Noise Cancellation method in assistive listening system - Noor Aliff, Noor Affande (2020)
For easy understanding, noise is simply an unwanted noise. But at certain occasion, noise can be completely disruptive and harmful for human being, specifically acoustical noise Continuously exposure of noise in a long term will lead to adversities toward human ear or even worse case such as hearing despair. This harmful event was always encountered by heavy industrial workers. Consequently, noise cancellation technology had been developed whether a passive noise cancellation type or active noise cancellation type in order to protect workers from the exposure of dangerous noise. Nevertheless, verbal communication among the workers is still in a state of difficulty. They depend mostly on sign languages and this is not the most efficient method of communication as the possibility of miscommunication might happen anytime. Thus, this study is dedicated to improve the capability of verbal communicate in an unfavorable condition which is a situation filled by noise. Noise cancellation system is proposed to resolve the problem. The noise cancellation system is categorized as active type of noise cancelling method as it includes adaptive filter and adaptive algorithm. This study also dedicated to use various type of adaptive algorithm to test the performance of each adaptive algorithm in order to identify the most efficient of algorithm. Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. Besides, the proposed adaptive filter is Finite Impulse Response filter. Apart from that, this study also proposed to combine basic filter which act as pre-processing method for the proposed active noise cancellation system. The filters included were Butterworth filter, Chebyshev filter, Hamming Window filter and Hanning Window filter. Based on result, it is found that Dynamic Set-Membership Affine Projection Algorithm combine together with Butterworth filter shows the best result regarding its performance which is high signal-to-noise ratio (dB), low output level of noise, and fast rate of convergence. As a conclusion, combination of Butterworth filter as pre-processing and Dynamic Set-Membership Affine Projection Algorithm as adaptive algorithm to optimize the adaptive Finite Impulse Response is the favourable element to cancel surrounding noise and subsequently can assist the objective of reaching the capability of workers to communicate verbally their time working in high noise surrounding.