Gamma Stokastik Bozunma Modeli Kullanarak Demiryolu Tekerleklerinin Kalan Kullanım Ömrü Tahmini

Özet (abstract)

Predicting the Remaining Useful Life (RUL) of railway wheels is challenging because wheel–rail degradation is cumulative, stochastic, and influenced by operating conditions. This study evaluates a multi-indicator prognostic framework using real in-service measurements acquired with a CALIPRI C42 optical profilometer (NextSense GmbH, Graz, Austria). The database comprises 80 wheels from ten vehicles of the same rolling-stock type, monitored during five monthly measurement campaigns, and includes flange width (Fw), flange height (Fh), and the flange-gradient dimension (qR). The Gamma process and first-passage formulation are established tools; the contribution of this work is their common application to all three indicators on the same in-service fleet and the benchmarking of long-horizon probabilistic results against an AR(1) short-term predictor embedded in the First-Passage Auto-Regressive (FP-AR) framework using the same dataset. Median Gamma-based RUL values were 21.2–22.0 months for Fw, 13.7–17.6 months for Fh, and 5.7–9.5 months for qR, with qR showing the largest relative percentile dispersion. For one-step prediction, the FP-AR benchmark achieved global MAE/RMSE values of approximately 0.368/0.502 mm for Fw and 0.0187/0.0216 mm for Fh; qR was more difficult to predict, with global MAE/RMSE values of approximately 0.575/0.991 mm. Under the adopted intervention thresholds, these results identify qR as the most variable and operationally constraining indicator under the studied Fès–Marrakech service conditions. The proposed dual-model analysis therefore provides a position-specific, uncertainty-aware basis for comparing wheel-profile degradation indicators, while its maintenance implications remain fleet- and route-specific pending validation in additional operating contexts.

Yazarların özeti; kaynağından alınmıştır. Applied Sciences, 2026 · DOI ↗