1. Fault detection and diagnosis using vibration signal analysis in frequency domain for electric motors considering different real fault types
- Author
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Isac Antônio dos Santos Areias, Ronny Francis Ribeiro Junior, and Guilherme Ferreira Gomes
- Subjects
Electric motor ,0209 industrial biotechnology ,Signal processing ,Computer science ,Condition monitoring ,02 engineering and technology ,Fault (power engineering) ,Industrial and Manufacturing Engineering ,Fault detection and isolation ,Power (physics) ,Vibration ,020303 mechanical engineering & transports ,020901 industrial engineering & automation ,0203 mechanical engineering ,Control theory ,Frequency domain ,Electrical and Electronic Engineering - Abstract
Purpose Electric motors are present in most industries today, being the main source of power. Thus, detection of faults is very important to rise reliability, reduce the production cost, improving uptime and safety. Vibration analysis for condition-based maintenance is a mature technique in view of these objectives. Design/methodology/approach This paper shows a methodology to analyze the vibration signal of electric rotating motors and diagnosis the health of the motor using time and frequency domain responses. The analysis lies in the fact that all rotating motor has a stable vibration pattern on health conditions. If the motor becomes faulty, the vibration pattern gets changed. Findings Results showed that through the vibration analysis using the frequency domain response it is possible to detect and classify the motors in several induced operation conditions: healthy, unbalanced, mechanical looseness, misalignment, bent shaft, broken bar and bearing fault condition. Originality/value The proposed methodology is verified through a real experimental setup.
- Published
- 2021
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