Analysis of Data from the Thermal Imaging Inspection System Project

摘要

The goal of this study was to use temperature measurements derived from infrared cameras to identify trucks with potential brake, tire, or hub defects. Data were collected at inspection sites on six different days and vehicles were subjected to CVSA inspections. Based on the inspections, axle ends were classified into three brake problem categories: yes, no, maybe. Subsequently, the data were analyzed in order to find associations between the temperature measurements and the brake problem classifications. Metrics were developed to identify outliers or large variation in temperatures within or between trucks. Many of the measures focus on differences between axles, left side and right side, and single outlying temperatures. The analysis is restricted to trucks with five axles. Various truck and environment variables were recorded. The maximum brake temperature was most closely associated with the brake problem variable. The coefficient of variation and standard deviation identified ten of the fourteen trucks classified with at least one brake problem correctly. In conjunction with other metrics, additional trucks with brake problems were also identified. Associations between trucks with single outlying temperatures on axle ends and brake problem classifications were not strong. However, it is possible that these outliers could be indicative of brake problems not captured by results produced from inspections.