Vehicular Traffic Noise Reduction using Fuzzy Logic based Active Noise Control System
Manoj Kumar Sharma1, Renu Vig2
1Manoj Kumar Sharma, Department of EEE, UIET, Panjab University, Chandigarh (Punjab), India.
2Renu Vig, Department of ECE, UIET, Panjab University, Chandigarh (Punjab), India.
Manuscript received on 27 March 2019 | Revised Manuscript received on 04 April 2019 | Manuscript Published on 12 April 2019 | PP: 124-128 | Volume-7 Issue-6C April 2019 | Retrieval Number: F90420476C19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The exposure to the noise emanating from the vehicles is resulting in adverse effects on our health. This requires determined efforts for the alleviation of road noise. The implementation of noise reduction techniques is the need of the hour to safeguard ourselves from the rising traffic noise conditions. This paper aims to investigate prominent vehicular noises in peak traffic conditions in Chandigarh, India and to reduce identified noises using fuzzy logic based active noise control system. A study was conducted to record the sound pressure level at the peak traffic timings during the day using the sound level meter in Chandigarh, India. The vehicle horns are identified as major sources producing high noise levels. The horn noise signals of bus, car, two-wheeler, and three-wheeler were recorded. A Fuzzy Logic based Active Noise Control (ANC) system was developed in MATLAB software and was implemented for the reduction of recorded vehicle horn noises. The performance of the Fuzzy Logic based Active Noise Control system for noise reduction is compared on the basis of error plots, signal to noise ratio (SNR) and mean square error (MSE). The proposed Fuzzy Logic based Active Noise Control (ANC) system is successful in reducing the noise levels of a bus and two-wheeler by 23 dB(A) each. Noise is reduced by 28 dB (A) and 25 dB (A) in the case of car and three-wheeler horn respectively. The fuzzy based ANC system is successful in reducing the noise to comfortable levels which can be implemented in real-time for attaining permissible limits of noise.
Keywords: Traffic Noise, Vehicle Horn Noise, Active Noise Control, Fuzzy Mklogic-Based ANC, Horn Noise Reduction.
Scope of the Article: Fuzzy Logics