Journal
JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES
Volume 14, Issue 1, Pages 43-56Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/1045389X03014001005
Keywords
structural health monitoring; wireless sensor module; remote sensing; real-time damage detection; statistical process control; statistical pattern recognition; and time series analysis
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System integration of an online structural health monitoring module was accomplished by coupling commercially available microclectro-mechanical system sensors and a wireless telemetry unit with damage detection firmware. To showcase the capabilities of the integrated monitoring module, a bolted frame structure was constructed, and the preload in one of the bolted joints was controlled by a piezoelectric stack actuator to simulate gradual deterioration of a bolted connection. Two separate damage detection algorithms were used to classify a joint as damaged or undamaged. First, a statistical process control algorithm was used to monitor the correlation of vibration data from two accelerometers mounted across a joint. Changes in correlation were used to detect damage to the joint. For each joint, data were processed locally on a microprocessor integrated with the wireless module, and the diagnosis result was remotely transmitted to the base monitoring station. Second, a more sophisticated damage detection algorithm combining time series analysis and statistical hypothesis testing was employed using a conventional wired data acquisition system to classify a joint on the demonstration structure as damaged or undamaged.
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