Print Email Facebook Twitter A new approach for structural health monitoring by applying anomaly detection on strain sensor data Title A new approach for structural health monitoring by applying anomaly detection on strain sensor data Author Trichias, K. Pijpers, R.J.M. Meeuwissen, H.B. Publication year 2014 Abstract Structural Health Monitoring (SHM) systems help to monitor critical infrastructures (bridges, tunnels, etc.) remotely and provide up-to-date information about their physical condition. In addition, it helps to predict the structure’s life and required maintenance in a cost-efficient way. Typically, inspection data gives insight in the structural health. The global structural behavior, and predominantly the structural loading, is generally measured with vibration and strain sensors. Acoustic emission sensors are more and more used for measuring global crack activity near critical locations. In this paper, we present a procedure for local structural health monitoring by applying Anomaly Detection (AD) on strain sensor data for sensors that are applied in expected crack path. Sensor data is analyzed by automatic anomaly detection in order to find crack activity at an early stage. This approach targets the monitoring of critical structural locations, such as welds, near which strain sensors can be applied during construction and/or locations with limited inspection possibilities during structural operation. We investigate several anomaly detection techniques to detect changes in statistical properties, indicating structural degradation. The most effective one is a novel polynomial fitting technique, which tracks slow changes in sensor data. Our approach has been tested on a representative test structure (bridge deck) in a lab environment, under constant and variable amplitude fatigue loading. In both cases, the evolving cracks at the monitored locations were successfully detected, autonomously, by our AD monitoring tool. Subject Communication & Information Building Engineering & Civil EngineeringPNS - Performance of Networks & Services SR - Structural ReliabilityTS - Technical SciencesBuildings and InfrastructureArchitectureBuilt EnvironmentStructural health monitoringAnomaly detectionDamage detectionCracksStrain sensors To reference this document use: http://resolver.tudelft.nl/uuid:3cd1a3bf-7904-405e-a788-f97f2242234f TNO identifier 499657 Source Proceedings of SPIE. Health monitoring of Structural and Biological Systems 2014, 1-11 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.