Data quality indicators for vibration-based damage detection and localization. (1st March 2021) - Zhou, Zhengjie; Wegner, Leon D.; Sparling, Bruce F.
Highlights: The quality of ambient VBDD data is assessed by its consistency over multiple tests. The consistency of the data is quantified using data quality indicators (DQIs) Probability of locating damage is generated using FEA and random excitation. DQI values correlate well with the probability of successful damage localization. Necessary DQI values for a 90% localization success rate are identified. Abstract: The effective application of vibration-based damage detection (VBDD) methods as a structural health monitoring approach depends largely on the accurate measurement of modal properties, particularly the mode shapes. However, the modal properties of bridges and other civil engineering structures are commonly measured using an output-only approach and ambient excitation sources, which can lead to considerable variability in the measurements and therefore a lack of confidence in the reliability of the VBDD results. This paper proposes two data quality indicators that can be used to assess the quality of a calculated VBDD parameter in terms of its potential to confidently identify and characterize damage, based on the consistency of the parameter when obtained from different sets of vibration test data. The performance of the indicators is demonstrated by application to a simple-span slab-on-girder bridge deck and comparison to the probabilities of successfully locating nine damage cases, as calculated using transient dynamic finite element analyses under simulated randomly varying loads. The data quality indicators were found to correlate well with the probability of successful localization, and were able to reflect the varying probabilities associated with several factors, including the number of repeated random trials used to estimate the mode shapes, the distance from the damage to the nearest sensor, the proximity of the damage to simple supports, and the severity of the damage. The proposed parameters were therefore shown to be capable of determining whether the available data are of sufficient quality to confidently apply VBDD methods.