… the neural network to the FRF based structural damage detection. The … damage cases (ie,
trained damage cases and unseen damage cases, single damage cases and multiple-damage …

… noise levels on the damage detection results are discussed. … have been widely applied for
damage detection, as the modal … Artificial Neural Networks (ANN) have been utilized by many …

… To overcome these challenges, this article proposes a vision‐based method using a deep
architecture of convolutional neural networks (CNNs) for detecting concrete cracks without …

… feasibility of using artificial neural network in conjunction with system identification techniques
to detect the existence and to identify the characteristics of damage in composite structures…

… The next section of this paper presents a brief description of neural networks. Numerical
results illustrating the use of neural networks in detecting and identifying damages are pre…

… neural network (CPN) which has previously been used with static displacements for damage
detection. … less training time than would be needed for other neural network approaches. …

… neural network (CNN), which is one of the major breakthroughs in image recognition, to the
damage detection … simulated damaged and healthy cases and localize the damage when it …

… techniques developed so far require some information about the structure before damage …
damage detection method based on parameter identification using an iterative neural network (…

… In the present paper, damage detection is formulated as an inverse problem, and solved by
… sensitive neural networks. In the neural-network approach, possible damage and its extent is …

… dense sensor arrays, accurate damage diagnosis has become computationally … neural
network (CNN), which has led to breakthrough results in computer vision, to the damage detection …