Research On Multi-channel Virtual Sensing Method For Active Noise Reduction Seat

Active noise control(ANC)is a noise reduction technique based on acoustic wave superposition.The sound pressure level is reduced at the desire position by an anti-noise wave transmitted from the control source,which has the same amplitude and opposed phase of the noise wave.In the ANC system,the function of the error microphone is to monitor the error signal and continuously feed the signal back to the system using an adaptive control filter until a zone of quiet is formed at the desired position.However,due to application constraints,the error microphone sometimes cannot be placed at the desire position.Virtual sensing(VS)methods are proposed and developed for such situations.There are two most commonly used VS methods.They are the auxiliary filter based VS(AF-VS)method and the remote microphone based VS(RMVS)method.The AF-VS method preserves the information regarding the optimal control filter that can achieve the maximum noise reduction at the target Zo Q.The RM-VS method estimates the disturbance signal at the target Zo Q based on remote measurements.In this thesis,we propose a new VS method,the relative path based VS(RP-VS)method,which estimates both the disturbance signal and the anti-noise signal at the target Zo Q.This thesis first compares the noise reduction performance of the three VS algorithms and verifies the effectiveness of the RP-VS method in the feedforward ANC system through the changes in the acoustic paths and the noise frequency bands.Subsequently,the RP-VS method is realized in a feedback ANC system with crosschannel filters,which are more suitable for reducing noise signals with a certain bandwidth.Simulation results validate theoretical analysis and demonstrate that under different acoustic environments,the RP-VS method has good robustness in average noise reduction performance,whether it is applied in the feedforward structure or the feedback structure.Finally,this paper builds an active noise reduction seat,which proves that the newly proposed RP-VS algorithm can maintain considerable noise reduction performance in equipment experiments.It is worth noting that the robustness of the RP-VS algorithm does not mean that it can achieve the best noise reduction under all conditions.It can only show that the algorithm provides an alternative solution for practical applications.