The study of a periodic signal energy flow between adjacent frequency bandwidths in a diagnostic system of an induction motor

2017 ◽  
Author(s):  
Mieczyslaw Zajac ◽  
Maciej Sulowicz
Keyword(s):  
Induction Motor ◽  
Energy Flow ◽  
Diagnostic System ◽  
Periodic Signal ◽  
Signal Energy

scholarly journals Simple diagnostic technique of a single IGBT open-circuit faults for a SVM-VSI vector controlled induction motor drive

2015 ◽  
Vol 63 (1) ◽  
pp. 281-288 ◽  
Author(s):  
T. Orlowska-Kowalska ◽  
P. Sobanski
Keyword(s):  
Induction Motor ◽  
Diagnostic System ◽  
Diagnostic Technique ◽  
Open Circuit ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Stator Current ◽  
Wide Range ◽  
False Diagnosis ◽  
Signal Normalization

Abstract In this paper a simple diagnostic system for a single IGBT open-circuit faults for a two level voltage inverter-fed field oriented controlled induction motor drive was presented. A fault diagnostic procedure is carried out by utilizing an analysis of a stator current vector trajectory in α-β coordinates. An extraction of the failure information is based on monitoring of an angle between the stator current space vector and the axis. Thanks to a diagnostic signal normalization, high robustness to false diagnosis alarms is guaranteed. To confirm the proposed method, simulation results under a wide range working condition of the induction motor drive were presented.

Model- and Information Theory-Based Diagnostic Method for Induction Motors

2005 ◽  
Vol 128 (3) ◽  
pp. 584-591 ◽  
Author(s):  
Sanghoon Lee ◽  
Michael D. Bryant ◽  
Lalit Karlapalem
Keyword(s):  
Information Theory ◽  
Induction Motor ◽  
Channel Capacity ◽  
Diagnostic System ◽  
Functional Health ◽  
State Equations ◽  
Two Phase ◽  
Squirrel Cage ◽  
Three Phase ◽  
Cage Induction Motor

Introduced is a model-based diagnostic system for motors, that also employs concepts of information theory as a health metric. From an existing bond graph of a squirrel cage induction motor, state equations were extracted and simulations performed. Simulated were various cases, including the response of an ideal motor, which functions perfectly to designer’s specifications, and motors with shorted stator coils, a bad phase capacitor, and broken rotor bars. By constructing an analogy between the motor and a communication channel, Shannon’s theorems of information theory were applied to assess functional health. The principal health metric is the channel capacity, which is based on integrals of signal-to-noise ratios. The channel capacity monotonically reduces with degradation of the system, and appears to be an effective discriminator of motor health and sickness. The method was tested via simulations of a three-phase motor; and for experimental verification, a two-phase induction motor was modeled and tested. The method was able to predict impending functional failure, significantly in advance.

scholarly journals Identification of the Technical Condition of Induction Motor Groups by the Total Energy Flow

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6677
Author(s):  
N. I. Koteleva ◽  
N. A. Korolev ◽  
Y. L. Zhukovskiy
Keyword(s):  
Induction Motor ◽  
Energy Flow ◽  
Classification Problem ◽  
Technical Condition ◽  
Power Bus ◽  
Linear Load ◽  
Non Linear Load ◽  
Motor Operation ◽  
Equal Power

The paper discusses the method of identifying the technical condition of induction motors by classifying the energy data coming from the main common power bus. The work shows the simulation results of induction motor operation. The correlation between occurring defects and current diagrams is presented. The developed simulation model is demonstrated. The general algorithm for conducting experiments is described. Five different experiments to develop an algorithm for the classification are conducted: determination of the motors number in operation with different power; determination of the motors number in operation with equal power; determination of the mode and load of induction electric motor; determination of the fault and its magnitude with regard to operation and load of induction motor; determination of the fault and its magnitude with regard to operation and load of induction motor with regard to non-linear load in the flow. The article also presents an algorithm for preprocessing data to solve the classification problem. In addition, the classification results are shown and recommendations for testing and using the classification algorithm on a real object are made.

Sensorless Detection of Induction Motor Rotor Faults Using the Clarke Vector Approach

2011 ◽  
Vol 28 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Toomas Vaimann ◽  
Ants Kallaste ◽  
Aleksander Kilk
Keyword(s):  
Induction Motor ◽  
Condition Monitoring ◽  
Induction Motors ◽  
Diagnostic System ◽  
Cost Effective ◽  
Vast Number ◽  
Broken Rotor Bars ◽  
Rotor Faults ◽  
Effective Performance ◽  
Vector Approach

Sensorless Detection of Induction Motor Rotor Faults Using the Clarke Vector ApproachDue to their rugged build, simplicity and cost effective performance, induction motors are used in a vast number of industries, where they play a significant role in responsible operations, where faults and downtimes are either not desirable or even unthinkable. As different faults can affect the performance of the induction motors, among them broken rotor bars, it is important to have a certain condition monitoring or diagnostic system that is guarding the state of the motor. This paper deals with induction motor broken rotor bars detection, using Clarke vector approach.

Induction Motor Diagnostic System Based on Electrical Detection Method and Fuzzy Algorithm

2016 ◽  
Vol 18 (5) ◽  
pp. 732-740 ◽  
Author(s):  
Hong-Chan Chang ◽  
Shang-Chih Lin ◽  
Cheng-Chien Kuo ◽  
Cheng-Fu Hsieh
Keyword(s):  
Induction Motor ◽  
Detection Method ◽  
Diagnostic System ◽  
Electrical Detection ◽  
Fuzzy Algorithm
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