This paper presents a beam width control for a directional audible sound system using an optimization method that combines a neural network with a search algorithm. A uniform linear array, composed of 64 ultrasonic transducers with different weightings, produces the directional audible sound. A novel method is proposed for the control of the beam width of this directional audible sound system. A back-propagationneural network is trained to simulate the feasible domain of the optimal weightings. Then, a search algorithm searches for the optimal weightings in the feasible domain simulated by the neural network. The directivity of the audible sound beam has been investigated through simulations and real-time experiments in this study. The results show that the optimization method proposed in the paper can effectively control the beam width of the directional audible sound system. Therefore, the good directivity of the audible sound beam can be achieved. The novel contributions of the paper are summarized as follows: (1) A novel method using an optimization method that combines a neural network with a search algorithm is proposed to control the beam width of a directional audible sound system. However, the method presented in the literature uses Chebyshev method, which can be found in the Matlab function. (2) The directivity of the directional audible sound system has been significantly improved compared with that in the literature. (3) The advantage of the directional audible sound system proposed in this paper is that the directivity can be controlled in the x-y plane, whereas the examples presented in the literature only allow control of the directivity on the x-axis. (4) Good performance is demonstrated for the proposed method through simulations and real-time experiments in a Toyota Camry 2.5G vehicle cabin. However, most of the literature focuses only on simulations.
|Number of pages||18|
|Journal||International Journal of Innovative Computing, Information and Control|
|Publication status||Published - 2013 Jul 17|
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Computational Theory and Mathematics