Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Practical Applications of Active Noise and Vibration Control
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

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 4508

Special Issue Editor

Prof. Dr. Junhong Park

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

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://doi.org/10.3390/app122312017 - 24 Nov 2022
Viewed by 1320
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)
►▼ Show Figures

Figure 1

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://doi.org/10.3390/app122010248 - 12 Oct 2022
Cited by 1 | Viewed by 2692
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)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop