Piezoelectric impedance based damage detection in truss bridges based on time frequency ARMA model

Recent progress and future trends on damage identification methods for bridge structures

“…Sen and Bhattacharya proposed an online health monitoring scheme that was utilized to synchronously estimate the system parameters along with the response states of a reduced‐order system based on dual extended Kalman filtering technique; location‐based structural properties are introduced as the system parameter so that the damage localization beyond sensor resolution can be conducted successfully; numerical results based on a truss bridge show that the proposed algorithm can locate damage beyond sensor resolution successfully. Fan et al proposed a new method to identify damage based on the time domain impedance response; a damage index based on singular value decomposition was defined by using the time frequency autoregressive moving average model; the high sensitivity and robustness of the proposed method for detecting the bolt damage in the gusset plates were verified based on an experimental model of a space steel truss bridge. Lin developed a crack localization method based on rotational frequency response functions obtained from measured translational frequency response function data; a crack location matrix was constructed using the estimated rotational frequency response functions to localize cracks, and a new numerical inverse frequency response function sensitivity method was proposed to identify crack parameters such as crack depths; results based on a numerical cantilever truss structure show that the location and depth of the crack can be identified successfully even in the presence of 5% noise level.…”

Characterization of Ultrasound Energy Diffusion Due to Small-Size Damage on an Aluminum Plate Using Piezoceramic Transducers

“…For damage detection in an SHM system, a PZT (lead zirconate titanate) transducer is usually utilized as an actuator to generate ultrasonic waves along a structure, and other PZT transducers are used as sensors to detect the changes in both environmental and operational conditions [ 8 , 9 , 10 , 11 , 12 ] and structural damages [ 13 , 14 , 15 , 16 , 17 , 18 ]. The damage-induced changes in properties such as electromechanical impedance [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], ultrasonic energy [ 29 , 30 , 31 , 32 , 33 , 34 ], nonlinear characteristics of Lamb waves [ 35 , 36 , 37 , 38 ], and other ultrasonic parameters [ 39 , 40 ], are further employed to estimate the health state of the structure [ 41 , 42 , 43 , 44 , 45 , 46 ] or locate the damage [ 47 , 48 , 49 , 50 , 51 ]. However, previous studies of damage detection mainly focus on how to make use of these structural changes to estimate or locate the damage, but do not consider the ultrasonic changes which are brought about by structural damage.…”

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

“…These methods rely on the well-established statistical concepts instead of human expertise to extract features that change with the onset of damage [37], which eliminates possible individual biases and requires very few assumptions regarding the physical structure. This method is represented by the Auto-Regressive (AR) family method such as the AR or Auto-Regressive Moving Average (ARMA) models [37][38][39][40], AR model with exogenous inputs (ARX) [41,42], Auto-Regressive Moving Average Vector (ARMAV) model [43], vector autoregressive (ARV) models [44], and the time frequency autoregressive moving average (TFARMA) model [45]. The ARMA or other similar models are used to model the time-domain vibration signals obtained from the structure, and then the model coefficients estimated using statistical methods are used to identify the system dynamic parameters and to extract features that indicate the damage occurrence.…”