Damage detection in frame structures using noisy accelerometers and Damage Load Vectors (DLV)

In the area of damage detection, there have been many notable methods introduced in the past years. Damage Load Vectors (DLV) is among the most powerful methods, which computes a set of load vectors from variations in flexibility matrices of a frame in the undamaged and damaged conditions. These flexibility matrices are derived from acceleration responses of the frame which can be captured using accelerometers. The DLV method then scrutinizes this shift among the flexibility matrices, which ultimately enables locating the damaged member(s). This study holistically conducted seven experimental tests, with seven damage scenarios of a test frame installed on a semi-harmonic shaking table. The DLV method was subsequently employed to locate the damaged members using recorded frame vibration data obtained from ‘noisy’ accelerometers positioned on the frame at eight predefined locations. The Eigen Realization Algorithm (ERA) alongside Pandy’s recommendations were adapted herein to facilitate generation of accurate flexibility matrices derived from the noisy accelerometers. The outcome is very encouraging with accurate identification of damaged members in all seven damage scenarios without any ‘positive-false’ and ‘negative-false’ findings. Additionally, there is a decrease (from 0.045 to 0.289) in the accuracy of WSI index when the number of damaged members is increased.