Fast Time-varying modal parameter identification algorithm based on two-layer linear neural network learning for subspace tracking
Автор: Kai Yang, Kaiping Yu
Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb
Статья в выпуске: 1 vol.3, 2011 года.
Бесплатный доступ
The key of fast identification algorithm of time-varying modal parameter based on subspace tracking is to find efficient and fast subspace-tracking algorithm. This paper presents a modified version of NIC(Novel Information Criterion) adopted in two-layer linear neural network learning for subspace tracking, which is applied in time-varying modal parameter identification algorithm based on subspace tracking and get a new time-varying modal parameter identification algorithm. Comparing with the original subspace-tracking algorithm, there is no need to set a key control parameter in advance. Simulation experiments show that new time-varying modal parameter identification algorithm has a faster convergence in the initial period and a real experiment under laboratory conditions confirms further its validity of the time-varying modal identification algorithm presented in this paper.
Subspace tracking, time-varying modal parameter, identification algorithm, neural network learning
Короткий адрес: https://sciup.org/15013061
IDR: 15013061
Список литературы Fast Time-varying modal parameter identification algorithm based on two-layer linear neural network learning for subspace tracking
- Zou Jingxiang, Yu Kaiping and Pang Shiwei. Methods of time-varying structural parameter identification[J]. Advances in mechanics, 2000, 30(3):370-377
- Kefu Liu . Extension of modal analysis to linear time-varying system[J] . Journal of Sound and Vibration, 1999, 226(1):149-167
- Kefu Liu . Identification of linear time-varying system[J] . Journal of Sound and Vibration, 1997,206(4):487-505
- Juang J N and Pappa R S . An eigensystem realization algorithm for modal parameter identification and model reduction[J] . Journal of Guidance, Control and Dynamic, 1985,8(5):620-627
- Longman R W and Juang J N . Recursive form of the Eigensystem Realization algorithm for system identification[J] . Journal of Guidance, Control and Dynamic, 1989, 12(5):647-652
- Yu Kaiping, Xie Lili, Fan Jiuming et.al . A parameter identification of simple supported beams system carrying a moving mass[J] . Earthquake engineering and engineering vibration, 2002, 22(5):14-17
- Pang Shiwei, Yu Kaiping and Zou Jingxiang . Improved subspace method with application in linear tie-varying structural modal parameter indentification[J] . Chinese Journal of applied mechanics, 2005, 22(2):184-189
- Yang Lifang, Yu Kaiping, Pang Shiwei et. al . Comparison study on identification methods applied to linear time-varying structures[J] . Journal of Vibration and Shock, 2007,26(3):8-12
- F Tasker, A Bosse, S Fisher . Real-time modal parameter estimation using subspace methods:theory[J] . Mechanical Systems and Signal Processing,1998,12(6):797-808
- A Bosse, F Tasker, S Fisher . Real-time modal parameter estimation using subspace methods: application[J] . Mechanical Systems and Signal Processing, 1998, 12(6):809-823
- E M Dowling, L P Ammann and R D Degroat . A TQR-iteration based adaptive SVD for real time angel and frequency tracking[J] . IEEE Transactions on Signal Processing, 1994,42(4):914-926
- Wu Riqiang, Yu Kaiping and Zou Jingxiang . An improved subspace method and its application to parameter identification of time-varying structures[J] . Engineering Mechaics，2002，19(4):67-70
- Michel Verhaegen , Xiaode Yu . A class of subspace model identification algorithms to identify periodically and arbitrarily time-varying systems[J] . Automatica, 1995, 31:201-216
- Hiroshi Oku and Hidenori Kimura . Recursive 4SID algorithms using gradient type subspace tracking[J] . Automatica, 2002,38:1035-1043
- Pang Shiwei, Yu Kaiping and Zou Jingxiang. A projection approximation recursive subspace method for identification of modal parameter of time-varying structures [J]. Engineering Mechanics, 2002, 22(5):115-119
- Pang Shiwei, Yu Kaiping and Zou Jingxiang . Time-varying system identification using recursive subspace method based on free response data[J] . Journal of Vibration Engineering,2005, 18(2):233-237
- Bin Yang . Projection Approximation subspace tracking[J] . IEEE Transactions of Signal Processing, 1995, 43(1):95-107
- K Abed-Meraim, A Chkeif and Y Hua . Fast orthonormal PAST algorithm[J] . IEEE Signal Processing Letters, 2000, 7(3):60-62
- Bin Yang . An extension of the PASTd algorithm to both rank and subspace tracking[J] . IEEE Signal Processing Letters, 1995, 2(9):179-182
- Imran Ali, Doug Nyun Kim and Taikyeong Ted Jeong . A new subspace tracking algorithm using approximation of Gram-Schmidt procedure . In: 2009 International Conference on Information and Multimedia Technology, 2009, 245-248
- Yingbo Hua, Yong Xiang, Tianping Chen and so on . A new look at the power method for fast subspace tracking [J]. Digital Signal Processing, 1999,9:297-314
- Yingbo Hua, Yong Xiang, Tiangping Chen, Karim Abedmeraim et al . Natural power method for fast subspace tracking . In:Proceeding of the 1999 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing, 1999, 176-185
- Roland Badeau, Bertrand David and Gael Richard . Fast approximated power iteration subspace tracking[J] . IEEE Transactions on Signal Processing, 2005, 53(8):2391-2341
- Yongfeng Miao and Yingbo Hua . Fast Subspace Tracking by a Novel Information Criterion . Signals, Systems and Computer, the Thirty-First Asilomar Conference, 1997, vol2:1312-1316
- Yongfeng Miao and Yingbo Hua . Fast Subspace Tracking and Neural Network Learing by a Novel Information Criterion . IEEE Transactions on Signal Processing, 1998,46(7):1967-1979
- Amir Valizadeh, Mehdi Farrokhrooz and Ali Rafiei . Fast Signal Subspace Tracking Using Two-Layer Linear Neural Network Learning. 16th Mediterranean Conference on Control and Automation . France, 2008:1828-1832
- E Esmailzadeh and M Ghorashi . Vibraton analysis of beams traversed by uniform partially distributed moving masses[J] . Journal of Sound and Vibration, 1995, 184(1):9-17
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