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Articles 1 - 2 of 2
Full-Text Articles in Signal Processing
Structural Health Monitoring Of Pipelines In Radioactive Environments Through Acoustic Sensing And Machine Learning, Michael Thompson
Structural Health Monitoring Of Pipelines In Radioactive Environments Through Acoustic Sensing And Machine Learning, Michael Thompson
FIU Electronic Theses and Dissertations
Structural health monitoring (SHM) comprises multiple methodologies for the detection and characterization of stress, damage, and aberrations in engineering structures and equipment. Although, standard commercial engineering operations may freely adopt new technology into everyday operations, the nuclear industry is slowed down by tight governmental regulations and extremely harsh environments. This work aims to investigate and evaluate different sensor systems for real-time structural health monitoring of piping systems and develop a novel machine learning model to detect anomalies from the sensor data. The novelty of the current work lies in the development of an LSTM-autoencoder neural network to automate anomaly detection …
Detecting Structural Defects Using Novel Smart Sensory And Sensor-Less Approaches, Amin Baghalian
Detecting Structural Defects Using Novel Smart Sensory And Sensor-Less Approaches, Amin Baghalian
FIU Electronic Theses and Dissertations
Monitoring the mechanical integrity of critical structures is extremely important, as mechanical defects can potentially have adverse impacts on their safe operability throughout their service life. Structural defects can be detected by using active structural health monitoring (SHM) approaches, in which a given structure is excited with harmonic mechanical waves generated by actuators. The response of the structure is then collected using sensor(s) and is analyzed for possible defects, with various active SHM approaches available for analyzing the response of a structure to single- or multi-frequency harmonic excitations. In order to identify the appropriate excitation frequency, however, the majority of …