DOA estimation of a gas leakage sound source based on analog signals’ time-domain compression sensing

WEI Juan1, ZHENG Liuqing1, ZHENG Haonan1, WANG Wenjing1, NING Fangli2,3

Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (17) : 165-171.

PDF(917 KB)
PDF(917 KB)
Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (17) : 165-171.

DOA estimation of a gas leakage sound source based on analog signals’ time-domain compression sensing

  • WEI Juan1, ZHENG Liuqing1, ZHENG Haonan1, WANG Wenjing1, NING Fangli2,3
Author information +
History +

Abstract

Aiming atproblems ofshortage of analog signal compression sampling in existing compression sensing algorithmsand large amount of memory and calculation of traditional measurement matrices, a direction of arrival (DOA) estimation algorithm based on analog signals’time-domain compression was proposed and applied to study DOA estimation of a gas leakage sound source.Firstly, a DOA estimation model of a gas leakage sound source was established.Then a direct non-uniform random under-sampling scheme was designed and the corresponding equivalent measurement matrix with a simple formwas constructed to realize the direct compression sampling of analog sound source signals, and avoidlarge amount of data and high computational complexity of traditional measurement matrix.Finally, the subspace tracking algorithm was adopted to reconstruct acoustic signals, and realize faster calculation speed and higher reconstruction accuracy.Theoretical analysis and tests showed that the proposed algorithm can successfully realizethe DOA estimation of a gas leakage sound source; it can significantly reduce sampling rate and computational complexity, and realize higher estimation precision and resolution, so it has a better estimation performance.

Key words

gas leakage / DOA estimation / compressed sensing / random sampling

Cite this article

Download Citations
WEI Juan1, ZHENG Liuqing1, ZHENG Haonan1, WANG Wenjing1, NING Fangli2,3. DOA estimation of a gas leakage sound source based on analog signals’ time-domain compression sensing[J]. Journal of Vibration and Shock, 2019, 38(17): 165-171

References

[1] Dizadji N, Mahmoudkhani A M, Nouri N. Theoretical and experimental aspects of saving energy in fans [J]. International Journal of Environmental Science and Technology, 2012, 9(4):729-736.
[2] 廖平平,蔡茂林,许启跃,等. 基于频谱分析的压缩空气泄漏直射和反射超声的识别[J]. 振动与冲击,2013, 32(8):58-62.
LIAO Ping-ping, CAI Mao-lin, XU Qi-yue, et.al. Distinguishing between directed and reflected ultrasonic signals generated by a compressed air leak source based on spectral analysis [J]. Journal of Vibration and Shock, 2013, 32(8):58-62.
[3] 韩慧伶,王彤宇,李俊杰. 智能气体泄漏超声检测方法研究[J]. 长春理工大学学报:自然科学版,2010, 33 (4): 114-117.
HAN Hui-ling, WANG Tong-yv, LI Jun-jie. The Design of Intelligent Ultrasonic Gas Leak Detection and Analysis System [J]. Journal of Changchun University of Science and Technology (Natural Science Edition), 2010, 33 (4): 114-117.
[4] 闫荣鑫,孙  伟,李唯丹. 便携式舱内超声检漏仪的研制[J]. 中国空间科学技术,2015, 35(3): 58-65.
YAN Rong-xin, SUN Wei, LI Wei-dan. Research and design on a portable intravehicular ultrasonic leak detector for manned spacecraft [J]. Chinese Space Science and Technology, 2015, 35(3): 58-65.
[5] Liao P, Cai M, Shi Y, et al. Compressed air leak detection based on time delay estimation using a portable multi-sensor ultrasonic detector[J]. Measurement Science & Technology, 2013, 24(5): 055-102.
[6] Huseynov J, Baliga S, Dillencourt M, et al. Gas-leak localization using distributed ultrasonic sensors[C]// Smart Sensor Phenomena, Technology, Networks, and Systems. San Diego, California, United States: International Society for Optics and Photonics, 2009:72930Z-72930Z-18.
[7] Eret P, Meskell C. Microphone arrays as a leakage detection tool in industrial compressed air systems[J]. Advances in Acoustics and Vibration, 2012, 2012(1).
[8] Steckel J, Peremans H. Ultrasound-based air leak detection using a random microphone array and sparse representations [C]// Sensors. IEEE, 2014:1026-1029.
[9] Huseynov J J, Baliga S B, Romero J G. Directional ultrasonic gas leak detector [P]. US 9482592 B2 2016.
[10] Donoho D L. Compressed sensing [J]. IEEE Transactions on information theory, 2006, 52(4): 1289-1306.
[11] Candès E J. Compressive sampling[C]//.Proceedings of the international congress of mathematicians, Madrid, Spain, 2006: 1433-1452.
[12] 石光明,刘丹华,高大化,等. 压缩感知理论及其研究进展[J]. 电子学报,2009, 37(5): 1070-1081.
SHI Guang-ming, LIU Dan-hua, Gao Da-hua,et al. Advances in Theory and Application of Compressed Sensing[J]. Acta Electronica Sinica, 2009, 37(5): 1070-1081.
[13] Kirolos S, Laska J, Wakin M, et al. Analog-to-Information Conversion via Random Demodulation[C]//. Design, Applications, Integration and Software, 2006 IEEE Dallas/CAS Workshop on. IEEE, 2007:71-74.
[14] Laska J, Kirolos S, Massoud Y, et al. Random Sampling for Analog-to-Information Conversion of Wideband Signals[C]//. Design, Applications, Integration and Software, 2006 IEEE Dallas/CAS Workshop on. IEEE, 2006:119-122.
[15] Mishali M, Eldar Y C, Dounaevsky O, et al. Xampling: analog to digital at sub-Nyquist rates [J]. Circuits Devices and Systems Iet, 2009, 5(1):8-20.
[16] Gurbuz A C, Cevher V, Mcclellan J H. Bearing estimation via spatial sparsity using compressive sensing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(2): 1358-1369.
[17] Candes E, Tao T. The Dantzig selector: Statistical estimation when p is much larger than n[J]. The Annals of Statistics, 2007,35(6): 2313-2351.
[18] Yu K, Yin M, Luo J A, et al. Wireless sensor array network DOA estimation from compressed array data via joint sparse representation [J]. Sensors, 2016, 16(5):686.
[19] Boyd S, Vandenberghe L. Convex optimization[M]. Cambridge university press, 2004.
[20] Candes E J. The restricted isometry property and its implications for compressed sensing[J]. Comptes Rendus Mathematique, 2008, 346(9-10): 589-592.
[21] Simard P, Antoni J. Acoustic source identification: Experimenting the ℓ1 minimization approach[J]. Applied Acoustics, 2013, 74(7): 974-986.
[22] Foucart S. A note on guaranteed sparse recovery via ℓ1-minimization[J]. Applied and Computational Harmonic Analysis, 2010, 29(1): 97-103.
PDF(917 KB)

334

Accesses

0

Citation

Detail

Sections
Recommended

/