Fault Diagnosis of HTS–SLIM Based on 3D Finite Element Method and Hilbert–Huang Transform

Abstract

The Linear Induction Motors (LIMs) are a novel structure of industrial motors, which have appeared in recent years. There are various models of optimal LIMs that help better performance. However, no research could be found about the behavior of these motors under the fault conditions. In this paper, a High-Temperature Superconducting Single-sided LIM (HTS-SLIM), with flat-solid secondary sheet is considered. Besides, a comprehensive review of novel and robustness fault diagnosis methods in electrical machines is carried out. To satisfy the paper aims, two mechanical and electrical failures, in forms of broken conductor sheet and short-circuit of coil are considered, respectively, and the dynamic model of the studied motor under short-circuit fault is proposed. The motor is modeled with 3D Finite Element Method (FEM), in order to consider the 3D effects of linear motors. Finally, the electromagnetic and mechanical behaviors of the considered machine are rendered under various conditions. The variation of various parameters are studied and their increament or decreament under faulty states are analyzed. In the next step, the Hilbert-Huang Transform (HHT) is employed to detect the features of the mentioned faults. The results and analysis show that the thrust and speed of motor have decreased under short circuit faults, and they have increased suddenly, when the primary cross over the broken secondary sheet about 600 % and 43 %, respectively. Besides, the flux density of all components under short circuit is reduced, while it increased under broken sheet fault and when these faults occur simultaneously.

A Feature Selection Approach Based on Memory Space Computation Genetic Algorithm Applied in Bearing Fault Diagnosis Model

“…2) Hilbert Transform (HT) HT is a specific linear operator which acts as a function, c i (t) of a continuous signal and produces another function of a real variable. The Hilbert spectrum matrix of the signal was formed from the process of analyzing the IMFs by the HT [38]. HT spectrum can be used to analyze the nonlinear and non-stationary signals of the spectrum content over time [39].…”