BIC-Based Data-Driven Rail Track Deterioration Adaptive Piecewise Modeling Framework

Abstract

The records of maintenance activities are required for modeling the track irregularity deterioration process. However, it is hard to guarantee the completeness and accuracy of the maintenance records. To tackle this problem, an adaptive piecewise modeling framework for the rail track deterioration process driven by historical measurement data from the comprehensive inspection train (referred to as CIT) is proposed. The identification of when maintenance activities occurred is reformulated as a model selection optimization problem based on Bayesian Information Criterion. An efficient solution algorithm utilizing adaptive thresholding and dynamic programming is proposed for solving this optimization problem. This framework’s validity and practicability are illustrated by the measurement data from the CIT inspection of the mileage section of K21 + 184 to K220 + 308 on the Nanchang-Fuzhou railway track from 2014 to 2019. The results indicate that this framework can overcome the disturbance of contaminated measurement data and accurately estimate when maintenance activities were undertaken without any historical maintenance records. What is more, the adaptive piecewise fitting model provided by this framework can describe the irregular deterioration process of corresponding rail track sections.

Correlation Coefficient‐Based Information Criterion for Quantification of Dependence Characteristics in Hydrological Time Series

“…When $$n\to \infty $$, the model order determined by AIC cannot converge to the true value according to the probability theory (Fishler et al., 2002). In order to obtain consistent estimation, Akaike (Wang et al., 2018) and Schwarz (Yang et al., 2021) proposed BIC according to the Bayesian principle: $$$\text{BIC}(p)=\mathrm{ln}\,{\sigma }_{\varepsilon }^{2}+\frac{\mathrm{ln}\,n}{n}\mathrm{p}$$$ …”

“…When 𝐴𝐴 𝐴𝐴→ ∞ , the model order determined by AIC cannot converge to the true value according to the probability theory (Fishler et al, 2002). In order to obtain consistent estimation, Akaike (Wang et al, 2018) and Schwarz (Yang et al, 2021) proposed BIC according to the Bayesian principle:…”

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“…The technological development of humanity is faced with the need to provide an innovative and effective tool for productively solving the issues of ensuring the reliability, availability [1], maintainability [2][3][4][5], and safety of railway systems [6,7].…”

Experimental test rig for simulating dynamic loads on subway systems

“…The maintenance records help model the deterioration process and develop mathematical models for defining relationships between measurements and predictions. Yang et al [4] presented a method for modeling the deterioration process of railroad tracks. Their method includes an adaptive framework for measuring the data produced by a Comprehensive Inspection Train (CIT).…”