Abstract
In the transition to automated and automatic manufacturing an urgent problem is to increase the reliability of mobile robots (MR) and their drives, creation of devices to monitor the technical characteristics of MR, diagnose and predict the remaining resource. Inspite of the high relevance of the diagnosing MR drives problem, there are no generally accepted methodology for diagnosing MR drives, criteria for selecting methods, parameters and volumes of diagnostics at present. An unsolved problem, related to the diagnosis of MR drives and the prediction of their residual life remains, is the development of methods that allow to carry out of automatic complex multiparametric diagnostics and prediction of the residual life using artificial intelligence methods. Effective fault detection and diagnosis can improve the reliability of the MR drive and avoid costly maintenance. In this paper a fault detection scheme for synchronous motors with permanent magnets based on a fuzzy system is proposed. The sequence current components (positive and negative sequence currents) are used as fault indicators and are set as input to the fuzzy fault detector. The expediency of the proposed scheme for determining of various types of faults for a synchronous motor with permanent magnets under various operating conditions is simulated using the SimInTech software.
Highlights
Three-phase drives based on high-power synchronous motors are widely used for mobile robots with high carrying capacity
Combined defect Overloading can physically affect on the rotor shaft, causing it to break or crack, which in turn will cause a decrease in magnetic flux, that will reduce the efficiency of the motor
The PMSM fault simulation was carried out as follows^ Overload Overload is modeled by changing the shaft load (TL) from 100% to 200% of the rated load
Summary
Three-phase drives based on high-power synchronous motors are widely used for mobile robots with high carrying capacity. The model-based diagnostic concept is the most widely used approach due to the need for uninterrupted operation of mobile robot drives and increasing requirements for their reliability [3]. The accuracy of the drive model is limited due to its idealization Environmental factors such as motor temperature and operational factors: speed and current may affect the fault signature [6]. Https://doi.org/10.10 51/matecconf /202134603067 considered in [7] The disadvantages of this method are necessary to use the expensive high-precision vibration sensors. A fault detection scheme for the PMSM drive, taking into account electrical defects such as stator resistance and inductance, is described in [9]
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