Narrow‐band indoor measurement of the sound power of a complex mechanical noise source

1990 ◽  
Vol 87 (3) ◽  
pp. 1182-1191 ◽  
Author(s):  
Robert Hickling
Keyword(s):  
Noise Source ◽  
Narrow Band ◽  
Sound Power ◽  
Mechanical Noise

Sound Power Assessment, Noise Source Identification and Directivity Analysis of Compaction Machines

2021 ◽  
Author(s):  
Milind Dadarao Kandalkar ◽  
Jaykumar bari ◽  
Dhondiram Mole ◽  
Nagesh Harishchandra Walke
Keyword(s):  
Source Identification ◽  
Noise Source ◽  
Sound Power ◽  
Noise Source Identification

Identification of the Vehicle Noise Source by Sound Intensity Method

2011 ◽  
Vol 346 ◽  
pp. 634-638 ◽  
Author(s):  
He Li ◽  
Qing Rong Zhao ◽  
Bang Chun Wen
Keyword(s):  
Power Spectrum ◽  
Noise Source ◽  
Sound Intensity ◽  
Regulation System ◽  
Sound Power ◽  
Analysis Software ◽  
Noise Sources ◽  
Vehicle Noise ◽  
Measurement Results ◽  
Radiation Noise

In this paper, we analysed the level of radiation noise and distribution of noise sources of car’s engine and front panels by using sound intensity method. To get the nephogram of sound intensity and sound power spectrum, we used the sound intensity probe and Multi-channel Data Acquisition Regulation System B&K 3560-D and Pulse Data Processing Analysis Software. By analysing experimental results, we can conclude the location of noise sources of these parts. The measurement results will serve as a reference for the car noise reduction.

Analysis of the Sound Power Level Emitted by Portable Electric Generators (Outdoor Powered Equipment) Depending on Location and Measuring Surface

2013 ◽  
Vol 430 ◽  
pp. 266-275 ◽  
Author(s):  
Elena Postelnicu ◽  
Valentin Vladut ◽  
Cristian Sorica ◽  
Petru Cardei ◽  
Ion Grigore
Keyword(s):  
Noise Source ◽  
Power Level ◽  
Acoustic Power ◽  
Sound Power ◽  
Noise Emission ◽  
Sound Power Level ◽  
Measuring Surface ◽  
Measurement Surface ◽  
Electric Generators

Acoustic power is a measure which must be specified on the outdoor used equipments and its determination depends on several factors: the place where the equipment works (indoor or outdoor), the placement of the microphones for its determination (the distance less or greater from the noise source), the shape of the measurement surface (parallelepiped or hemispherical). This paper aims to analyze the values obtained in these situations and interpret the data to determine the influence that each factor has on the acoustic power compared with the values obtained (permissible) according to Directive regarding noise emission D 2000/14/EC.

scholarly journals COGENERATION UNIT NOISE REDUCTION BY ITS CASE

2021 ◽  
Vol 2021 (2) ◽  
pp. 4501-4504
Author(s):  
RADEK STRAMBERSKY ◽  
◽  
VACLAV PAVELKA ◽  
TOMAS PAWLENKA ◽  
PAVEL SURANEK ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Frequency Spectrum ◽  
Noise Source ◽  
Microphone Array ◽  
Noise Measurement ◽  
Sound Power ◽  
Final Number ◽  
Beamforming Algorithm

This paper deals with cogeneration unit noise measurement by the acoustic camera. Noise is not only measured as the final number of sound power levels, but also its original location is determined with the use of the beamforming algorithm. The properties of the used microphone array are considered and numerically calculated as every different microphone array layout will measure with another resolution. From the frequency spectrum, the possible technical source is determined. The results of noise source visualization show the cogeneration unit case noise decreasing effect while also offering the possibilities for design improvements.

