Abstract:An algorithm to predict train wheel diameter based on Gaussian process regression (GPR) optimized using a fast simulated annealing algorithm (FSA-GPR) is proposed in this study to address the problem of dynamic decrease in wheel diameter with increase in mileage, which affects the measurement accuracy of train speed and location, as well as the hyper-parameter problem of the GPR in the traditional conjugate gradient algorithm. The algorithm proposed as well as other popular algorithms in the field, such as the… Show more
“…The paper concluded that Gaussian Process Regression performs better than Support Vector Machines and Artificial Neural Networks in the accuracy of their tool wear predictive model because of the Gaussian distributed noise data can be utterly modeled quantitatively. Yu et al [171] applied a GPR model to inspect the dynamic change patterns in wheel diameter with the operation mileage increase based on a small group artificial measurement data. A normal distributed wheel wear rate regarding to the driving distance was assumed in that paper.…”
Section: Methods Review Of Pca and Gprmentioning
confidence: 99%
“…For example, the rail head surface height decrease due to wear is nonlinearly related to operation load, rail density and the sliding distance [57]. The wheel and rail wear rate shows a normal distribution and there is nonlinear mathematical relation between wear amount and the train driving distance [58]. Zhou et al [59] found that the wear rate keeps constant for a broad ranges of MGT (Million Gross Ton) but suddenly changes at specific MGT which suggests that the wear rate is not a linear function of the cumulative load.…”
“…The paper concluded that Gaussian Process Regression performs better than Support Vector Machines and Artificial Neural Networks in the accuracy of their tool wear predictive model because of the Gaussian distributed noise data can be utterly modeled quantitatively. Yu et al [171] applied a GPR model to inspect the dynamic change patterns in wheel diameter with the operation mileage increase based on a small group artificial measurement data. A normal distributed wheel wear rate regarding to the driving distance was assumed in that paper.…”
Section: Methods Review Of Pca and Gprmentioning
confidence: 99%
“…For example, the rail head surface height decrease due to wear is nonlinearly related to operation load, rail density and the sliding distance [57]. The wheel and rail wear rate shows a normal distribution and there is nonlinear mathematical relation between wear amount and the train driving distance [58]. Zhou et al [59] found that the wear rate keeps constant for a broad ranges of MGT (Million Gross Ton) but suddenly changes at specific MGT which suggests that the wear rate is not a linear function of the cumulative load.…”
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