Practical Applications of Active Noise and Vibration Control

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 3350

Special Issue Editor


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Guest Editor
Department of Mechanical Engineering, College of Engineering, Hanyang University, Seoul 04763, Korea
Interests: interior aerodynamic noise in road and air vehicles; micromechanics of polymers and granular materials; measurement of dynamic material properties of polymers; granular and porous materials; fluid-structure interactions and aeroacoustics; vibration; sound radiation analysis of advanced structures; active vibration and noise control using smart materials; structural health monitoring; control of flow-induced sound and vibrations
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Special Issue Information

Dear Colleagues,

With the increasing use of machinery systems in living environments, acoustic noise has become a primary source of discomfort for residents. Efficient methodology to implement quiescent space for individuals is a crucial element for personal wellness. For transportation systems, it is important to secure quiet space with minimal mass loading. Active noise and vibration controls are proposed as an effective methodology for minimizing discomfort. Successive implementation depends on the hardware and algorithm used for active control. Since active noise control utilizes electronic systems for modification of dynamic characteristics, successful implementation requires investigations from many different fields, including electronic embedded systems, digital signal processing, acoustics, vibration analysis, modal analysis, electronics, and material science. This Special Issue is intended to collect recent advancements in the relevant fields.

Prof. Dr. Junhong Park
Guest Editor

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Keywords

  • active noise and vibration control
  • adaptive control
  • semi-active control
  • feedback and feedforward control
  • digital signal processing
  • electronic system implementation
  • neural network and deep learning
  • transfer path analysis
  • multi-channer active control
  • acoustics and vibration analysis of enclosed systems
  • system identification

Published Papers (2 papers)

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14 pages, 7057 KiB  
Article
A Feasibility Study of the Use of PZT Actuators for Active Control to Enrich Engine Sound
by Young-Sup Lee, Seokhoon Ryu, Jihea Lim and Eunsuk Yoo
Appl. Sci. 2022, 12(23), 12017; https://0-doi-org.brum.beds.ac.uk/10.3390/app122312017 - 24 Nov 2022
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Abstract
This study examines the feasibility of a novel active sound enrichment (ASE) system using piezoelectric actuators as sound generators and an inverse control filter to supplement poor engine sound at the driver’s ear location in a passenger car instead of using an interior [...] Read more.
This study examines the feasibility of a novel active sound enrichment (ASE) system using piezoelectric actuators as sound generators and an inverse control filter to supplement poor engine sound at the driver’s ear location in a passenger car instead of using an interior audio system. The proposed ASE algorithm is developed as a purely feedforward control strategy to track the pre-defined target engine sound (three engine orders). Theoretical and experimental analyses are investigated in-depth on the vibro-acoustic characteristics of a PZT (lead zirconate titanate) actuator bonded on a steel plate and a dedicated control filter to supplement sound using an inverse method to compensate for the secondary path. The location of the PZT-plate actuator was carefully chosen to satisfy the causality condition and robustly stable control of the ASE algorithm. The experimental ASE system was set up in a test car, and the ASE algorithm was implemented in a real-time controller. The real-time ASE experiment results showed that the measured sound of the three orders was well supplemented as the tracking of the target sound was achieved robustly with small errors without any divergent instability. Thus, this study suggests that the proposed ASE system using the PZT-plate actuator and the dedicated control filter is a feasible method for enriching sound in cars, and this approach can be considered as a masking tool against some exotic noise frequently observed in various vehicles including electric vehicles. Full article
(This article belongs to the Special Issue Practical Applications of Active Noise and Vibration Control)
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12 pages, 4788 KiB  
Article
Active Noise Reduction with Filtered Least-Mean-Square Algorithm Improved by Long Short-Term Memory Models for Radiation Noise of Diesel Engine
by Semin Kwon, Bo-Seung Kim and Junhong Park
Appl. Sci. 2022, 12(20), 10248; https://0-doi-org.brum.beds.ac.uk/10.3390/app122010248 - 12 Oct 2022
Cited by 1 | Viewed by 1951
Abstract
This study presents an active noise control (ANC) algorithm using long short-term memory (LSTM) layers as a type of recurrent neural network. The filtered least-mean-square (FxLMS) algorithm is a widely used ANC algorithm, where the noise in a target area is reduced through [...] Read more.
This study presents an active noise control (ANC) algorithm using long short-term memory (LSTM) layers as a type of recurrent neural network. The filtered least-mean-square (FxLMS) algorithm is a widely used ANC algorithm, where the noise in a target area is reduced through a control signal generated from an adaptive filter. Artificial intelligence can enhance the reduction performance of ANC for specific applications. An LSTM is an artificial neural network for recognizing patterns in arbitrarily long sequence data. In this study, an ANC controller consisting of LSTM layers based on deep neural networks was designed for predicting a reference noise signal, which was used to generate the control signal to minimize the noise residue. The structure of the LSTM neural networks and procedure for training the LSTM controller for the ANC were determined. Simulations were conducted to compare the convergence time and performances of the ANC with the LSTM controller and those with a conventional FxLMS algorithm. The noise source adopted sounds from a single-cylinder diesel engine, while reference noises selected were single harmonics, superposed harmonics, and impulsive signals generated from the diesel engine. The characteristics of each algorithm were examined through a Fourier transform analysis of the ANC results. The simulation results demonstrated that the proposed ANC method with LSTM layers showed outstanding noise reduction capabilities in narrowband, broadband, and impulsive noise environments, without high computational cost and complexity relative to the conventional FxLMS algorithm. Full article
(This article belongs to the Special Issue Practical Applications of Active Noise and Vibration Control)
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