Motor fault diagnosis scheme by machine noise integration and signal similarity measurement

Jeongho Kang; Hongjae Im; Yunseok Oh; Dooyeon Kim; Minkyu Park; Jooyoung Son

doi:10.5916/jamet.2020.44.5.405

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자료유형: 학술저널

저자정보: Jeongho Kang (Korea Maritime & Ocean University) Hongjae Im (Korea Maritime & Ocean University) Yunseok Oh (Korea Maritime & Ocean University) Dooyeon Kim (Korea Maritime & Ocean University) Minkyu Park (Korea Maritime & Ocean University) Jooyoung Son (Korea Maritime & Ocean University)

저널정보: 한국마린엔지니어링학회 Journal of Advanced Marine Engineering and Technology (JAMET) 한국마린엔지니어링학회지 제44권 제5호

발행연도: 2020.10

수록면: 405 - 413 (9page)

DOI: 10.5916/jamet.2020.44.5.405

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In general, when an unusual phenomenon occurs in a device in a ship environment, it is detected by an alarm monitoring system (AMS) through a sensor, and its status and cause are immediately transmitted to the ship crew by an alarm. However, a specific mechanical fault is difficult to detect in the AMS; as such, the diagnosis of mechanical faults in the ship environment is often dependent on the subjective judgment of the crew. Therefore, if the noise generated from the machine can be collected, compared, and analyzed using information technology, the condition can be diagnosed instead of sounding an alarm to prevent damage to the machine. Herein, we propose two techniques for listening to noise from a machine that can categorize noise by a specific factor, extract features, differentiate noise from a normal machine noise, and diagnose noise as a failure. The two implemented techniques are the noise integration and signal similarity measurement techniques. These techniques are studied through motor noise measurement and analysis, and this paper focuses on motor failure diagnosis. The noise integration technique measures and analyzes the mechanical noise, and diagnosis is performed by extracting the noise integral value. The signal similarity measurement technique compares the similarity between the measured noise and the steady-state operating sound to perform a diagnosis. An experiment is conducted by creating an environment in which noises of various devices are mixed in a manner similar to the situation on a ship. It is discovered that the characteristics of the individual fault applied to the experiment are discernible. Hence, an effective fault diagnosis technique is devised by considering this analysis result and several combined factors.

#Ship machine #Fault diagnosis #Noise Integration #FFT

참고문헌 (9)

참고문헌 신청

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MATLAB / Integration of Numeric Data

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