Cyber-physical predictive diagnostics system for servos of mobile construction robots. (November 2020)

• Record Type: Journal Article
• Authors: Travush, V; Erofeev, V; Bulgakov, A; Kruglova, T; Svetlov, D
• Is Part Of: Journal of physics. Volume 1687(2020)
• Publication Date: 2020-11
• Subjects: Cyber-physical system -- construction robots -- servos -- predictive diagnosis -- neural networks classification -- fuzzy decision-making model; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1687/1/012014
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The article is devoted to solving the urgent scientific and technical problem of increasing the operational reliability of mobile construction robots. The cyber-physical system for predictive diagnostics of their servo drives is proposed. A five-level structure of a cyber-physical predictive diagnostics system is proposed. A description of each level is provided. An effective set of diagnostic parameters for predictive diagnostics of servo drives has been selected. A method is proposed to distinguish a faulty state from a load change based on wavelet transform and neural networks. A method for predicting the technical state of construction robots and electric motors based on neural networks has been developed. A fuzzy decision-making model based on the results of predictive diagnostics to optimize the trajectory of a mobile construction robot is described in detail. This allows to significantly extend the operational life of the mobile construction robot to eliminate sudden malfunctions and downtime of the construction site.