An Approach to Remote Condition Monitoring Systems Management

This paper presents an approach for detecting and identifying faults in railway infrastructure components. The method is based on pattern recognition and data analysis algorithms. Principal component analysis (PCA) is employed to reduce the complexity of the data to two or three dimension. PCA involves a mathematical procedure that transforms a number of variables, which may be correlated, into a smaller set of uncorrelated variables called "principal components". Also the paper presents a brief overview of the state of the art in predictive maintenance on the basis of condition monitoring for critical elements of the railway infrastructure