Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 87, Issue -, Pages 384-400Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2016.10.033
Keywords
Structural Health Monitoring; Power Spectral Density; Spectral Moment; Clustering; Anomaly Detection; k-means-
Categories
Funding
- Roads and Maritime Services (RMS) in New South Wales, Australia
- Australian Government through the Department of Communications
- Australian Research Council through the ICT Centre of Excellence Program
Ask authors/readers for more resources
This paper presents the results of a large scale Structural Health Monitoring application on the Sydney Harbour Bridge in Australia. This bridge has many structural components, and our work focuses on a subset of 800 jack arches under the traffic lane 7. Our goal is to identify which of these jack arches (if any) respond differently to the traffic input, due to potential structural damages or instrumentation issues. We propose a novel non-model-based method to achieve this objective, using a spectrum driven feature based on the Spectral Moments (SMs) from measured responses from the jack arches. SMs contain information from the entire frequency range, thus subtle differences between the normal signals and distorted ones could be identified. Our method then applies a modified k-means-clustering algorithm to these features, followed by a selection mechanism on the clustering results to identify jack arches with abnormal responses. We performed an extensive evaluation of the proposed method using real data from the bridge. This evaluation included a control component, where the approach successfully detected jack arches with already known damage or issues. It also included a test component, which applied the method to a large set of nodes over a month of data to detect any potential anomaly. The detected anomalies turned out to have indeed system issues after further investigations.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available