Methodologies of Damage Identification Using Non-Linear Data-Driven Modelling

Arredondo, Miguel Angel Torres; Burgos, Diego Alexander Tibaduiza; Buethe, Inka; Mujica, Luis Eduardo; Vejar, Maribel Anaya; Rodellar, José; Fritzen, Claus‐Peter

doi:10.4018/978-1-4666-5888-2.ch093

Cited by 1 publication

(1 citation statement)

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“…[46,47] During each actuation phase, a PZT transducer is defined as an actuator and a known signal is applied to the structure through this transducer; this electric signal is then converted into a vibration signal that travels over the structure and interacts with elements and damages in the structure. [48,49] After that, the propagated signals are collected from the rest of the sensors in the sensor network, these data is preprocessed with the DWT in order to obtain a lower dimensional representation of the information to reduce the computational cost of the training algorithm and make feasible its real implementation. This step can be seen as a feature extraction scheme.…”

Section: Training Stepmentioning

confidence: 99%

An acousto-ultrasonics approach for probabilistic modelling and inference based on Gaussian processes

Torres-Arredondo

Burgos

2018

Struct Control Health Monit

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Summary In recent years, there has been an increasing interest in employing and analysing complex ultrasonic waves for the purpose of designing health monitoring systems for guaranteeing the safe structural operation by means of early damage prognosis strategies and reducing the costs of maintenance and downtimes. For this reason, monitoring systems are essential and require highly efficient techniques providing a probabilistic interpretation of their diagnostics. On that account, a Bayesian framework within the context of Gaussian processes is adopted in the present work for the purpose of probabilistic data‐driven modelling and damage detection. A network of permanently installed piezoelectric sensors in a pitch‐catch configuration is used for collecting the propagated ultrasonic waves together with the discrete wavelet transform for feature extraction purposes and matrix unfolding procedures such as the ones used in the monitoring of batch processes for sensor data fusion. The effectiveness of the proposed methodology is experimentally evaluated in three different composite structures. Receiver operating characteristics are used as a statistical measure to assess the damage detection capabilities of the presented method.

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Section: Training Stepmentioning

confidence: 99%