Identification of fault frequency variation in the envelope spectrum in the vibration-based local damage detection in possible changing load/speed conditions

被引:2
作者
Kuzio, Daniel [1 ]
Zimroz, Radoslaw [1 ]
Wylomanska, Agnieszka [2 ]
机构
[1] Wroclaw Univ Sci & Technol, Fac Geoengn Min & Geol, Grobli 15, PL-50421 Wroclaw, Poland
[2] Wroclaw Univ Sci & Technol, Fac Pure & Appl Math, Hugo Steinhaus Ctr, Hoene Wronskiego 13c, PL-50376 Wroclaw, Poland
关键词
Vibration signal; Local damage; Varying speed; Cycle detection; Statistical analysis; ELEMENT BEARING DIAGNOSTICS; NOISE;
D O I
10.1016/j.measurement.2023.113148
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The problem of local damage diagnosis (based on the detection of impulsive and periodic signals) is discussed. Both features should be checked, as fault frequency must be linked to the true value calculated for a given machine and speed. The precise estimation of the fault frequency is hard due to several factors. If a speed fluctuation exists, it is solved by order analysis. A wider perspective is proposed here, namely, an automatic statistical approach to analyze the distribution of estimated fault frequencies. We propose a procedure to evaluate whether the fault frequency is constant or not. The algorithm uses frequency estimation based on peak detection in the envelope spectrum and statistical testing. We present simulation studies and industrial examples. We have found that if the fault frequency is not constant and its distribution does not follow Gaussian shape with minor variance, then one should use more advanced techniques, e.g. order analysis.
引用
收藏
页数:16
相关论文
共 42 条
[1]  
Abramowitz M., 1965, Handbook of Mathematical Functions
[2]  
[Anonymous], 1989, Ames Iowa State Univ Press Iowa
[3]   CS2 analysis in presence of non-Gaussian background noise - Effect on traditional estimators and resilience of log-envelope indicators [J].
Borghesani, P. ;
Antoni, J. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 90 :378-398
[4]   A new procedure for using envelope analysis for rolling element bearing diagnostics in variable operating conditions [J].
Borghesani, P. ;
Ricci, R. ;
Chatterton, S. ;
Pennacchi, P. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 38 (01) :23-35
[5]   Cyclostationary processes: Application in gear faults early diagnosis [J].
Capdessus, C ;
Sidahmed, M ;
Lacoume, JL .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2000, 14 (03) :371-385
[6]  
Chaari F, 2012, SHOCK VIB, V19, P635, DOI [10.1155/2012/839420, 10.3233/SAV-2011-0656]
[7]  
Chen Y.-C., 2017, Biostatistics Epidemiology, V1, P161, DOI DOI 10.1080/24709360.2017.1396742
[8]   A novel tacholess order analysis method for bearings operating under time-varying speed conditions [J].
Choudhury, Madhurjya Dev ;
Hong, Liu ;
Dhupia, Jaspreet Singh .
MEASUREMENT, 2021, 186
[9]   An algorithm to diagnose ball bearing faults in servomotors running arbitrary motion profiles [J].
Cocconcelli, Marco ;
Bassi, Luca ;
Secchi, Cristian ;
Fantuzzi, Cesare ;
Rubini, Riccardo .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2012, 27 :667-682
[10]   Optimal filtering of gear signals for early damage detection based on the spectral kurtosis [J].
Combet, F. ;
Gelman, L. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (03) :652-668