In this study, the performance data from 30 inspectors evaluating 147 specimens with fatigue cracks in representative in-situ conditions were analysed to identify the role of human factors in bridge inspection. Two performance measures, the percentage of correct detections (detection rate) and the number of false calls, were considered. The variability in both performance measures was large, and only a small amount of the variance could be explained by individual characteristics or environmental conditions. Experience, training, temperature, and inspection duration were correlated with detection rate, while no single factor was correlated with false calls. A multivariate analysis found that the number of false calls could be best estimated considering an inspector’s employment sector and training, the maximum wind speed on the day of the inspection, and the use of a tape measure. Based on these results, recommendations for improved training methods, procedures, and equipment were developed.
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Campbell et al. (2020) studied this question.
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