Air Compressor Fault Diagnosis Through Vibration Signals using Statistical Features and J48 Algorithms
نویسندگان
چکیده
منابع مشابه
Bearing Fault Diagnosis Based on Vibration Signals
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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Fault diagnosis of monoblock centrifugal pump is conceived as a pattern recognition problem. There are three important phases involved in a pattern recognition namely feature extraction, feature selection and classification. In this study, stationary wavelet transform (SWT) is used for feature extraction and J48 algorithm is used for feature selection and classification. The different fault con...
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Bearing fault diagnosis has been a challenge in the monitoring activities of rotating machinery, and it’s receiving more and more attention. The conventional fault diagnosis methods usually extract features from the waveforms or spectrums of vibration signals in order to realize fault classification. In this paper, a novel feature in the form of images is presented, namely the spectrum images o...
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The aim of this work is the application of the phase variation in vibration signal for fault detection on rotating machines. The vibration signal from the machine is modulated in amplitude and phase around a carrier frequency. The modulating signal in phase is determined after the Hilbert transform and is used, with the Fast Fourier Transform, to extract the harmonics spectrum in phase. This me...
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ژورنال
عنوان ژورنال: Indian Journal of Science and Technology
سال: 2016
ISSN: 0974-6846,0974-5645
DOI: 10.17485/ijst/2016/v9i47/107912