Active Noise Isolation of a Plate Structure Without Using Acoustic Sensors

In this study, an improved system of active noise isolation without using acoustic sensors is used to suppress the noise transmission through a plate structure. The system used in this study is an improvement of the system proposed by the authors in an earlier study, in which the sound pressure of the noise radiated from a GFRP plate is estimated from the voltage signals of the piezoelectric elements embedded in the plate by using the Rayleigh's integral formula and the estimated sound pressure is used as the feedback signal in the control system. Owing to the large estimation error, the former method is only partially successful, that is, it is effective for some of the resonance frequencies, but not for the others. In this study, a neural network is used instead of the Rayleigh's integral formula. The control system consists of a neural network identifier and an adaptive feedback controller using the filtered-X LMS algorithm for feedback control. Experimental results show that the estimated sound pressure of the radiated noise agrees well with the sound pressure measured directly by a microphone. The new noise isolation system without using acoustic sensors exhibits the same noise control performance as the conventional system using microphone sensors. It also exhibits better noise control performance than the vibration control system, which directly uses the signals from the piezoelectric elements as feedback.