Prototype of an automatic system for monitoring the success of starting asynchronous motors in local power supply systems

I. Dulov, A. Fishov
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Abstract

The present study aims to develop and test a prototype of an intelligent automatic system for monitoring the success of starting asynchronous motors with a squirrel-cage rotor using the physical model of a local power supply system. The prototype implements stepwise predictive control, which checks the partial conditions of the process success at each step based on critical parameter models of both the engine and the supply network. The development is based on the use of the LabVIEW software suite, parametric identification methods, physical simulation, analog and digital signal filtering, auto-regulation theory, mathematical analysis, and statistics. The study experimentally proved the possibility and effectiveness of predictive start-up control for asynchronous motors of local power supply systems in terms of the magnitude, rate, and pattern of variations in the operating parameters of motor stator windings without a direct measurement of the shaft velocity. The error of the developed models for determining the critical mode parameters, affecting the success of starting the asynchronous motor, is demonstrated to be less or equal to 4%. The error in the predictive estimate of the start-up duration for an asynchronous motor did not exceed 14%. It is demonstrated that in 91% of experiments with the start-ups of an asynchronous motor using the physical model of a local power supply system under the variations of circuit-mode conditions, the automatic system prototype reliably identified the success/failure of the engine start at various stages of the process. If a failure was detected, the prototype ensured the interruption of start-ups in the early stages. The studies revealed no cases of non-issuance by the automatic system of a command to interrupt the start-up process under the conditions of its failure. Therefore, intelligent automatic systems for monitoring the success of starting asynchronous motors in local power supply systems will reduce the likelihood of damage to motors and equipment of power supply networks, preserve their serviceability, and improve the reliability of power supply to consumers.
监测本地供电系统中异步电机启动成功率的自动系统原型
本研究旨在利用本地供电系统的物理模型,开发和测试用于监测鼠笼式转子异步电动机启动成功率的智能自动系统原型。原型实现了分步预测控制,根据发动机和供电网络的关键参数模型,检查每一步过程成功的部分条件。开发过程中使用了 LabVIEW 软件套件、参数识别方法、物理模拟、模拟和数字信号滤波、自动调节理论、数学分析和统计学。研究通过实验证明了在不直接测量轴速的情况下,对本地供电系统异步电机定子绕组运行参数的变化幅度、速率和模式进行预测性启动控制的可能性和有效性。事实证明,所开发模型在确定影响异步电机启动成功与否的临界模式参数时,误差小于或等于 4%。异步电机启动持续时间的预测估计误差不超过 14%。实验证明,在电路模式条件变化的情况下,在使用本地供电系统物理模型进行的异步电动机启动实验中,91% 的自动系统原型都能在不同阶段可靠地识别发动机启动的成功/失败。如果检测到故障,原型系统可确保在早期阶段中断启动。研究表明,在出现故障的情况下,自动系统没有发出中断启动过程的指令。因此,监测本地供电系统中异步电动机启动成功与否的智能自动系统将降低电动机和供电网络设备损坏的可能性,保持其可维护性,并提高向用户供电的可靠性。
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