Quantifying the reliability of defects located by bridge inspectors through human observation behavioral analysis
Pengkun Liu, Ying Shi, Ruoxin Xiong, Pingbo Tang
Abstract
Distinct site conditions and individual expertise contribute to the subjective nature of bridge inspection processes, which involve uncertain human factors. Assessing inspection reliability can be achieved by examining inspectors' behaviors that lead to inaccurately identified or overlooked defects. However, the scarcity of comprehensive behavioral data regarding defect observation poses a challenge in evaluating inspection consistency. This paper investigates observation behaviors in bridge inspection to quantify the reliability of structural defect localizations. We employ defect inspection strategies correlated with more dependable defect localization records to construct a behavioral process graph that quantifies inspectors' performance and predicts their “inspection reliability index.” The generated reliability index for inspectors serves as a weighting factor to emphasize the opinions of more reliable inspectors when consolidating inspection records. The findings reveal that aggregating the inspection records of 96 human subjects based on their reliability indices effectively filters out false alarms while retaining reliable defect records.