Optimal Sensor Placement for Spatial Structure Based on Importance Coefficient and Randomness

The current methods of optimal sensor placement are majorly presented based on modal analysis theory, lacking the consideration of damage process of the structure. The effect of different minor damage cases acting on the total spatial structure is studied based on vulnerability theory in structural analysis. The concept of generalized equivalent stiffness is introduced and the importance coefficient of component is defined. For numerical simulation, the random characteristics for both structural parameters and loads are considered, and the random samples are established. The damage path of each sample is calculated and all the important members on the damage failure path are listed; therefore the sensor placement scheme is determined according to the statistical data. This method is extended to dynamic analysis. For every dynamic time-history analysis, time-varying responses of the structure are calculated by selecting appropriate calculating interval and considering the randomness of structural parameters and load. The time-varying response is analyzed and the importance coefficient of members is sorted; finally the dynamic sensor placement scheme is determined. The effectiveness of the method in this paper is certified by example.

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

[2]  Samuel H. Huang,et al.  System health monitoring and prognostics — a review of current paradigms and practices , 2006 .

[3]  M. Papadopoulos,et al.  Sensor placement methodologies for dynamic testing , 1998 .

[4]  C. Allin Cornell,et al.  Probabilistic seismic demand analysis of nonlinear structures , 1999 .

[5]  Christopher C. Flanigan,et al.  Automated selection of accelerometer locations for modal survey tests , 1992 .

[6]  Dan M. Frangopol,et al.  Predictive Analysis by Incorporating Uncertainty through a Family of Models Calibrated with Structural Health-Monitoring Data , 2013 .

[7]  A. Noor,et al.  Continuum Modeling of Large Lattice Structures: Status and Projections , 1988 .

[8]  Masanobu Shinozuka,et al.  Nonlinear Static Procedure for Fragility Curve Development , 2000 .

[9]  Seamus D. Garvey,et al.  Automatic choice of measurement locations for dynamic testing , 1994 .

[10]  Mitra Fouladirad,et al.  A methodology for probabilistic model-based prognosis , 2013, Eur. J. Oper. Res..

[11]  Charles R. Pickrel A PRACTICAL APPROACH TO MODAL PRETEST DESIGN , 1999 .

[12]  Jitendra Agarwal,et al.  Vulnerability of 3-dimensional trusses , 2001 .

[13]  Chung-Yue Wang,et al.  Nonlinear Dynamic Analysis of Reticulated Space Truss Structures , 2006 .

[14]  Michael Link,et al.  AN APPROACH TO OPTIMAL PICK-UP AND EXCITER PLACEMENT , 1996 .

[15]  Hong-Nan Li,et al.  Methodology Developments in Sensor Placement for Health Monitoring of Civil Infrastructures , 2012, Int. J. Distributed Sens. Networks.

[16]  Hoon Sohn,et al.  A review of structural health monitoring literature 1996-2001 , 2002 .

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

[18]  H Y Kim,et al.  STATISTICAL ANALYSIS OF FRAGILITY CURVES , 2000 .

[19]  Keith Worden,et al.  Overview of optimal sensor location methods for damage detection , 2001, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

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

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

[22]  Feng Fan,et al.  Failure mechanisms of single-layer reticulated domes subjected to earthquakes , 2007 .

[23]  Terje Haukaas,et al.  Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion , 2008, Reliab. Eng. Syst. Saf..

[24]  David I Blockley,et al.  The vulnerability of structures to unforeseen events , 2008 .

[25]  John William Smith Structural Robustness Analysis and the Fast Fracture Analogy , 2006 .