Real Time Identification and Classification of Road Surface with Neural Network 931344
Two methods have been developed for real time identification and classification of the roughness pattern of road surfaces using the neural network. These methods are directly available both for semi-active and active vibration controls of cars. Accelerations of the rear wheel axis under the suspension are used as the input data for real time identification. The neural network which has acquired the informations of the seven typical roughness patterns is used for real time classification of actual road surfaces during driving. Validity and usefulness of these methods are verified by simulation.
Citation: Shiotsuka, T., Nagamatsu, A., and Yoshida, K., "Real Time Identification and Classification of Road Surface with Neural Network," SAE Technical Paper 931344, 1993, https://doi.org/10.4271/931344. Download Citation
Author(s):
Toshinari Shiotsuka, Akio Nagamatsu, Kazuo Yoshida
Affiliated:
Tokyo Institute of Technology, Keio Univ.
Pages: 7
Event:
Noise & Vibration Conference & Exposition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
Proceedings of the 1993 Noise and Vibration Conference-P-264
Related Topics:
Neural networks
Identification
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