Vibration analysis based on empirical mode decomposition and partial least square

Procedia Engineering

Volumn 16, Issue , 2011, Pages 646-652

  Tang, Jian ^a   Zhao, Lijie ^a,b   Yue, Heng ^c   Yu, Wen ^d   Chai, Tianyou ^a,c  

^a KEY LABORATORY OF INTEGRATED AUTOMATION OF PROCESS INDUSTRY   (China)

^b SHENYANG UNIVERSITY OF CHEMICAL TECHNOLOGY   (China)

^c NORTHEASTERN UNIVERSITY   (China)

^d DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

Empirical mode decomposition (EMD); Partial least square(PLS); Power spectral density (PSD); Pulp density (PD); Shell vibration

Indexed keywords

EMPIRICAL MODE DECOMPOSITION; PARTIAL LEAST SQUARES; POWER SPECTRAL DENSITY (PSD); PULP DENSITY (PD); SHELL VIBRATION;

AUTOMATION; BALL MILLS; CONTROL; FAST FOURIER TRANSFORMS; POWER SPECTRAL DENSITY; SENSORS; SHELLS (STRUCTURES); SIGNAL PROCESSING; SPECTRAL DENSITY;

VIBRATION ANALYSIS;

EID: 84863408692     PISSN: 18777058     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.proeng.2011.08.1136     Document Type: Conference Paper

References (14)

1. Mori H, Kano J, Saito F. Ball mill simulation in wet grinding using a tumbling mill and its correlation to grinding rate. Powder Technology 2004;143:230-239. (Pubitemid 39091943)
2. Bai R, Chai TY, Optimization control of ball mill load in blending process with data fusion and case-based reasoning. Journal of Chemical Industry and Engineering 2009;60:1746-1751.
3. Iwasaki I, Pozzo RL, Natarajan KA, Aaam K, Orlich JN. Nature of corrosive and abrasive wear in ball mill grinding. International Journal of Mineral Processing 1988;22:345-360.
4. Spencer SJ, Campbell JJ, Weller KR, Liu Y. Acoustic emissions monitoring of SAG mill performance. Intelligent Processing and Manufacturing of Materials 1999;2:936-946.
5. Tang J, Zhao LJ, Zhou JW, Yue H, Chai TY. Experimental nalysis of wet mill load based on vibration signals of laboratoryscale ball mill shell. Minerals Engineering 2010;23:720-730.
6. Tang J, Zhao LJ, Yu W, Yue H, Chai TY. Soft sensor modeling of ball mill load via principal component analysis and support vector machines. Lecture Notes in Electrical Engineering 2010;67:803-810.
7. Huang NE, Shen Z, Long SR. The empirical mode decomposition and the Hilbert spectrum for non-linear and non stationary time series analysis. Proc. Royal Soc. London A 1998;454:903-995. (Pubitemid 128733183)
8. Yang JN, Lei Y, Pan S, Huang N. System identification of linear structure based on Hilbert-Huang spectral analysis. Part 1: Normal Modes. Earthquake Eng. Struct. Dyn. 2003;32:1443-1467. (Pubitemid 36971761)
9. Huang P, Pan ZW, Qi XL, Lei JP. Bearing fault diagnosis based on EMD and PSD. In: Proceedings of the 8th World Congress on Intelligent Control and Automation, WCICA 2010, Jinan, China, 2010, p: 1300-1304.
10. Höskuldsson A. PLS Regression Methods. Journal of Chemometrics, 1988;2:211-228.
11. Huang NE, Shen Z, Long SR. A New View of Nonlinear Water Waves: The Hilbert Spectrum. Annu. Rev. Fluid Mech. 1999; 31:417-457. (Pubitemid 36186209)
12. McInerny SA, Dai Y. Basic Vibration Signal Processing for Bearing Fault Detection. IEEE Transactions on education 2003;46:149-156.
13. Jia RD, Mao ZH, Chang YQ. Soft sensing for pH value of raffinate solution based on nonlinear partial robust m-regression. Acta Automatia Sinicanb 2009:35:583-588.
14. Tang J, Zhao LJ, Yue H, Chai TY. Analysis of vibration signal of wet ball mill shell and soft sensoring for mill load. Journal of Northeastern University(Natural Science), 2010;31:1521-1524.