A diagnostic signal selection scheme for planetary gearbox vibration monitoring under non-stationary operational conditions

被引:45
作者
Feng, Ke [1 ]
Wang, KeSheng [1 ]
Zhang, Mian [1 ]
Ni, Qing [1 ]
Zuo, Ming J. [1 ,2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Mechatron Engn, Equipment Reliabil Prognost & Hlth Management Lab, Chengdu 611731, Peoples R China
[2] Univ Alberta, Dept Mech Engn, Edmonton, AB T6G 2G8, Canada
基金
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词
planetary gearbox; fault diagnosis; computed order tracking (COT); Vold-Kalman filter order tracking (VKF-OT); FAULT-DIAGNOSIS; ORDER TRACKING; ENTROPY;
D O I
10.1088/1361-6501/aa543e
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The planetary gearbox, due to its unique mechanical structures, is an important rotating machine for transmission systems. Its engineering applications are often in non-stationary operational conditions, such as helicopters, wind energy systems, etc. The unique physical structures and working conditions make the vibrations measured from planetary gearboxes exhibit a complex time-varying modulation and therefore yield complicated spectral structures. As a result, traditional signal processing methods, such as Fourier analysis, and the selection of characteristic fault frequencies for diagnosis face serious challenges. To overcome this drawback, this paper proposes a signal selection scheme for fault-emphasized diagnostics based upon two order tracking techniques. The basic procedures for the proposed scheme are as follows. (1) Computed order tracking is applied to reveal the order contents and identify the order(s) of interest. (2) Vold-Kalman filter order tracking is used to extract the order(s) of interest-these filtered order(s) constitute the so-called selected vibrations. (3) Time domain statistic indicators are applied to the selected vibrations for faulty information-emphasized diagnostics. The proposed scheme is explained and demonstrated in a signal simulation model and experimental studies and the method proves to be effective for planetary gearbox fault diagnosis.
引用
收藏
页数:10
相关论文
共 25 条
[1]  
[Anonymous], P SAE NOIS VIBR C TR
[2]   Vibration condition monitoring of planetary gearbox under varying external load [J].
Bartelmus, W. ;
Zimroz, R. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (01) :246-257
[3]   A new feature for monitoring the condition of gearboxes in non-stationary operating conditions [J].
Bartelmus, W. ;
Zimroz, R. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (05) :1528-1534
[4]   New focus on gearbox condition monitoring for failure prevention technology [J].
Bartelmus, Walter .
SMART DIAGNOSTICS V, 2014, 588 :184-191
[5]   Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis [J].
Bartelmus, Walter ;
Chaari, Fakher ;
Zimroz, Radoslaw ;
Haddar, Mohamed .
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS, 2010, 29 (04) :637-646
[6]   A survey of DSP methods for rotating machinery analysis, what is needed, what is available [J].
Blough, JR .
JOURNAL OF SOUND AND VIBRATION, 2003, 262 (03) :707-720
[7]  
Feng K., 2016, TECHNICAL REPORT
[8]   Iterative generalized synchrosqueezing transform for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions [J].
Feng, Zhipeng ;
Chen, Xiaowang ;
Liang, Ming .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2015, 52-53 :360-375
[9]   Fault diagnosis of wind turbine planetary gearbox under nonstationary conditions via adaptive optimal kernel time frequency analysis [J].
Feng, Zhipeng ;
Liang, Ming .
RENEWABLE ENERGY, 2014, 66 :468-477
[10]   Joint amplitude and frequency demodulation analysis based on local mean decomposition for fault diagnosis of planetary gearboxes [J].
Feng, Zhipeng ;
Zuo, Ming J. ;
Qu, Jian ;
Tian, Tao ;
Liu, Zhiliang .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 40 (01) :56-75