Performance comparison of acoustic emission sensor arrays in different topologies for the localization of gas leakage on a flat-surface structure

Yan, Yong; Hu, Yonghui; Guo, Miao

doi:10.1016/j.sna.2019.111659

Cited by 13 publications

(4 citation statements)

References 25 publications

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“…The array performance has a large impact on the localization results [ 34 ], so it is necessary to focus on the design of the sensor array. The performance factors affected by the array design mainly include spatial resolution, sidelobe distributions and levels, and spatial aliasing [ 35 ].…”

Section: The Design Of Acoustic Localization Sensormentioning

confidence: 99%

An Acoustic Localization Sensor Based on MEMS Microphone Array for Partial Discharge

Yan

Chen

et al. 2023

Sensors

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Partial discharge (PD) localization is important for monitoring and maintaining high-voltage equipment, which can help to prevent accidents. In this work, an acoustic localization sensor based on microelectromechanical system (MEMS) microphone array is proposed, which can detect and locate the partial discharge through a beam-forming algorithm. The MEMS microphone array consists of eight commercial MEMS microphones (SPV08A0LR5H-1, Knowles Electronics, IL, USA) with an aperture size of about 0.1 m × 0.1 m, allowing for a small hardware size and low cost. In order to optimize the acoustic performance of the array, a random array topology is designed. The simulation analysis indicates that the designed random topology is superior to several commonly used topologies. In terms of the localization algorithm, a deconvolution method called Fourier-based fast iterative shrinkage thresholding algorithm (FFT-FISTA) is applied. Simulation and experiment results demonstrate that FFT-FISTA used in the proposed acoustic localization sensor has significant advantages over the conventional beam-forming algorithm on spatial resolution and sidelobe suppression. Experimental results also show that the average localization error of the proposed scheme is about 0.04 m, which can meet the demands of practical application.

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Section: The Design Of Acoustic Localization Sensormentioning

confidence: 99%

An Acoustic Localization Sensor Based on MEMS Microphone Array for Partial Discharge

Yan

Chen

et al. 2023

Sensors

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“…For spacecraft, the load needs to be as small and light as possible. Research by Cui et al [16] showed that L-type arrays can obtain the best experimental results with the smallest number of sensors. Therefore, in the following research, an L-shaped array with 8 sensors was used as an example.…”

Section: Delay-and-sum Beamforming Algorithmmentioning

confidence: 99%

Research on Leakage Location of Spacecraft in Orbit Based on Frequency Weighting Matrix Beamforming Algorithm by Lamb Waves

Zeng

Zhang

et al. 2020

Applied Sciences

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Featured Application: The Frequency Weighting Matrix Beamforming Algorithm proposed in this paper has the potential to locate leakages in large structures such as spacecraft, and the algorithm can adapt the characteristics of leaks.Abstract: Clashes between space debris and spacecraft in orbit may cause air leakages, which pose a substantial danger to the crew and the spacecraft. Lamb wave dispersion in spacecraft structures and the randomness of leak holes are the difficulties in leak location. To solve these problems, a frequency weighting matrix beamforming algorithm is proposed in this paper. The elastic Lamb waves that are caused by leakages are acquired by an 'L' shaped sensor array consisting of eight acoustic emission sensors. The angle of a leak can be obtained through the superposition of different time delays, and the intersection of two angles can be used to find the location of the leak. Traditional beamforming is improved by matching the wave speeds in different frequency bands and weightings according to the energy distribution. Narrowband filtering is used to delay overlay different signal speeds with different frequency bands via a dispersion curve. The weighting method is used to compensate the frequency band response of different leak holes. The detailed location algorithm process is introduced and verified by experiments. For 1.5 and 2 mm leak holes, location direction accuracies of 1.33 • and 1.93 • for one sensor array were obtained, respectively.

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“…An important factor affecting the accuracy of ultrasonic localization is the time delay estimation of an ultrasonic signal. The commonly used methods for time delay estimation include: the rising-edge triggering method, the threshold triggering method, basic cross correlation, generalized cross correlation, adaptive filtering, a neural network, deep learning, and so on [ 18 , 19 , 20 , 21 , 22 ]. Among them, the rising-edge trigger method and threshold trigger method are the least computationally intensive methods for time delay estimation, which are generally applicable to the occasions where the waveform profile is clear and has no distortion or small distortion.…”

Section: Introductionmentioning

confidence: 99%

Spatial Localization of a Transformer Robot Based on Ultrasonic Signal Wavelet Decomposition and PHAT-β-γ Generalized Cross Correlation

Ji,

Liu,

Zhang

et al. 2024

Sensors

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Because large oil-immersed transformers are enclosed by a metal shell, the on-site localization means it is difficult to achieve the accurate location of the patrol micro-robot inside a given transformer. To address this issue, a spatial ultrasonic localization method based on wavelet decomposition and PHAT-β-γ generalized cross correlation is proposed in this paper. The method is carried out with a five-element stereo ultrasonic array for the location of a transformer patrol robot. Firstly, the localization signal is decomposed into wavelet coefficients of different scales, which would realize the adaptive decomposition of the frequency of the localization signal from low frequencies to high frequencies. Then, the wavelet coefficients are denoised and reconstructed by using the semi-soft threshold function. Second, a modified phase transform-beta-gamma (PHAT-β-γ) method is used to calculate the exact time delay between different sensors by increasing the weights of the PHAT weighting function and introducing a correlation function. Finally, by using the proposed method, the accurate localization of the transformer patrol micro-robot is achieved with a five-element stereo ultrasonic array. The simulation and test results show that inside a transformer experimental oil tank (120 cm × 100 cm × 100 cm, L × W × H), the relative error of transformer patrol micro-robot spatial localization is within 4.1%, and the maximum localization error is less than 3 cm, which meets the requirement of engineering localization.

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Performance comparison of acoustic emission sensor arrays in different topologies for the localization of gas leakage on a flat-surface structure

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 13 publications

References 25 publications

An Acoustic Localization Sensor Based on MEMS Microphone Array for Partial Discharge

An Acoustic Localization Sensor Based on MEMS Microphone Array for Partial Discharge

Research on Leakage Location of Spacecraft in Orbit Based on Frequency Weighting Matrix Beamforming Algorithm by Lamb Waves

Spatial Localization of a Transformer Robot Based on Ultrasonic Signal Wavelet Decomposition and PHAT-β-γ Generalized Cross Correlation

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