Gearbox Fault Features Extraction Using Vibration Measurements and Novel Adaptive Filtering Scheme

被引:4
作者
Ibrahim, Ghalib R. [1 ]
Albarbar, A. [2 ]
机构
[1] Univ Anbar, Dept Mech Engn, Coll Engn, Anbar, Iraq
[2] Manchester Metropolitan Univ, Sch Engn, Adv Ind Diagnost Ctr, Manchester M1 5GD, Lancs, England
关键词
D O I
10.1155/2012/283535
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Vibration signals measured from a gearbox are complex multicomponent signals, generated by tooth meshing, gear shaft rotation, gearbox resonance vibration signatures, and a substantial amount of noise. This paper presents a novel scheme for extracting gearbox fault features using adaptive filtering techniques for enhancing condition features, meshing frequency sidebands. A modified least mean square (LMS) algorithm is examined and validated using only one accelerometer, instead of using two accelerometers in traditional arrangement, as the main signal and a desired signal is artificially generated from the measured shaft speed and gear meshing frequencies. The proposed scheme is applied to a signal simulated from gearbox frequencies with a numerous values of step size. Findings confirm that 10-5 step size invariably produces more accurate results and there has been a substantial improvement in signal clarity (better signal-to-noise ratio), which makes meshing frequency sidebands more discernible. The developed scheme is validated via a number of experiments carried out using two-stage helical gearbox for a healthy pair of gears and a pair suffering from a tooth breakage with severity fault 1 (25% tooth removal) and fault 2 (50% tooth removal) under loads (0%, and 80% of the total load). The experimental results show remarkable improvements and enhance gear condition features. This paper illustrates that the new approach offers a more effective way to detect early faults.
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页数:7
相关论文
共 16 条
[1]  
Abdulmagid M., 2004, ANN RES J, V2
[2]   Acoustic monitoring of engine fuel injection based on adaptive filtering techniques [J].
Albarbar, A. ;
Gu, F. ;
Ball, A. D. ;
Starr, A. .
APPLIED ACOUSTICS, 2010, 71 (12) :1132-1141
[3]  
Bajic V., 2005, THESIS
[4]  
Barron, 1996, ENG COND MON PRACT M
[5]   Seeded fault detection on helical gears with acoustic emission [J].
Eftekharnejad, Babak ;
Mba, D. .
APPLIED ACOUSTICS, 2009, 70 (04) :547-555
[6]  
Fohl W, 2009, P 12 INT C DIG AUD E
[7]  
HAYKIN S, 1995, ADAPTIVE FILTER THEO
[8]   Subspace-based gearbox condition monitoring by kernel principal component analysis [J].
He, Qingbo ;
Kong, Fanrang ;
Yan, Ruqiang .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (04) :1755-1772
[9]   Comparison between Wigner-Ville distribution- and empirical mode decomposition vibration-based techniques for helical gearbox monitoring [J].
Ibrahim, G. R. ;
Albarbar, A. .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2011, 225 (C8) :1833-1846
[10]   Gearbox condition monitoring using self-organizing feature maps [J].
Liao, G ;
Liu, S ;
Shi, T ;
Zhang, G .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2004, 218 (01) :119-129