Multichannel Processing of Noisy Vibration Responses: A Constrained Subspace Approach

In this paper we discuss multiple input/multiple output (MIMO) constrained subspace identification techniques that will be evaluated when applied to the fundamental problem of identification of a dynamic structural model from noisy vibrational response measurements. The structure is a cylindrical copper pipe consisting of three (3) accelerometers positioned along its length as well as a single transducer measuring the excitation function (chirp or white noise) totaling ten (10) sensor channels (9 outputs and a single input). Here we discuss a suite of "constrained" subspace identification techniques and evaluate their performance on experimental data.

[1]  Thomas Kailath,et al.  Linear Systems , 1980 .

[2]  V. Verdult,et al.  Filtering and System Identification: A Least Squares Approach , 2007 .

[3]  P. Kalata,et al.  The tracking index: A generalized parameter for α-β and α-β-γ target trackers , 1983, The 22nd IEEE Conference on Decision and Control.

[4]  B. Peeters,et al.  Stochastic System Identification for Operational Modal Analysis: A Review , 2001 .

[5]  Wodek Gawronski,et al.  Advanced Structural Dynamics and Active Control of Structures , 2004 .

[6]  James V. Candy,et al.  Modal Frequency Identification of a Cylindrical Object from Noisy Vibrational Response Measurements , 2018 .

[7]  Β. L. HO,et al.  Editorial: Effective construction of linear state-variable models from input/output functions , 1966 .

[8]  Miguel C. Junger,et al.  Sound, Structures, and Their Interaction , 1972 .

[9]  J V Candy,et al.  Anomaly detection for a vibrating structure: A subspace identification/tracking approach. , 2017, The Journal of the Acoustical Society of America.

[10]  James V. Candy,et al.  Model-Based Signal Processing , 1985 .

[11]  J. Juang.  Applied system identification , 1994 .

[12]  Tohru Katayama,et al.  Subspace Methods for System Identification , 2005 .

[13]  H. Zeiger,et al.  Approximate linear realizations of given dimension via Ho's algorithm , 1974 .

[14]  P. Faurre.  Stochastic Realization Algorithms , 1976 .

[15]  James Candy.  Model-Based Processing: An Applied Subspace Identification Approach , 2019 .

[16]  Michael R. Hatch,et al.  Vibration Simulation Using MATLAB and ANSYS , 2000 .