In the past few years, intelligent structural damage identification algorithms based on machine learning techniques have been developed and obtained considerable attentions worldwide, due to the ad...

https://journals.sagepub.com/doi/pdf/10.1177/1475921718804132

A novel deep learning-based method for damage identification of smart building structures:

Structural health monitoring using modal strain energy damage indicator coupled with teaching-learning-based optimization algorithm and isogoemetric analysis

Size-dependent isogeometric analysis of functionally graded carbon nanotube-reinforced composite nanoplates

Fast simulations for solving fracture mechanics inverse problems using POD-RBF XIGA and Jaya algorithm

Modal identification and damage detection in beam-like structures using the power spectrum and time-frequency analysis

A robust damage detection method based on multi-modal analysis in variable temperature conditions

An algorithm to assess transversal cracks in composite structures based on natural frequency changes due to damage is proposed. The damage assessment is performed in two steps; first the crack location is found, and afterwards an evaluation of its severity is performed. The technique is based on a mathematical relation that provides the exact solution for the frequency changes of bending vibration modes, considering two terms. The first term is related to the strain energy stored in the beam, while the second term considers the increase of flexibility due to damage. Thus, it is possible to separate the problems of localization and severity assessment, which makes the localization process independent of the beams cross-section shape and boundary conditions. In fact, the process consists of comparing vectors representing the measured frequency shifts with patterns constructed using the mode shape curvatures of the undamaged beam. Once the damage is localized, the evaluation of its severity is made taking into account the global rigidity reduction. The damage identification algorithm was validated by experiments performed on numerous sandwich panel specimens.

/pdf/localization-of-transversal-cracks-in-sandwich-beams-and-4yyy789pu5.pdf

Localization of transversal cracks in sandwich beams and evaluation of their severity

THIS PAPER INTRODUCES A METHOD TO IDENTIFY DAMAGES IN BEAM-LIKE STRUCTURES BY ANALYZING THE NATURAL FREQUENCY CHANGES OF THE FIRST SIX TRANSVERSAL VIBRATION MODES. A CORRELATION BETWEEN THE DAMAGE LOCATION AND FREQUENCY CHANGE IS ESTABLISHED FOR EACH MODE SEPA-RATELY, BY CONSIDERING THE MODAL STRAIN ENERGY STORED IN THAT LOCA-TION. THE MATHEMATICAL RELATION DESCRIBING THIS CORRELATION IS USED TO CHARACTERIZE THE DYNAMIC BEHAVIOR OF A BEAM WITH A DAMAGE OF KNOWN POSITION AND TO DERIVE ITS DAMAGE LOCATION INDICATOR (DLI) AS A SIX-TERM VECTOR. THE METHOD CONSISTS IN COMPARING THE VEC-TORS DESCRIBING THE DAMAGE AT ANY POSSIBLE LOCATION ALONG THE BEAM WITH THE DAMAGE SIGNATURE (DS), WHICH IS ACHIEVED FROM THE MEASUREMENTS THAT COMPARE THE BEAMÂS FREQUENCIES IN HEALTHY AND DAMAGED STATE. A MODIFIED KULLBACK-LEIBLER DIVERGENCE IS USED TO ASSESS THE DAMAGE LOCATION. IN ORDER TO PERMIT EARLY DAM-AGE ASSESSMENT, AN IMPROVED FREQUENCY EVALUATION ALGORITHM WAS DEVELOPED. IT IS BASED ON SIGNAL TRUNCATION AND CONSEQUENT SPECTRAL LINES REARRANGEMENT, IN ORDER TO ACCURATELY FIND THE STRONGEST SPECTRAL COMPONENTS. THE EFFECTIVENESS OF THE PROPOSED METHOD IS DEMONSTRATED BY SIMULATIONS AND EXPERIMENTS.

/pdf/early-structural-damage-assessment-by-using-an-improved-4i45e2m40m.pdf

Gilbert-Rainer Gillich

Papers

Modal identification and damage detection in beam-like structures using the power spectrum and time-frequency analysis

A robust damage detection method based on multi-modal analysis in variable temperature conditions

Localization of transversal cracks in sandwich beams and evaluation of their severity

Early structural damage assessment by using an improved frequency evaluation algorithm

The use of virtual instruments in engineering education