Optimal sensor placement for structural health monitoring based on multiple optimization strategies

SUMMARY Careful selection and placement of sensors are the critical issue in the construction and implementation of an effective structural health monitoring system. A hybrid method termed the optimal sensor placement strategy (OSPS) based on multiple optimization methods is proposed in this paper. The initial sensor placement is firstly obtained by the QR factorization. Then, using the minimization of the off-diagonal elements in the modal assurance criterion matrix as a measure of the utility of a sensor configuration, the quantity of the sensors is determined by the forward and backward sequential sensor placement algorithm together. Finally, the locations of the sensor are determined by the dual-structure coding-based generalized genetic algorithm (GGA). Taking the scientific calculation software matlab (MathWorks, Natick, MA, USA) as a platform, an OSPS toolbox, which is working as a black box, is developed based on the command-line compiling and graphical user interface-aided graphical interface design. The characteristic and operation method of the toolbox are introduced in detail, and the scheme selection of the OSP is carried out on the world's tallest TV tower (Guangzhou New TV Tower) based on the developed toolbox. The results indicate that the proposed method is effective and the software package has a friendly interface, plenty of functions, good expansibility and is easy to operate, which can be easily applied in practical engineering. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  R. Guyan Reduction of stiffness and mass matrices , 1965 .

[2]  Yozo Fujino,et al.  Structural Control and Health Monitoring , 2009 .

[3]  Daniel C. Kanner Sensor Placement for On-Orbit Modal Identification and Correlation of Large Space Structures , 1990 .

[4]  Dongsheng Li,et al.  The connection between effective independence and modal kinetic energy methods for sensor placement , 2007 .

[5]  Tv Tower Wind tunnel force balance test and wind-induced responses of the Guangzhou New TV Tower structure I:wind tunnel test , 2009 .

[6]  M. Friswell,et al.  Model reduction using dynamic and iterated IRS techniques , 1995 .

[7]  Mircea Grigoriu,et al.  Optimal design of sensor networks for vehicle detection, classification, and monitoring , 2006 .

[8]  T. K. Gangopadhyay,et al.  Fibre Bragg gratings in structural health monitoring—Present status and applications , 2008 .

[9]  Costas Papadimitriou,et al.  Optimal sensor placement methodology for parametric identification of structural systems , 2004 .

[10]  Michele Meo,et al.  On the optimal sensor placement techniques for a bridge structure , 2005 .

[11]  Liang Shuo Experimental studies on multi-column out-plane buckling in bottom open-space region of the Guangzhou New TV Tower , 2010 .

[12]  Tv Tower,et al.  SHAKING TABLE TEST FOR THE STRUCTRAL MODEL OF GUANGZHOU NEW TV TOWER , 2008 .

[13]  R. Montes-Iturrizaga,et al.  Optimal instrumentation of structures on flexible base for system identification , 1999 .

[14]  Pol D. Spanos,et al.  Probabilistic engineering mechanics , 1992 .

[15]  M. Salama,et al.  Optimal placement of excitations and sensors for verification of large dynamical systems , 1987 .

[16]  Kenneth T. V. Grattan,et al.  Monitoring of an all-composite bridge using Bragg grating sensors , 2007 .

[17]  Gangbing Song,et al.  Recent applications of fiber optic sensors to health monitoring in civil engineering , 2004 .

[18]  Chinchao Liu,et al.  Sensor placement for time-domain modal parameter estimation , 1996 .

[19]  D. Kammer Sensor Placement for On-Orbit Modal Identification and Correlation of Large Space Structures , 1990, 1990 American Control Conference.

[20]  Edward J. Kuhar,et al.  Dynamic Transformation Method for Modal Synthesis , 1974 .

[21]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[22]  Michael L. Tinker,et al.  Optimal placement of triaxial accelerometers for modal vibration tests , 2002 .

[23]  Pei-Ling Chiu,et al.  A near-optimal sensor placement algorithm to achieve complete coverage-discrimination in sensor networks , 2005, IEEE Communications Letters.

[24]  Tan Ping Study on wind-resistant dynamic reliability of TMD with limited spacing , 2009 .

[25]  Helmut Wenzel,et al.  Health monitoring of bridges , 2009 .

[26]  Clark R. Dohrmann,et al.  A modal test design strategy for model correlation , 1994 .

[27]  Yi-Qing Ni,et al.  Technology innovation in developing the structural health monitoring system for Guangzhou New TV Tower , 2009 .

[28]  Kyriacos Kalli,et al.  Fibre Bragg Gratings , 2006 .