Spatial resolution limits for the localization of noise sources using direct sound mapping

Comesaña, Daniel Fernández; Holland, Keith; Fernández-Grande, Efrén

doi:10.1016/j.jsv.2016.04.010

Cited by 13 publications

(4 citation statements)

References 19 publications

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“…In evaluation of beamform maps, involving subjectivity (visual inspection), the arbitrary use of the Rayleigh limit [8,13,14], as well as the Sparrow limit [13,15] is widespread. The application of the Rayleigh criterion and the Full Width at Half Maximum criterion is investigated in [18], where alternative limits are also introduced.…”

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confidence: 99%

Algorithmic localisation of noise sources in the tip region of a low-speed axial flow fan

Tóth

Vad

2017

Journal of Sound and Vibration

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An objective and algorithmised methodology is proposed to analyse beamform data obtained for axial fans. Its application is demonstrated in a case study regarding the tip region of a low-speed cooling fan. First, beamforming is carried out in a co-rotating frame of reference. Then, a distribution of source strength is extracted along the circumference of the rotor at the blade tip radius in each analysed third-octave band. The circumferential distributions are expanded into Fourier series, which allows for filtering out the effects of perturbations, on the basis of an objective criterion. The remaining Fourier components are then considered as base sources to determine the blade-passage-periodic flow mechanisms responsible for the broadband noise. Based on their frequency and angular location, the base sources are grouped together. This is done using the fuzzy c-means clustering method to allow the overlap of the source mechanisms. The number of clusters is determined in a validity analysis. Finally, the obtained clusters are assigned to source mechanisms based on the literature. Thus, turbulent boundary layer-trailing edge interaction noise, tip leakage flow noise, and double leakage flow noise are identified.

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confidence: 99%

Algorithmic localisation of noise sources in the tip region of a low-speed axial flow fan

Tóth

Vad

2017

Journal of Sound and Vibration

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“…For the experimental results in figure 10, the peak to valley ratios with 160 iterations for the 1.0 mm and 0.8 mm rods were 1.53 and 1.14 respectively. Using the Rayleigh criterion of separating two peaks, which is having a peak to valley ratio of 1.23 [19], the 1.0 mm rods were resolved, but the 0.8 mm rods were not.…”

Section: Peak To Valley Ratiomentioning

confidence: 99%

Tomographic imaging with Compton PET modules: ideal case and first implementation

et al. 2021

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In our previous studies, we demonstrated that the Compton PET module, a layer structure PET detector with side readout, can provide high performance in terms of spatial/energy/timing resolution, as well as high gamma ray detection efficiency. In this study, we investigate how to translate the high performance of the detector module into good quality reconstructed tomographic images. This study is performed using GATE simulation, as well as with physical experiments. Similar detector geometry is used in the simulation and experiment: two identical 4-layer detector modules are placed with face to face distance of 56 mm. In the simulation study, each layer consists of a 1-mm-pitch pixelated crystal array. In the experimental study, each layer is a monolithic crystal, which is virtually binned into 1 mm^2 cells to group single events according to the gamma ray interaction locations. A customized Derenzo phantom was placed between the two detector modules. By rotating the phantom using a motorized rotary stage, data along lines of response (LORs) at different angles were collected for reconstructing the tomographic image. The same reconstruction algorithm was used for both simulation and experimental studies. The results demonstrate that the simulation study could resolve 0.8 mm rods while the experimental study was able to resolve 1.0 mm rods.

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“…However, there is a near-field error 12 in the sound intensity test, which will be smaller when the double microphones are closer to the sound source. And the Rayleigh criterion 13 holds that the spatial resolution of sound field imaging is related to the 1 School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China 2 distance from the microphone to the sound source surface. So the conventional sound intensity test does not obtain high-resolution sound intensity images to accurately distinguish the dense and complex excitation sources inside the motor.…”

Section: Introductionmentioning

confidence: 99%

High precision localisation of the sources of noise of a bent-axis motor

Xu,

Xiangming,

Qinghong

et al. 2023

Noise & Vibration Worldwide

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The hydraulic motor will generate noise in operation and it has fluid-structure coupling and compact internal structure. The sound intensity measurement is difficult to distinguish the noise sources of motor. In this paper, a high-precision localization method for noise sources of bent-axis motor is studied to improve the resolution of the sound intensity images to locate noise sources accurately. Firstly, the structural characteristics of the motor are analyzed, and the sound intensity images are obtained through the experiment. Then the high-resolution optimization method based on compressed sensing is designed according to the characteristics of the sound intensity field. Finally, the sound intensity images with high resolution are constructed. The high-resolution images can distinguish the position of the prominent points, and the error is less than 0.4 dB. The identification distance of noise sources can reach 30 mm, and it breaks through the highest resolution of the traditional sound intensity test.

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Spatial resolution limits for the localization of noise sources using direct sound mapping

Cited by 13 publications

References 19 publications

Algorithmic localisation of noise sources in the tip region of a low-speed axial flow fan

Algorithmic localisation of noise sources in the tip region of a low-speed axial flow fan

Tomographic imaging with Compton PET modules: ideal case and first implementation

High precision localisation of the sources of noise of a bent-axis motor

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