Condition-based Maintenance of Brake Pads and Tires in Shared Vehicles using Cloud-based Health monitoring and prognostics.

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Published Sep 4, 2023
Jeong Hae Lee Jaewook Oh Jeongwoo Lee Seungyoung Park Jihyeon Lee Namsu Kim

Abstract

Cloud-based prognostics and health management is a centralized method for monitoring the condition of individual shared vehicles and determining their maintenance schedules.
In this study, we focused on monitoring the condition of brake pads and tires, as these crucial components require frequent and regular maintenance for safety. We developed a data acquisition system to transmit data from acoustic and vibration sensors to the cloud server. Useful and efficient features were extracted and selected from time and frequency
domains to assess the degradation of brake pads and tires. Moreover, based on feature extraction using the KruskalWallis method, we confirmed that diagnosing brake pad conditions with support vector machines (SVM) provides consistent result for classification of sevierities.. Our preliminary results suggest that cloud-based condition
monitoring can be an effective approach to managing shared vehicles.

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Keywords

Condition Monitoring, Cloud-based Monitoring, Brake Pad Tire, CBM(Condition-based Maintenance)

References
JUNIOR, Mario Triches; GERGES, Samir NY; JORDAN, Roberto. Analysis of brake squeal noise using the finite element method: a parametric study. Applied Acoustics, 2008, 69.2: 147-162.

TABBAI, Yassine, et al. Friction and wear performance of disc brake pads and pyroelectric energy harvesting. International Journal of Precision Engineering and Manufacturing-Green Technology, 2021, 8: 487-500.

RAJESH, P. K., et al. Digital twin of an automotive brake pad for predictive maintenance. Procedia Computer Science, 2019, 165: 18-24.

SAWCZUK, Wojciech, et al. Evaluation of wear of disc brake friction linings and the variability of the friction coefficient on the basis of vibroacoustic signals. Sensors, 2021, 21.17: 5927.

JEGADEESHWARAN, R.; SUGUMARAN, V. Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines. Mechanical Systems and Signal Processing, 2015, 52: 436-446.

HU, Ruohui, et al. Deep subdomain generalisation network for health monitoring of high-speed train brake pads. Engineering Applications of Artificial Intelligence, 2022, 113: 104896.

XIE, M. S., et al. Brake pad taper wear on brake moan noise. International Journal of Automotive Technology, 2014, 15: 565-571.

XIONG, Yi; TUONONEN, Ari. A laser-based sensor system or tire tread deformation measurement. Measurement Science and Technology, 2014, 25.11: 115103.

YI, Jingang; LIANG, Hong. A PVDF-based deformation and motion sensor: Modeling and experiments. IEEE Sensors Journal, 2008, 8.4: 384-391.

SIEGEL, Joshua, et al. Smartphone-based vehicular tire pressure and condition monitoring. In: Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016: Volume 1. Springer International Publishing, 2018. p. 805-824.

Ling, Senlin, et al. "A comprehensive review of tirepavement noise: Generation mechanism, measurement methods, and quiet asphalt pavement." Journal of Cleaner Production 287 (2021): 125056.

LI, Tan. Influencing parameters on tire–pavement interaction noise: Review, experiments, and design considerations. Designs, 2018, 2.4: 38.

HO, Ka-Yee, et al. The effects of road surface and tyre deterioration on tyre/road noise emission. Applied Acoustics, 2013, 74.7: 921-925.

SANDBERG, Ulf, et al. The influence of tyre wear and ageing on tyre/road noise emission and rolling resistance. European Commission. DG research, AVL List GmbH, 2008.
Section
Special Session Papers