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A STATISTICAL CLASSIFICATION-BASED DECISION-MAKING MODEL FOR MONITORING THE TECHNICAL CONDITION OF MOBILE ROBOT ELECTRICAL EQUIPMENT

2025 · Reliability and Quality of Complex Systems · 0 citations

Abstract

Background. The possibility of using statistical classification methods to support decision-making in the process of monitoring the technical condition of mobile robot electrical equipment is being investigated. Materials and methods. A model for estimating state changes is proposed based on probabilistic patterns of parameter dynamics, such as current consumption and speed of movement, using the nonparametric density estimation method (KDE) and Bayes' theorem. Results and conclusions. The structure of the decision function has been developed to determine the state of a potential failure based on a posteriori probabilities and the Mahalanobis distance.

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