Automotive Air Conditioning Compressor Noise Source Identification Method

2015 ◽  
Vol 741 ◽  
pp. 397-400
Author(s):  
Xiao Bo Huang ◽  
Jun Ye ◽  
Shu Sheng Xiong ◽  
Bin Tao Mao ◽  
Ying Hui Wang ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Air Conditioning ◽  
Noise Source ◽  
Air Conditioner ◽  
Noise Sources ◽  
Major Objective ◽  
Identification Methods ◽  
Automotive Air Conditioning ◽  
Automobile Air Conditioner ◽  
Noise Source Identification

With the improvement of requirements for vehicle comfort, people put forward higher requirements on the noise control of automotive air conditioning. As the power source of the automobile air conditioner, the compressor is also the main noise sources, so it is the major objective of vibration damping and noise reduction. In this paper, with analyzing the noise mechanism of compressor, introduces four identification methods of automotive air conditioning compressor noise source, providing theoretical basis for automobile air conditioning damping and noise reduction.

Noise Source Identification and Noise Reduction of PDP TV Using Transfer Path Analysis

2010 ◽  
Author(s):  
Hyung-Taek Kwak ◽  
Ji-Hyun Yoon ◽  
In-Hyung Yang ◽  
Jung-Youn Lee ◽  
Jae-Eung Oh
Keyword(s):  
Path Analysis ◽  
Noise Reduction ◽  
Noise Source ◽  
Analysis Method ◽  
Noise Sources ◽  
Transfer Path ◽  
Input Signals ◽  
Noise Source Identification ◽  
Absorbing Materials ◽  
Transfer Path Analysis

The module which is used for the operation of PDP TV consists of three main PCB board, X-board, Y-board, SMPS. Numerous studies on identifying noise sources of PDP TV, and reducing the noise have so far been done through experiments. However, it has been difficult to identify the exact noise sources due to correlations between sources as they are located close to each other. For that reason, Multi-Dimensional Spectral Analysis, MDSA, one of Transfer Path Analysis method, is increasingly required since it enables a quantitative analysis of each input signal’s contribution to the out signal to be carried out by eliminating the correlations of input signals. In this study, Transfer Path Analysis using MDSA is implemented to determine the quantitative noise contribution of each board. And the possibility of noise reduction is confirmed through the experimental method that isolates the most contributing board by adding sound-absorbing materials to it.

Identification of Noise Source Based on Partial Coherence Analysis

2012 ◽  
Vol 239-240 ◽  
pp. 482-486
Author(s):  
Hai Ping Wu ◽  
Jing Jun Lou ◽  
Wen Wu Liu
Keyword(s):  
Analytic Hierarchy Process ◽  
Source Identification ◽  
Noise Source ◽  
Partial Coherence ◽  
Coherence Analysis ◽  
Noise Sources ◽  
Analytic Hierarchy ◽  
Noise Source Identification ◽  
Source Excitation ◽  
Hierarchy Process

Noise source identification is the precondition and foundation of the noise reduction. There are some limitations while using some common method to analyze noise sources, so on the basis of partial coherence analysis and analytic hierarchy process, a method was proposed which can sort noise source contribution. When noise in the multi-source excitation system is coherent，this method can identify and sort noise source.

scholarly journals Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines

2017 ◽  
Vol 2017 ◽  
pp. 1-24
Author(s):  
Ping Ma ◽  
Fue-Sang Lien ◽  
Eugene Yee
Keyword(s):  
Wind Turbine ◽  
Noise Source ◽  
Sound Generation ◽  
Noise Sources ◽  
Wind Turbine Noise ◽  
Trailing Edge Noise ◽  
Small Wind Turbine ◽  
Small Wind Turbines ◽  
Noise Source Identification ◽  
Naca 0012

This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz.

Noise assessment of taxibotted versus conventional taxiing operations using a phased microphone array

2021 ◽  
Vol 263 (5) ◽  
pp. 1152-1163
Author(s):  
Bieke von den Hoff ◽  
Mirjam Snellen ◽  
Dick G. Simons
Keyword(s):  
Noise Source ◽  
Microphone Array ◽  
Noise Levels ◽  
Noise Sources ◽  
Operational Testing ◽  
Electric Aircraft ◽  
Noise Source Identification ◽  
Noise Measurements ◽  
Noise Assessment ◽  
Lower Noise

