Digital and Analog Communication Systems
Digital and Analog Communication Systems
Digital Signal Processing: A Computer-Based Approach
Digital Signal Processing: A Computer-Based Approach
An introduction to variable and feature selection
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Mires++: a reliable, energy-aware clustering algorithm for wireless sensor networks
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Interconnecting Smart Objects with IP: The Next Internet
Interconnecting Smart Objects with IP: The Next Internet
Three-way analysis of structural health monitoring data
Neurocomputing
Novelty detection in projected spaces for structural health monitoring
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
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Structural Health Monitoring (SHM) aims at monitoring buildings or other structures and assessing their condition, alerting about new defects in the structure when necessary. For instance, vibration measurements can be used for monitoring the condition of a bridge. We investigate the problem of extracting features from lightweight wireless acceleration sensors. On-line algorithms for frequency domain monitoring are considered, and the resulting features are combined to form a large bank of candidate features. We explore the feature space by selecting random sets of features and estimating probabilistic classifiers for damage detection purposes. We assess the relevance of the features in a large population of classifiers. The methods are assessed with real-life data from a wooden bridge model, where structural problems are simulated with small added weights.