On Optimal Sensor Placement Criterion for Structural Health Monitoring with Representative Least Squares Method

Dong Sheng Li; Hong Nan Li; Claus Peter Fritzen

doi:10.4028/www.scientific.net/KEM.413-414.383

Paper Titles

Bayesian Logic Applied to Damage Assessment of a Smart Precast Concrete Element
p.351

Assessment, Strengthening and Validation of Prestressed Damaged Beams
p.359

Detection of Various Damages Based on Piezoceramic Optical Fiber Sensor
p.367

Applicaton of Modal Filtration for Damage Detection of Rotating Shaft
p.373

On Optimal Sensor Placement Criterion for Structural Health Monitoring with Representative Least Squares Method
p.383

FE Model Updating for Damage Detection – Application to a Welded Structure
p.393

Monitoring Vertical Loads on the Bearings of the High Coast Suspension Bridge
p.401

The Design of Piezoelectric Transducer for Structural Health Monitoring Using Longitudinal Vibration Modes
p.407

Particle Impact Damping in Two Dimensions
p.415

HomeKey Engineering MaterialsKey Engineering Materials Vols. 413-414On Optimal Sensor Placement Criterion for...

On Optimal Sensor Placement Criterion for Structural Health Monitoring with Representative Least Squares Method

Abstract:

A novel sensor placement criterion is proposed for structural health monitoring after five influencing criteria are critically reviewed. The objective of the proposed criterion is to achieve best identification of modal frequencies and mode shapes through almost unbiased estimation of modal coordinates. The proposed criterion derived by the Representative Least Squares method depends on both the characteristics and the actual loading situations of a structure. It selects sensor positions with the best subspace approximation of the vibration responses from the linear space spanned by the mode shapes. Furthermore, the connection between the Effective Independence and the approximate Representative Least Squares estimator is obtained through matrix perturbation analysis. It is found that the Effective Independence is a step-by-step approximation to that of the Representative Least Squares criterion.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Key Engineering Materials (Volumes 413-414)

Pages:

383-391

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.413-414.383

Citation:

Cite this paper

Online since:

June 2009

Authors:

Dong Sheng Li, Hong Nan Li, Claus Peter Fritzen

Keywords:

Condition Number, Effective Independence, Optimal Sensor Placement, Representative Least Squares Method, Structural Health Monitoring (SHM)

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] D.S. Li, H.N. Li, and C.P. Fritzen: Journal of Sound and Vibration. Vol. 305(2007), p.945.

Google Scholar

[2] M. Papadopoulos and E. Garcia: AIAA Journal. Vol. 36(1998), p.256.

Google Scholar

[3] D.S. Li, H.N. Li, and C.P. Fritzen, in: Proceedings of the 3rd International Conference on Structural Health Monitoring and Intelligent Infrastructure, edited by B. Bakht, A. Mufti, November 13-16, 2007, Vancouver, Canada.

Google Scholar

[4] X.L. Guo, D.S. Li: Structural Engineering and Mechanics. Vol. 18, (2004), p.791.

Google Scholar

[5] D.S. Li, H.N. Li, and X.L. Guo, in: Proceedings of SPIE - Volume 5049, Smart Structures and Materials, edited by R.C. Smith, p.742, (2003).

Google Scholar

[6] T.G. Carne, C.R. Dohrmann, in : Proceedings of the 13th IMAC, p.927, (1995).

Google Scholar

[7] J.E.T. Penny, M.I. Friswell and G.D. Garvey : AIAA Journal. Vol. 32, (1994), p.407.

Google Scholar

[8] R.J. Allemang and D.L. Brown, in: Proceedings of the IMAC, 1982; 110-116.

Google Scholar

[9] D.J. Ewins: Modal Testing: Theory, Practice, and Application (Research Studies Press, 2000).

Google Scholar

[10] D.S. Li, H.N. Li, and C.P. Fritzen, in: Proceedings of the IMAC, Paper No. 78, (2008).

Google Scholar

[11] D.J. Inman: Vibration with Control Theory (John Wiley & Sons, Ltd, U.S.A. 2006).

Google Scholar

[12] D.C. Kammer: Journal of Guidance Control and Dynamics, Vol. 14, (1991), p.251.

Google Scholar

[13] C.R. Pickrel: Mechanical Systems and Signal Processing, Vol. 13, (1999), p.271.

Google Scholar

[14] G.H. Golub, C.F. Van Loan: Matrix computations. 3rd ed. (Johns Hopkins University Press, U.S.A. 1996).

Google Scholar

[15] D.S. Li, H.N. Li, and C.P. Fritzen: Mechanical Systems and Signal Processing, Vol. 23, (2009), p.1160.

Google Scholar