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人工神经网络在矢量控制感应电动机驱动中电流传感器故障检测的应用。

Artificial Neural Network Application for Current Sensors Fault Detection in the Vector Controlled Induction Motor Drive.

机构信息

Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and Technology, ul. Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland.

Independent Researcher, 50-370 Wroclaw, Poland.

出版信息

Sensors (Basel). 2019 Jan 29;19(3):571. doi: 10.3390/s19030571.

Abstract

This paper describes a Fault Tolerant Control structure for the Induction Motor (IM) drive. We analyzed the influence of current sensor faults on the properties of the vector-controlled IM drive system. As a control algorithm, the Direct Field Oriented Control structure was chosen. For the proper operation of this system and for other vector algorithms, information about the stator currents components is required. It is important to monitor and detect these sensor faults, especially in drives with an increased safety level. We discuss the possibility of the neural network application in detecting stator current sensor faults in the vector control algorithm. Simulation and experimental results for various drive conditions are presented.

摘要

本文描述了一种感应电机(IM)驱动的容错控制结构。我们分析了电流传感器故障对矢量控制 IM 驱动系统性能的影响。作为控制算法,选择了直接磁场定向控制结构。为了使该系统和其他矢量算法正常运行,需要有关定子电流分量的信息。监测和检测这些传感器故障非常重要,尤其是在安全等级提高的驱动器中。我们讨论了神经网络在检测矢量控制算法中定子电流传感器故障的可能性。给出了各种驱动条件下的仿真和实验结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44dd/6387162/6ea56153e460/sensors-19-00571-g001.jpg

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