Performance optimization of road noise system based on convolutional neural network
2022-01-0370
03/29/2022
- Event
- Content
- Abstract: In view of the traditional road noise active control system being unable to adapt to different types of road excitations, a convolutional neural network method is designed to identify the road surface in advance, and the convergence factor of the road noise system algorithm is adaptively controlled by different road input to make the vehicle on different roads. To achieve the best noise reduction effect. This paper collects three typical road images, uses migration learning to train and test the network, and combines the recognition results with the road noise active control algorithm for joint simulation. The results show that the road surface can be recognized accurately by using convolutional neural network. According to different road types, by adjusting the algorithm convergence factor, the noise reduction effect of the vehicle can be effectively improved.
- Citation
- Shi, C., Zhu, Y., Sen, Z., Ge, X. et al., "Performance optimization of road noise system based on convolutional neural network," SAE Technical Paper 2022-01-0370, 2022, .