Track quality detection method for grooved rail

In recent years, the tram market has developed rapidly, and it is increasingly important to evaluate the safety detection and overall smoothness of the relevant lines. However, most of the relevant tests are in the stage of manual detection with low detection efficiency and low accuracy. In this paper, a set of algorithm for TQI of tram was developed. First, the weight coefficient distribution of track irregularity parameters in the traditional TQI model was improved by analytic hierarchy process. The massive track detection data were trained into a comprehensive prediction model by using big data technology, and the calculation and prediction of TQI of modern tram were realized, which provided a new idea and method for the modern track detection and evaluation method of tram.