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 source location and scaling of subsonic upper-surface blowing

2020 ◽  
Vol 19 (3-5) ◽  
pp. 191-206
Author(s):  
Trae L Jennette ◽  
Krish K Ahuja
Keyword(s):  
Strouhal Number ◽  
Noise Source ◽  
Low Frequency ◽  
Directivity Pattern ◽  
Source Location ◽  
Dipole Source ◽  
Frequency Noise ◽  
Noise Sources ◽  
Trailing Edge ◽  
Trailing Edge Noise

This paper deals with the topic of upper surface blowing noise. Using a model-scale rectangular nozzle of an aspect ratio of 10 and a sharp trailing edge, detailed noise contours were acquired with and without a subsonic jet blowing over a flat surface to determine the noise source location as a function of frequency. Additionally, velocity scaling of the upper surface blowing noise was carried out. It was found that the upper surface blowing increases the noise significantly. This is a result of both the trailing edge noise and turbulence downstream of the trailing edge, referred to as wake noise in the paper. It was found that low-frequency noise with a peak Strouhal number of 0.02 originates from the trailing edge whereas the high-frequency noise with the peak in the vicinity of Strouhal number of 0.2 originates near the nozzle exit. Low frequency (low Strouhal number) follows a velocity scaling corresponding to a dipole source where as the high Strouhal numbers as quadrupole sources. The culmination of these two effects is a cardioid-shaped directivity pattern. On the shielded side, the most dominant noise sources were at the trailing edge and in the near wake. The trailing edge mounting geometry also created anomalous acoustic diffraction indicating that not only is the geometry of the edge itself important, but also all geometry near the trailing edge.

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.

COMPUTATIONAL AEROACOUSTICS EXAMPLES SHOWING THE FAILURE OF THE ACOUSTIC ANALOGY THEORY TO IDENTIFY THE CORRECT NOISE SOURCES

2002 ◽  
Vol 10 (04) ◽  
pp. 387-405 ◽  
Author(s):  
CHRISTOPHER K. W. TAM
Keyword(s):  
Noise Source ◽  
Scaling Law ◽  
Sound Generation ◽  
Acoustic Analogy ◽  
Noise Sources ◽  
Instability Waves ◽  
Full Wave ◽  
Applied Mathematician ◽  
Misleading Interpretation ◽  
Dominant Theory

Lighthill's Acoustic Analogy has been the dominant theory of aeroacoustics, especially jet aeroacoustics for almost fifty years. As yet, except for the u8 scaling law, which was derived by dimensional analysis, jet noise prediction based on the Acoustic Analogy approach has not been particularly successful. This paper examines some of the weaknesses and ambiguities in the formulation of the Acoustic Analogy theories. It is concluded that if the analogy is carried out completely, in the sense that the full wave propagation terms are retained in the propagation part of the equations of the analogy, then the theory offers no sensible noise source terms. To demonstrate that the Acoustic Analogy can fail to identify the correct noise sources, four examples are considered. They include an initial value problem, a boundary problem, the problem of weak solution and the problem of sound generation by instability waves in jets and mixing layers. These examples show clearly how, in each case, the Acoustic Analogy theory identifies the wrong noise source. Indeed, the Acoustic Analogy could provide, if not careful, misleading interpretation of the physics of sound generation. This paper is dedicated to Professor David G. Crighton, outstanding applied mathematician, world famous acoustician and a much respected friend.

Feasibility of Small Wind Turbine via Net Metering in Greek Islands

2021 ◽  
Vol 1 (1) ◽  
pp. 23-28
Author(s):  
D. Daskalaki ◽  
J. Fantidis ◽  
P. Kogias
Keyword(s):  
Wind Speed ◽  
Greenhouse Gases ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Average Wind Speed ◽  
Small Wind Turbine ◽  
Net Metering ◽  
Average Wind ◽  
Environmental Criteria ◽  
Small Wind Turbines

The evaluation of a small 3kW wind turbine through the net metering scheme is studied in this article. 14 near to sea locations in Greece examined with the help of the RetScreen expert software. The simulations based on electrical, financial and environmental criteria. Siros with average wind speed of 6.93 m/s is the most attractive area while Iraklion is the least attractive location. According to the results the simulated project is already economically sound and a small wind turbine in the Greek islands will become a progressively an even more financially source of electricity in Greece. Finally yet importantly is the fact that the use of small wind turbines has as a result that significant amount of Greenhouse gases do not reradiate into the topical atmosphere.

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.

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.

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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