Decision-making System Algorithms for the Maintenance and Forecasting of Automated Electric Drives

O. Kryukov, Igor Gulyayev, D. Teplukhov
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Abstract

The control system algorithms for the technical condition of complex automated electric drive systems using forecast-ing are presented, which make it possible to increase the efficiency of the maintenance systems implementation. Ap-proaches to forecasting the state of the driving synchronous electric motors of technological installations as discrete stochastic systems that provide reliable information on the state in an on-line mode have been considered. A logical-probabilistic diagnostic model of the decision-making system on the need for technical diagnostics procedures has been formed. The proposed method has been tested on synchronous machines of the STD-12500-2 type, which operate as drive electric motors for gas-pumping units at linear compressor stations of the main gas transport.
自动化电力传动系统维护与预测的决策系统算法
提出了基于预测的复杂自动化电驱动系统技术状态控制算法,从而提高了维护系统的实施效率。将技术装置驱动同步电动机的状态预测方法作为离散随机系统,在在线模式下提供可靠的状态信息。建立了基于技术诊断程序需求的决策系统的逻辑-概率诊断模型。所提出的方法已在STD-12500-2型同步电机上进行了试验,该同步电机作为主要输气管道线性压缩站抽气机的驱动电动机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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