Abstract

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.

摘要

在这项研究中，分析了 30 名检查员在具有代表性的现场条件下评估 147 个具有疲劳裂纹的试样的性能数据，以确定人为因素在桥梁检查中的作用。考虑了两个性能指标，正确检测的百分比（检测率）和误报的数量。两种绩效指标的变异性都很大，只有一小部分差异可以用个体特征或环境条件来解释。经验、培训、温度和检查持续时间与检出率相关，而没有单个因素与误报相关。多变量分析发现，考虑到检查员的就业部门和培训，可以最好地估计误报的数量，检查当天的最大风速，并使用卷尺。根据这些结果，制定了改进培训方法、程序和设备的建议。