Fault diagnosis of motor bearing based on deep learning
نویسندگان
چکیده
منابع مشابه
Fault Diagnosis of Motor Bearing Based on the Bayesian Network
On the basis of the analysis of vibration characteristics of motor bearing faults and the influence from testing noise on site, calculation of the symptom parameters representing the vibration signals according to the measured vibration signals is proposed, and the sensitivity analysis is carried out to these parameters which can refine effective symptom parameters. As there are limitations for...
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Motor systems are very important in modern society. They convert almost 60% of the electricity produced in the U.S. into other forms of energy to provide power to other equipment. In the performance of all motor systems, bearings play an important role. Many problems arising in motor operations are linked to bearing faults. In many cases, the accuracy of the instruments and devices used to moni...
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The vibration signal obtained from operating machines contains information relating to machine condition as well as noise. Further processing of the signal is necessary to elicit information particularly relevant to bearing faults. Many techniques have been employed to process the vibration signals in bearing faults detection and diagnosis. Two common techniques, time domain techniques and freq...
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Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration s...
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ژورنال
عنوان ژورنال: Advances in Mechanical Engineering
سال: 2019
ISSN: 1687-8140,1687-8140
DOI: 10.1177/1687814019875620