تشخیص بروز شکستگی در میله‌های رتور موتورهای القایی با استفاده از شبکه‌های عصبی
نویسندگان
چکیده
kW 1/1 مورد آموزش قرار گرفت. برای اینکه این سیستم بتواند به ازای گشتاورهای مختلف کارایی داشته باشد، اطلاعات مورد نیاز به ازای گشتاورهای مختلف تولید شد. این سیستم قادر به تشخیص سلامت یا شکستگی حلقه انتهایی و یا میله‌های رتور، به صورت بهنگام بوده است.
کلیدواژه‌ها
عنوان مقاله [English]
Neural-Network-Aided On-line Diagnosis of Broken Bars inInduction Motors
نویسندگان [English]
- M. Ebrahimi
- M. Moradiyan
- H. Moeshginkelk
- M. Danesh
- and M. Bayat
This paper presents a method based on neural networks to detect broken rotor bars and end rings in squirrel cage induction motors. In the first part, detection methods are reviewed and traditional methods of fault detection as well as dynamic
model of induction motors are introduced using the winding function method. In this method, all stator and rotor bars are considered independently in order to check the performance of the motor for any faults in the parts. Then the frequency spectrum of current signals is derived using the Fourier transform and analyzed under various conditions. In the second part of the paper, an analytical discussion of the theoretical principles is presented to arrive at a simple algorithm for fault detection based on neural networks. The neural network has been trained using the information from a 1.1 KW induction motor. Finally, the system is tested with different values of load torque and is found capable of working on-line to detect all normal and ill-performing conditions.
کلیدواژه‌ها [English]
- Squirrel cage induction motor
- Rotor fault
- neural network
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