Review of data quality indicators and metrics, and suggestions for indicators and metrics for structural health monitoring

Abstract

Structural Health Monitoring (SHM) systems have been extensively implemented to deliver data support and safeguard structural safety in structural integrity management context. SHM relies on data that can be noisy in large amounts or scarce. Little work has been done on SHM data quality (DQ). Therefore, this article suggests SHM DQ indicators and recommends deterministic and probabilistic SHM DQ metrics to address uncertainties. This will allow better decision-making for structural integrity management.

Therefore, first, the literature on DQ indicators and measures is thoroughly examined. Second, and for the first time, necessary SHM DQ indicators are identified, and their definitions are tailored.

Then SHM deterministic simplified DQ metrics are suggested, and more essentially probabilistic metrics are offered to address the embedded uncertainties and to account for the data flow.

A generic example of a bridge with permanent and occasional monitoring systems is provided. It helps to better understand the influence of SHM data flow on the choice of DQ metrics and allocated probability distribution functions. Finally, a real case example is provided to test the feasibility of the suggested method within a realistic context.

Funding

Politecnico di Milano(Seal of Excellence)