Archives of Acoustics, 42, 4, pp. 619–629, 2017

A Fast Method of Feature Extraction for Lowering Vehicle Pass-By Noise Based on Nonnegative Tucker3 Decomposition

Haijun WANG
NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

Guoyong DENG
NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

Xueping LI
NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

Honggeng LI
NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

Yuanyi HUANG
NVH Research Department, SAIC-GM-Wuling Automobile CO., LTD

Usually, the judgement of one type fault of vehicle pass-by noise is difficult for engineers, especially when some significant features are disturbed by other interference noise, such as the squealing noise is almost simultaneous with the whistle in the exhaust system. In order to cope with this problem, a new method, with the antinoise ability of the algorithm on the condition by which the features are entangled, is developed to extract clear features for the fault analysis. In the proposed method, the nonnegative Tucker3 decomposition (NTD) with fast updating algorithm, signed as NTD FUP, can find out the natural frequency of the parts/components from the exhaust system. Not only does the NTD FUP extract clear features from the confused noise, but also it is superior to the traditional methods in practice. Then, an aluminium-foil alloy material, which is used for the heat shield for its lower noise radiation, replaces the aluminium alloy alone. Extensive experiments show that the sound pressure level of the vehicle pass-by noise is reduced 0.9 dB(A) by the improved heat shield, which is also considered as a more lightweight design for the exhaust system of an automobile.
Keywords: vehicle pass-by noise; NTD; feature extraction; sound pressure level
Full Text: PDF
Copyright © Polish Academy of Sciences & Institute of Fundamental Technological Research (IPPT PAN).


Andersson C.A., Bro R. (1998), Improving the speed of multi-way algorithms: Part I. Tucker3, Chemometrics and Intelligent Laboratory Systems, 42, 93–103,

Bader B.W, Kolda T.G. (2006), Algorithm 862: MATLAB tensor classes for fast algorithm prototyping, ACM Transactions on Mathematical Software, 32, 635–653,

Braun M.E., Walsh S.J., Horner J.L., Chuter R. (2013), Noise source characteristics in the ISO 362 vehicle pass-by noise test: Literature review, Applied Acoustics, 74, 1241–1265,

Buciu I., Pitas I. (2006), NMF, LNMF, and DNMF modeling of neural receptive fields involved in human facial expression perception, Journal of Visual Communication and Image Representation, 17, 958–969,

Beijing labor protection research (2002), Limits and measurement methods for noise emitted by accelerating motor vehicles [in Chinese], GB 1495-2002,

Cichocki. A, Amari S. (2010), Families of Alpha- Beta- and Gamma- Divergences: Flexible and Robust Measures of Similarities. Entropy, 12, 1532–1568.

Cichocki A., Zdunek R., Phan A.H., Amari S.I. (2009), Nonnegative matrix and tensor factorizations: Applications to exploratory multi-way data analysis and blind source separation. John Wiley & Sons,

Davies P., Harrison M. (1997), Predictive acoustic modelling applied to the control of intake/exhaust noise of internal combustion engines, Journal of Sound and Vibration, 202, 249–274.

Hemmateenejad B., Javidnia K., Saeidi-Boroujeni M. (2008), Spectrophotometric monitoring of nimesulide photodegradation by a combined hard-soft multivariate curve resolution-alternative least square method, Journal of Pharmaceutical and Biomedical Analysis; 47, 3, 625–630,

Kim Y.D., Choi S.J. (2007), Nonnegative tucker decomposition, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1–8, pp. 3104-3111, Minneapolis, MN,

Kopriva I., Cichocki A. (2010), Nonlinear band expansion and 3D nonnegative tensor factorization for blind decomposition of magnetic resonance image of the brain, International Conference on Latent Variable Analysis and Signal Separation; 6363, pp. 490–497, St. Malo, France,

Lim L.H, Comon P. (2010), Multiarray signal processing: Tensor decomposition meets compressed sensing, Comptes Rendus Mecanique, 338, 6, 311–320,

Mongia R.K., Bhartia P. (1994), Dielectric resonator antennas. A review and general design relations for resonant frequency and bandwidth, International Journal of Microwave and Millimeter-Wave Computer Aided Engineering, 4, 230–247,

Nilsson M.E. (2007), A-weighted sound pressure level as an indicator of short-term loudness or annoyance of road-traffic sound, Journal of Sound and Vibration, 302, 197–207,

Okokon E.O., Turunen A.W., Ung-Lanki S., Vartiainen A.K., Tiittanen P., Lanki T. (2015), Road-traffic noise: annoyance, risk perception, and noise sensitivity in the finnish adult population, International Journal of Environmental Research and Public Health, 12, 5712–5734,

Park S.H., Kim Y.H. (2001), Visualization of pass-by noise by means of moving frame acoustic holography, Journal of the Acoustical Society of America, 110, 2326–2339,

Patterson E., Gillette D. (1977), Commonalities in measured size distributions for aerosols having a soil‐derived component. Journal of Geophysical Research, 82, 2074–2082,

Romanowicz B. (2014), Surface Waves, Encyclopedia of Solid Earth Geophysics, Springer Netherlands, pp.1406–1419, 481-8702-7_143.

Xu Y.Y, Yin W.T. (2013), A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion, SIAM Journal on Imaging Sciences, 6, 1758–1789,

Wang C., He X., Bu J., Chen Z., Chen C., Guan Z. (2011), Image representation using Laplacian regularized nonnegative tensor factorization, Pattern Recognition, 44, 2516–2526,

Wang H., Xu F., Jia M., Hu J., Huang P. (2013a), Research on exponential regularization approach for nonnegative Tucker3 decomposition, Optik – International Journal for Light and Electron Optics, 124, 6615–6621, 2013.05. 024.

Wang H.J., Deng G.Y., Li Q.L., Kang Q. (2016), Research on bispectrum analysis of secondary feature for external vehicle noise based on nonnegative tucker3 decomposition, Eksploatacja i Niezawodność – Maintenance and Reliability, 18, 291–298,

Wang H.J., Xu F.Y., Zhao J., Jia M.P., Hu J.Z., Huang P. (2013b), Bispectrum feature extraction of gearbox faults based on nonnegative Tucker3 decomposition with 3D calculations, Chinese Journal of Mechanical Engineering, 26, 1182–1193, http://dx.doi. org/10.3901/CJME.2013.06.1182.

DOI: 10.1515/aoa-2017-0066