• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.31-38
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• 2003

In the present work, a nonlinear inverse perturbation method which has been used in the structural optimization, is adopted so as to identify the structural damages. Unlike the structural optimization, a larger number of constrained equations than the number of unknown parameters are often required detect structural damage. Therefore, nonlinear least squares method is utilized to solve the problem. Because only a limited number of sensors are available I real situation of damage detection, the determination of sensor location becomes one of the most important issues. Hence, this work concentrates on the issue of sensor placement in the framework of nonlinear inverse perturbation method, and the performances of various methodologies concerning to sensor placement are compared with each other. The comparisons show tat the successive elimination method gets good performance for sensor placement. From the several numerical studies, it is confirmed that the inverse perturbation method, combined with the successive elimination method, is very promising in structural damage detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.98-104
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• 2002

System condensation technique improves the efficiency of the inverse perturbation method of damage detection developed in the previous work. The technique is applied to transform the unmeasured DOFs to the measured DOFs. This approach makes it possible to eliminate the unmeasured DOFs, which accelerates the computational efficiency. The numerical instability problems due to the system condensation technique are also resolved by updating the transformation matrix for each step, and also by adopting the accelerated improved reduced system(AIRS) condensation method.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.637-646
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• 2003

In the previous study, the inverse perturbation method was used to identify structural damages. Because all unmeasured DOFs were considered as unknown variables, considerable computational effort was required to obtain reliable results. Thus, in the present study, a system condensation method is used to transform the unmeasured DOFs into the measured DOFs, which eliminates the remaining unmeasured DOFs to improve computational efficiency. However, there may still arise a numerically ill-conditioned problem, if the system condensation is not adequate for numerical Programming or if the system condensation is not recalibrated with respect to the structural changes. This numerical problem is resolved in the present study by adopting more accurate accelerated improved reduced system (AIRS) as well as by updating the transformation matrix at every step. The criterion on the required accuracy of the condensation method is also proposed. Finally, numerical verification results of the present accelerated inverse perturbation method (AIPM) are presented.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.938-945
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• 2003

In the present study, the inverse perturbation method is applied to the structural damage detection in conjunction with a system condensation technique. The system condensation technique is adopted to r esolve the problem due to the incomplete measurement of the degrees-of-freedom (DOFs) in a natural mode. However, the numerical difficulty may arise in the system condensation when the DOFs to be measured are not properly selected. Thus, the issue of sensor placement for structural damage detection, in the framework of the condensation technique-based inverse perturbation method, is considered in this study. Also, a methodology to measure the number of sensors required to obtain reliable damage detection is proposed and then verified through some illustrative example problem.