In sustainable aviation the focus is mostly applied to the greenhouse gas emissions during flight. However airports have an increasing interest in reducing emissions during ground operations such as taxiing for example to improve the local air quality. Amsterdam Airport Schiphol started a pilot for sustainable taxiing with a pilot-controlled hybrid-electric aircraft towing vehicle called TaxiBot in 2020. The COVID-19 pandemic created an opportunity for extensive operational testing on a near-empty airport. Due to the low background noise levels in this situation, also a noise assessment of taxiing with the TaxiBot versus conventional two-engine taxiing was performed. This assessment can be used to evaluate the noise levels to which ground workers or neighbouring communities are exposed due to TaxiBot operations. For the noise measurements a phased microphone array was used, which allowed not only for a noise level and directionality assessment, but also for noise source identification. This paper compares the noise emissions and noise sources between a taxibotted and conventional taxiing operation. The results show that a taxibotted taxiing operation produces significantly lower noise levels. Additionally, acoustic imaging shows that the TaxiBot engine is the main noise source for a taxibotted pass-by manoeuvre.

The interplay of tourism and noise: A literature review

2021 ◽  
Vol 263 (2) ◽  
pp. 4111-4119
Author(s):  
Lisa-Marie Wadle ◽  
Noemi Martin
Keyword(s):  
Literature Review ◽  
Noise Reduction ◽  
Noise Source ◽  
Economic Factor ◽  
Research Interest ◽  
Future Research ◽  
Noise Sources ◽  
Search Results ◽  
New Methods ◽  
Research Areas

Tourism is an important economic factor for countries, cities and individual beings. However, tourism also has an impact on the environment, e.g. in terms of noise. This does not only constitute a burden for locals but also effects tourists whose goal, among others, commonly is to rest during their holidays. A literature review was conducted covering the last ten years (2011-2021) and will be updated until the conference. The terms or and noise as well as synonyms and related terms were used in the search string. The search results in over 400 documents which were reduced based on their fit to the area of research interest and a practical screening. The overview gained by reviewing the literature indicates the most common noise sources with relation to tourism. Furthermore, several studies were found which analyse the consequences for locals and how they react to and deal with the noise. Some of the studies focused on measures taken on noise reduction like reducing the noise source itself, developing new methods to measure or visualize noise as well as structural measures. Based on this review, future research areas were identified.

Industrial Noise Source Identification by Using an Acoustic Beamforming System

1998 ◽  
Vol 120 (2) ◽  
pp. 426-433 ◽  
Author(s):  
M. R. Bai ◽  
J. Lee
Keyword(s):  
Source Identification ◽  
Noise Source ◽  
Microphone Array ◽  
Field Tests ◽  
Minimum Variance ◽  
Industrial Applications ◽  
Noise Sources ◽  
Multiple Signal Classification ◽  
Noise Source Identification ◽  
Identification Technique

A noise source identification technique is proposed for industrial applications by using a microphone array and beamforming algorithms. Both of the directions and the distances of long-range noise sources are calculated. The conventional method, the minimum variance (MV) method, and the multiple signal classification (MUSIC) method are the main beamforming algorithms employed in this study. The results of numerical simulations and field tests indicate the effectiveness of the acoustic beam-former in identifying noise sources in industrial environments.

Study of the measurement, analysis, and noise-source identification of a home air conditioner

1993 ◽  
Author(s):  
Qi-Bai Huang ◽  
Wen-Xiang Lu ◽  
Ya Wu ◽  
Xiu-Juan Qiao ◽  
Xue-Chuan Wang ◽  
...  
Keyword(s):  
Source Identification ◽  
Noise Source ◽  
Air Conditioner ◽  
Measurement Analysis ◽  
Noise Source Identification

NOISE SOURCE IDENTIFICATION IN A REVERBERANT FIELD USING SPHERICAL BEAMFORMING

2008 ◽  
Vol 22 (11) ◽  
pp. 1147-1151 ◽  
Author(s):  
YOUNG-CHUL CHOI ◽  
JIN-HO PARK ◽  
DOO-BYUNG YOON ◽  
HYU-SANG KWON
Keyword(s):  
Source Identification ◽  
Noise Source ◽  
Free Field ◽  
Sound Field ◽  
Source Location ◽  
Noise Sources ◽  
Identification Process ◽  
Noise Source Identification ◽  
Conventional Methods ◽  
Reverberant Field

Identification of noise sources, their locations and strengths, has been taken great attention. The method that can identify noise sources normally assumes that noise sources are located at a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field, reflections are added to sound field. Therefore, the source location estimated by the conventional methods may give unacceptable error. In this paper, we explain the effects of reverberant field on interior source identification process and propose the method that can identify noise sources in the reverberant field.

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