Abstract detail

131 / 2021-03-31 11:40:15
Performance Degradation Factors of Compact Hybrid Noise Control System using Theoretical Control Filter
Active noise control,Noise barrier,Hybrid noise control,Theoretical model,Sensitivity analysis
Special Sessions > Applications of active control
Final Paper
Sanghyeon Lee / Korea Advanced Institute of Science and Technology
Youngjin Park / KAIST
Unintended noise source outside of a specific space, such as workspaces, causes adverse effects such as work disturbance, stress, and hearing loss. For noise reduction, general methods are noise barriers and active noise control (ANC). Problem is that noise barriers are not effective in low-frequency. ANC is ineffective in high-frequency and requires an arrangement of microphones which are obstacles to users in workspaces. Accordingly, a compact hybrid noise control system using a theoretically calculated control filter (CHNCS) was proposed to reduce the noise in a wide frequency band without an arrangement of the microphones. Although the experimental system is not identical to an extreme simple theoretical model, an average noise reduction of approximately 8dB is achieved at frequencies above 200Hz which the control speakers can generate. However, in the previous research, noise reduction performance of CHNCS was degraded due to the difference between the manufactured noise control system and the extremely simplified theoretical model, since the control filter applied to the control speakers was obtained based on a theoretical model. It is too difficult to accurately build the noise control system same as the theoretical model due to manufacturing problems and using a theoretical model exactly same as the manufactured control system is inefficient due to an excessive computation amount by the complex model. Therefore, to efficiently improve the performance of a CHNCS, it is required to investigate major factors that affect noise reduction performance. In this study, factors that may cause performance degradation were selected and the sensitivity analysis for each factor was performed through simulations to identify the major factors affecting the performance. Moreover, the improvement of performance is investigated through the experiments when considering the major factors of performance degradation.

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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