOE. This enables PHM which allows a more reliable and sustainable operation of drivetrains in industrial plants and systems.}, added-at = {2023-09-20T14:50:50.000+0200}, address = {13.-15.09.2023, Garching/Munich}, author = {Binanzer, Lisa and Merkle, Lukas and Dazer, Martin and Nicola, Andreas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/250eaeda15626ae05d617f99acab5d607/ima-publ}, booktitle = {Proceedings of the International Conference on Gears 2023}, eventdate = {13.09.2023}, interhash = {f270743eff2f5c24b39256ed3e0c0897}, intrahash = {50eaeda15626ae05d617f99acab5d607}, keywords = {a_nicola antriebstechnik from:lisabinanzer gruebchen l_binanzer l_merkle m_dazer myown}, language = {en}, month = {9}, pages = {97-108}, timestamp = {2023-09-21T12:36:44.000+0200}, title = {Pitting Detection for Prognostics and Health Management in Gearbox Applications}, year = 2023 }