This paper presents a methodology for classifying train passages into different types with a weigh-in-motion (WIM) system to allow the calibration of railway fatigue load models and identify individual vehicles from the measurements for the continuous calibration of railway WIM stations from in-service trains. The quality assurance of the measured responses is demonstrated using statistical methods. This paper discusses the measurement station, the method used for processing the raw data, the algorithm used to identify the train types and vehicles automatically, and the limits of the obtained load spectra. The measurement errors are demonstrated to be satisfying for use in fatigue load model calibration. Furthermore, this paper proposes actions for accurately obtaining the actual traffic conditions and describes the future work required in this area.

This study presents correction factors for the Norwegian fatigue load model for railway bridges. The fundamental idea of a correction factor is to ensure that the load model induces the same fatigue damage as actual traffic. Load measurements from traffic on a representative line on the Norwegian railway network are used to propose correction factors for improved fatigue life estimation with freight and passenger trains. Correction factors improve the accuracy of the estimated fatigue life and reduce the conservatism of the load model. The validity and conservatism of the most damaging train assumption for fatigue load modeling is also considered. The suitability and consequences of using the proposed correction factors for other lines and historic traffic are discussed.