Supervised Distributed Multi-Instance and Unsupervised Single-Instance Autoencoder Machine Learning for Damage Diagnostics with High-Dimensional Data - A Hybrid Approach and Comparison Study
暂无分享,去创建一个
[1] Peter Wierach,et al. Mode Selective Actuator-Sensor System for Lamb Wave-Based Structural Health Monitoring , 2014 .
[2] Martin Ester,et al. Density‐based clustering , 2019, WIREs Data Mining Knowl. Discov..
[3] Kaushal K. Shukla,et al. Efficient Algorithms for Discrete Wavelet Transform , 2013, SpringerBriefs in Computer Science.
[5] Lian Duan,et al. A Local Density Based Spatial Clustering Algorithm with Noise , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.
[6] J. Michaels,et al. Feature Extraction and Sensor Fusion for Ultrasonic Structural Health Monitoring Under Changing Environmental Conditions , 2009, IEEE Sensors Journal.
[7] Maria Moix-Bonet,et al. Damage Introduction, Detection, and Assessment at CFRP Door Surrounding Panel , 2016 .
[8] Rana Fayyaz Ahmad,et al. Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques , 2015, Australasian Physical & Engineering Sciences in Medicine.
[9] Hoon Sohn,et al. Structural health monitoring system design using finite element analysis , 2002, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.
[10] Xia Zhao,et al. Distributed structural health monitoring system based on smart wireless sensor and multi-agent technology , 2006 .
[11] J. Rose. Ultrasonic Waves in Solid Media , 1999 .
[12] Armin Lechleiter,et al. A hybrid approach for Structural Monitoring with self-organizing multi-agent systems and inverse numerical methods in material-embedded sensor networks , 2016 .
[13] Charles R. Farrar,et al. Machine learning algorithms for damage detection under operational and environmental variability , 2011 .
[14] Francesc Pozo,et al. Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications , 2020, Sensors.
[15] Michael Giering,et al. Deep Learning for Structural Health Monitoring : A Damage Characterization Application , 2016 .
[16] Roger M. Groves,et al. DeepSHM: a deep learning approach for structural health monitoring based on guided Lamb wave technique , 2019, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.
[17] Hui Li,et al. Computer vision and deep learning–based data anomaly detection method for structural health monitoring , 2019 .
[18] Luis Roseiro,et al. Neural networks in damage detection of composite laminated plates , 2005 .