scholarly journals Comparison of Analysis and Experiment for Gearbox Noise

1992 ◽  
Author(s):  
Fred B. Oswald ◽  
A. F. Seybert ◽  
T. W. Wu ◽  
William Atherton
Keyword(s):  
Narrow Band ◽  
Power Level ◽  
Experimental Results ◽  
Sound Power ◽  
Spur Gears ◽  
Contact Ratio ◽  
Acoustic Intensity ◽  
Resonant Frequencies ◽  
Gear Noise ◽  
The Difference

Abstract Low-contact-ratio spur gears were tested in the NASA gear-noise rig to study the noise radiated from the top of the gearbox. Experimental results were compared with a NASA acoustics code to validate the code for predicting transmission noise. The analytical code is based on the boundary element method (BEM) which models the gearbox top as a plate in an infinite baffle. Narrow-band vibration spectra measured at 63 nodes on the gearbox top were used to produce input data for the BEM model. The BEM code predicted the total sound power based on this measured vibration. The measured sound power was obtained from an acoustic intensity scan taken near the surface of the gearbox at the same 63 nodes used for vibration measurements. Analytical and experimental results were compared at four different speeds for sound power at each of the narrow-band frequencies over the range of 400 to 3200 Hz. Results are also compared for the sound power level at meshing frequency plus three sideband pairs and at selected gearbox resonant frequencies. The difference between predicted and measured sound power is typically less than 3 dB with the predicted value generally less than the measured value.

A Simulation on Aerodynamic Noise of an Air-Conditioning Duck

2012 ◽  
Vol 466-467 ◽  
pp. 778-783
Author(s):  
Wen Ku Shi ◽  
Jian Peng Yao ◽  
Suo Jun Hou ◽  
Fu Xiang Guo ◽  
De Guang Fang
Keyword(s):  
Flow Field ◽  
Air Conditioning ◽  
Transient Flow ◽  
Noise Source ◽  
New Products ◽  
Flow Simulation ◽  
Broadband Noise ◽  
Aerodynamic Noise ◽  
Sound Power ◽  
Simulation Results

The transient flow field is needed in order to predict the aerodynamic noise of an automotive HVAC duck by conventional methods. However, it is time-consuming when are several improved schemes .To solve the problem, schemes with large sound power can be discarded using Broadband Noise Source (BNS) model at first. Then, the best scheme can be found after the transient flow simulation .In this paper, an automotive HVAC duck is used as an example. Firstly BNS is used to predict which scheme is noisier, secondly the aerodynamic noise is computed using Fluent coupled with Sysnoise. At last they come to the same conclusion. The simulation results indicate BNS model can be used to find which scheme is the best without computing the transient flow field. So it can shorten the cycle of developing new products.

scholarly journals A System-Level Modelling of Noise in Coupled Resonating MEMS Sensors

2020 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Vinayak Pachkawade
Keyword(s):  
Noise Source ◽  
Operating Conditions ◽  
Sensor System ◽  
System Level ◽  
Mems Sensors ◽  
Noise Sources ◽  
System A ◽  
Sensing Applications ◽  
Mechanical Noise ◽  
The Impact

This paper presents realistic system-level modeling of effective noise sources in a coupled resonating mode-localized MEMS sensors. A governing set of differential equations are used to build a numerical model of a mechanical noise source in a coupled-resonator sensor and an effective thermo-mechanical noise is quantified through the simulation performed via SIMULINK. On a similar note, an effective noise that stems from the electronic readout used for the coupled resonating MEMS sensors is also quantified. Various noise sources in electronic readout are identified and the contribution of each is quantified. A comparison between an effective mechanical and electronic noise in a sensor system aids in identifying the dominant noise source in a sensor system. A method to optimize the system noise floor for an amplitude-based readout is presented. The proposed models present a variety of operating conditions, such as finite quality factor, varying coupled electrostatic spring strength, and operation with in-phase and out-of-phase mode. The proposed models aim to study the impact of fundamental noise processes that govern the ultimate resolution into a coupled resonating system used for various sensing applications.

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