| Author: | Leung, Ho-wai |
| Title: | Detection of unbalanced rotor faults in induction motor |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Electric motors, Induction -- Defects -- Testing Hong Kong Polytechnic University -- Dissertations |
| Department: | Multi-disciplinary Studies Department of Electrical Engineering |
| Pages: | iv, 82 leaves : ill. ; 30 cm |
| Language: | English |
| Abstract: | It is well know that the induction motor is the most common means of converting electrical energy to mechanical energy, and the most popular industrial drives used in the modern world. As they form a very essential part of modern industrial plants, the induction motors are getting more and more compact and efficient. Nowadays, people are also expecting an improvement in reliability from the induction motors. In fact, it is possible to locate the faults in the stator more easily as the windings are easily accessible. Faults in the rotor circuit are more difficult to detect, particularly at an early stage for a planned outage. If a slight rotor fault is left unattended, it could lead to a much more serious stator damage on machine breakdown and eventually lead to the occurrence of a shut-down of some important plants. Actually, there are instants at which the motor may prove to be too expensive to fail even though the cost of the motor itself is insignificant compared to the overall cost of the system, for example, induction motors used for the nuclear and oil industries. Therefore, if warning of an impending failure can be obtained, the motor can be scheduled for repair or replacement before catastrophic failure occurs, thus avoiding costly excess down-time of plant. In this project, the rotor unbalance detection technique is based on the spectral analysis on the motor current. We can determine the presence of rotor fault by identifying the presence of the [2(1-s)f+-fi] Hz frequency components, where f and fi are the frequencies of supply system and external signal respectively, from the frequency spectrum. This proposed method requires an adjustable low frequency generator which can inject a signal into the motor under investigation. The motor currents will be sampled via an analog-to-digital conversion system. A program will be developed for sampling and storing the motor current signals, and also performing Discrete Fourier Transform on the sampled data. The adjustable low frequency generator can be constructed by a Synchronous machine driven by a D.C. machine and a signal generator coupled with a power amplifier. The analog-to-digital conversion system is comprised of a current transformer, an A/C converter, a sample-and-hold circuit and an anti-aliasing filter. For a healthy induction motor, the only frequency component at mains supply frequency f will be located in the frequency spectrum. However, for a motor with rotor fault, the following components will be found in the frequency spectrum with the proposed method: fp (1-2s)f, f and [2(1-s)f+-fi]. Hence, the presence of [2(1-s)f+-fi] frequency components will indicate a fault being developed in the rotor circuit, and the magnitude of these components will reflect the how serious of the fault. In order to determine the sensitive of the proposed method, the frequency spectrum of a brand new 0.75 kW, 3-phase squirrel cage induction motor will be studied so as to provide a reference data for comparison between healthy and faulty motor. The brand new motor will be drilled with a hole on the end ring and hence producing a very slight imbalance in the rotor circuit. As the fault components generated in the motor current are comparatively very small with the main supply, a high resolution of A/D conversion is necessary so that 14-bit or higher A/D converter card is recommended. The aims of this project is to develop a reliable, sensitive and economical on-line rotor fault condition monitoring system for the induction motor running on no-load. |
| Rights: | All rights reserved |
| Access: | restricted access |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| b14605089.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.59 MB | Adobe PDF | View/Open |
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