Data acquisition plays a significant role in determining and optimizing maintenance actions for railway wheelsets, as small inaccuracies translate into decreasing useful life, unnecessary downtime and costs. In this study, a comparison between data acquired from three different inspection devices: i) manual (gauge device), ii) laser and iii) under-floor wheel lathe; is presented for three wheelset parameters: flange thickness, flange height, and flange slope. Using condition data to assess the agreement of measurements by contrasting several devices in a real-world case study is challenging, as many of the commonly adopted assumptions in controlled experiments are not met. Therefore, a linear mixed model (LMM) approach is proposed to enable a comparison of performance under those limitations. Findings support the use of LMM and showing its ability to capture and account for the differences among the various groups, highlighting statistical significant performances of the inspection devices.

数据采集​​在确定和优化铁路轮对的维护措施中起着重要作用，因为微小的误差会导致使用寿命缩短，不必要的停机时间和成本降低。在这项研究中，比较了从三种不同检查设备获得的数据：i）手动（仪表设备），ii）激光和iii）地板下轮式车床；列出了三个轮对参数：法兰厚度，法兰高度和法兰坡度。在现实世界的案例研究中，使用条件数据通过对比几种设备来评估测量结果的一致性具有挑战性，因为无法满足受控实验中许多通常采用的假设。因此，提出了一种线性混合模型（LMM）方法，以便能够比较那些限制下的性能。