journal article·2025-06-08Open access

Classification of Artificial Gear Damage by Angle Measurement Utilizing the Gear Wheel as a Material Measure

Yanik Koch, Florian Michael Becker-Dombrowsky, Eckhard Kirchner

Applied Sciences· Volume 15· Issue 12

Abstract

Gear condition monitoring is predominantly executed through the utilization of acceleration sensors positioned on the housing. However, recent advancements have identified measuring the instantaneous angular speed as a compelling alternative as it shortens the transmission path and therefore provides high-quality rotational angle information that can be used to increase damage prediction accuracy, particularly under transient operating conditions. Additionally, there are a variety of methodologies for integrating sensors into gears, which underscores the necessity for high-quality condition data. However, it should be noted that a significant amount of effort is required to successfully integrate these sensors into the rotating system. This publication uses a gear wheel sensor that employs the gear itself as a material measure to acquire rotational angle data and to deduce the damage condition. A magnetoresistive sensor is integrated into the gearbox housing radially facing a ferromagnetic gear and measures the rotational angle by the gear teeth. Various artificial tooth flank damages are applied to the pinion. The rotational angle is measured with the gear sensor, and the damage state is classified with a random forest classifier using established evaluations in the time and frequency domains. The tests are conducted under stationary operating conditions at an array of speed and torque levels. Additionally, they are performed under transient operating conditions, employing speed ramps at constant torque. The results of the classification are evaluated by means of classification accuracy and confusion matrices and compared with those obtained via a classic encoder at the pinion shaft and an acceleration sensor at the gearbox housing.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced machining processes and optimization · Advanced Measurement and Metrology Techniques · Gear and Bearing Dynamics Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Formerly Institute for Product Development and Machine Elements, Technical University of Darmstadt, 64287 Darmstadt, Germany

Institute for Product Development and Machine Elements, Technical University of Darmstadt, 64287 Darmstadt, Germany

References (24)

Show source-provided references
1. New procedure for gear fault detection and diagnosis using instantaneous angular speed10.1016/j.ymssp.2016.08.036 ↗
2. Impact of pulse time uncertainty on synchronous average: Statistical analysis and relevance to rotating machinery diagnosis10.1016/j.ymssp.2019.04.017 ↗
3. Toothwise health monitoring of planetary gearbox under time-varying speed condition based on rotating encoder signal10.1109/TIE.2021.3090713 ↗
4. Comparing Data Sources for Condition Monitoring Suitability10.1007/s10010-019-00331-y ↗
5. Felkaoui, A. (2017, January 9–11). Intelligent Gear Fault Diagnosis in Normal and Non-stationary Conditions Based on Instantaneous Angular Speed, Differential Evolution and Multi-class Support Vector Machine. Proceedings of the Signal Processing Applied to Rotating Machinery Diagnostics, (SIGPROMD’2017), Setif, Algeria.
6. Gear fault diagnosis based on angular measurements and support vector machines in normal and nonstationary conditions10.1007/978-3-319-20463-5_22 ↗
7. Use of transmission error for a quantitative estimation of root-crack severity in gears10.1016/j.ymssp.2022.108957 ↗
8. Sendlbeck, S., Fimpel, A., Siewerin, B., Otto, M., and Stahl, K. (2021). Condition monitoring of slow-speed gear wear using a transmission error-based approach with automated feature selection. Int. J. Progn. Health Manag., 12.10.36001/ijphm.2021.v12i2.3026 ↗
9. A review on the use of angle measurements in gear condition monitoring and fault detection10.1016/j.ymssp.2024.112254 ↗
10. Design of sensor integrating gears: Methodical development, integration and verification of an in-Situ MEMS sensor system10.1016/j.procir.2021.05.142 ↗
11. Derbel, F., and Strakosch, F. (2022, January 29–31). Integrated Sensor based Smart Diagnostic and Online Monitoring of Industrial Systems. Proceedings of the 2022 4th International Conference on Applied Automation and Industrial Diagnostics (ICAAID), Hail, Saudi Arabia.10.1109/ICAAID51067.2022.9799489 ↗
12. Rupprecht, B., Vogel-Heuser, B., Hujo, D., Vicaria, A., Knoll, E., Stahl, K., Ochs, M., and Brederlow, R. (2024, January 15–18). A Microcontroller Operating Strategy for (Micro-)Pitting and Temperature Increase Detection in Sensor-Integrating Gears Evaluated with Pre-recorded Sensor Data. Proceedings of the 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bangkok, Thailand.10.1109/IEEM62345.2024.10857258 ↗
13. Evaluation of vibration behavior at different sensing positions on gearboxes10.1007/s10010-024-00750-6 ↗
14. Bonaiti, L., Knoll, E., Otto, M., Gorla, C., and Stahl, K. (2022). The Effect of Sensor Integration on the Load Carrying Capacity of Gears. Machines, 10.10.3390/machines10100888 ↗
15. Feasibility study of measuring instantaneous angular speed of helical gears with magnetoresistive sensors10.1007/s10010-022-00590-2 ↗
16. Koch, Y. (2024). Gearbox Condition Monitoring Based On Angle Measurement Using A Gear As Material Measure. [Ph.D. Thesis, TU Darmstadt].
17. Koch, Y., Schäffner, M., de Orte, P., and Giebisch, S. (2025, March 27). Gearbox Condition Monitoring Based on Angle Measurement Using a Gear as Material Measure–Test Data. Available online: https://tudatalib.ulb.tu-darmstadt.de/submit?workspaceID=2652.
18. Direct least square fitting of ellipses10.1109/34.765658 ↗
19. de Dinechin, F., and Istoan, M. (2015, January 22–24). Hardware Implementations of Fixed-Point Atan2. Proceedings of the 2015 IEEE 22nd Symposium on Computer Arithmetic (ARITH), Lyon, France.10.1109/ARITH.2015.23 ↗
20. Koch, Y. (2025, March 27). Gearbox Condition Monitoring Based on Angle Measurement Using a Gear as Material Measure–Matlab Data. Available online: https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4240.
21. Random Forests10.1023/A:1010933404324 ↗
22. Transient feature identification from internal encoder signal for fault detection of planetary gearboxes under variable speed conditions10.1016/j.measurement.2020.108761 ↗
23. A review on sensor-integrating machine elements10.1002/adsr.202300113 ↗
24. Online instantaneous angular speed estimation from vibration on low-power embedded systems evaluated on a gas foil bearing use case10.1016/j.measen.2024.101600 ↗