Title :
Automatic tire pressure fault monitor using wavelet-based probability density estimation
Author :
Li, Li ; Wang, Fei-Yue ; Zhou, Qunzhi ; Shan, Guoling
Author_Institution :
Program for Adv. Res. in Complex Syst., Arizona Univ., Tucson, AZ, USA
Abstract :
This paper is devoted to the problem of tire pressure monitoring and tire fault detection. Based on wavelet package transformation, the density of the tire´s response vibration caused by the stochastic ground excitation is analyzed. Then using RBF neural networks to learn and classify the different types of vibration response, an automatic abnormal tire pressure detector is built. Theoretical analysis and simulation results show the I effectives of this new fault detector.
Keywords :
computerised monitoring; fault diagnosis; pressure sensors; probability; radial basis function networks; road vehicles; tyres; vibrations; wavelet transforms; RBF neural networks; automatic abnormal tire pressure detector; automatic tire pressure fault monitor; stochastic ground excitation; tire fault detection; tire response vibration density; wavelet based probability density estimation; wavelet package transformation; Automation; Computerized monitoring; Fault detection; Friction; Intelligent systems; Laboratories; Neural networks; Stochastic processes; Tires; Wavelet analysis;
Conference_Titel :
Intelligent Vehicles Symposium, 2003. Proceedings. IEEE
Print_ISBN :
0-7803-7848-2
DOI :
10.1109/IVS.2003.1212887
