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Open AccessArticle

Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support

1
Department of Mechatronic Systems, Kalashnikov Izhevsk State Technical University, 426069 Izhevsk, Russia
2
Slovak University of Technology in Bratislava, 812 43 Bratislava, Slovakia
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(16), 4429; https://doi.org/10.3390/s20164429
Received: 27 June 2020 / Revised: 4 August 2020 / Accepted: 6 August 2020 / Published: 8 August 2020
(This article belongs to the Section Sensors and Robotics)
The presented paper scientifically discusses the progressive diagnostics of electrical drives in robots with sensor support. The AI (artificial intelligence) model proposed by the authors contains the technical conditions of fuzzy inference rule descriptions for the identification of a robot drive’s technical condition and a source for the description of linguistic variables. The parameter of drive diagnostics for a robotized workplace that is proposed here is original and composed of the sum of vibration acceleration amplitudes ranging from a frequency of 6.3 Hz to 1250 Hz of a one-third-octave filter. Models of systems for the diagnostics of mechatronic objects in the robotized workplace are developed based on examples of CNC (Computer Numerical Control) machine diagnostics and mechatronic modules based on the fuzzy inference system, concluding with a solved example of the multi-criteria optimization of diagnostic systems. Algorithms for CNC machine diagnostics are implemented and intended only for research into precisely determined procedures for monitoring the lifetime of the mentioned mechatronic systems. Sensors for measuring the diagnostic parameters of CNC machines according to precisely determined measuring chains, together with schemes of hardware diagnostics for mechatronic systems are proposed. View Full-Text
Keywords: sensors; robotized workplace; algorithm; CNC machine; mechatronic modules; fuzzy inference; diagnostics; optimization sensors; robotized workplace; algorithm; CNC machine; mechatronic modules; fuzzy inference; diagnostics; optimization
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MDPI and ACS Style

Nikitin, Y.; Božek, P.; Peterka, J. Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support. Sensors 2020, 20, 4429. https://doi.org/10.3390/s20164429

AMA Style

Nikitin Y, Božek P, Peterka J. Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support. Sensors. 2020; 20(16):4429. https://doi.org/10.3390/s20164429

Chicago/Turabian Style

Nikitin, Yury; Božek, Pavol; Peterka, Jozef. 2020. "Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support" Sensors 20, no. 16: 4429. https://doi.org/10.3390/s20164429

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