Abstract
Modern diagnostic systems are characterized by that the flow of diagnostic information requires significant computational resources to process. In order to improve the reliability of the object to be diagnosed and reduce operating costs, it is necessary to improve procedures for analyzing diagnostic results. This paper suggests a procedure to form the diagnostic features of locomotive nodes based on the use of a principal components analysis. The proposed approach is distinguished by a decrease in the dimensionality of the input set of diagnostic features in order to select the sets of interconnected diagnostic parameters. Based on the selection of the sets of interconnected diagnostic features, constructing new latent diagnostic parameters has been proposed. A latent diagnostic parameter contains information that combines data from several initial diagnostic features. The result of the method is a set of latent diagnostic parameters that do not correlate with each other and reflect the behavior of the object to be diagnosed from different technical points. The application of a sufficient number of latent diagnostic parameters involved the scree test method. This paper reports the results from using the proposed approach for treating the results from diagnosing the hydraulic transmissions in locomotives. The result from applying the procedure has made it possible to propose using three latent diagnostic parameters to assess the technical condition of a locomotive’s hydraulic transmission during bench tests. The suggested parameters contain 90 % of the original information and reflect losses in the transmission, as well as the load at the input and output of the transmission.
Highlights
The rapid development of information systems has led to a sharp increase in the amount of information that characterizes any sphere of human activity
Based on the application of a principal components analysis, a technique to reduce the dimensionality of the set of diagnostic parameters has been proposed
The original diagnostic parameters were combined on the basis of the values of factor loads of parameters in each principal component
Summary
The rapid development of information systems has led to a sharp increase in the amount of information that characterizes any sphere of human activity. An approach can be used in which the maximum possible number of control parameters is measured to monitor the technical condition of vehicles. The use of such an approach is not rational for both economic and technical reasons. At the current stage of technological diagnostics development, the use of data mining technologies is relevant. The purpose of these technologies is to highlight the most informative and generate new diagnostic features. The introduction of intelligent analysis technologies could result in increased vehicle reliability and traffic safety, as well as lower operating and maintenance costs. The theoretical and practical results of such works would be in demand in the creation and implementation of automated fleet management systems for vehicles
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