Fault Detection of Rotating Machinery from Bicoherence Analysis of Vibration Data
نویسندگان
چکیده
The vibration signal carries the signature of the fault in most rotating equipments, and early fault detection of a fault is possible by analyzing the signal using different signal processing techniques. In this paper we consider gearboxes as a typical representation of a rotating or cyclo-stationary process. Faults in gearboxes leave their signature on the vibration signal with an increased presence of non-linearity. Bicoherence analysis detects and quantifies the non-linearity present in the signal and thus indicates the severity of the fault present in the gearbox. Time synchronous averaging is used to find the proper representation of one period of the cyclo-stationary vibration signal. A pilot plant case study is presented to demonstrate the practicality and utility of the proposed technique.
منابع مشابه
A Novel Intelligent Fault Diagnosis Approach for Critical Rotating Machinery in the Time-frequency Domain
The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...
متن کاملBearing Fault Detection Based on Maximum Likelihood Estimation and Optimized ANN Using the Bees Algorithm
Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...
متن کاملApplication of Bicoherence Analysis on Vibration Data for Condition Based Monitoring of Rotating Machinery
Bicoherence or Bispectrum analysis is emerging as a new powerful technique in signal processing, especially in areas where traditional linear spectral analysis provides insufficient information. It is most effective in analyzing systems with non-linear coupling between frequencies. Faults in rotating machineries leave their signature on the vibration signal sensors and generally manifest themse...
متن کاملFault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods
Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...
متن کاملFault Detection Method on a Compressor Rotor Using the Phase Variation of the Vibration Signal
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...
متن کامل