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...

Bearing fault can be detected using envelope demodulation of the bearing vibration signal in the resonant frequency band. Hence locating the correct resonant band is the key to successful application of the resonance envelope demodulation. A statistical criterion of the vibration signal can be used to guide the identification of the resonant band. However, a single criterion is often not robust...

Vibration-based analysis is an important technique in machine fault diagnosis. In complex machines, the vibration generated by a component is easily affected by the vibration of other components or is corrupted by noise from other sources. Hence, the fault-related vibration must be recovered from among those sources for accurate diagnosis. In this paper, a super-exponential algorithm (SEA) base...

This paper focuses on applying statistical process control techniques to vibration-based damage diagnosis. First, an auto-regressive (AR) model is fit to the measured acceleration-time histories from an undamaged structure. Coefficients of the AR model are selected as the damage-sensitive features for the subsequent control chart analysis. Finally, the AR coefficients of the models fit to subse...

Currently, vibration-based damage detection is an area of significant research activity. This paper attempts to extend the research in this field through the application of statistical analysis procedures to the vibration-based damage detection problem. The damage detection process is cast in the context of a statistical pattern recognition paradigm. In particular, this paper focuses on applyin...

The goal of this article is to assess the feasibility of estimating the state of various rotating components in agro-industrial machinery by employing just one vibration signal acquired from a single point on the machine chassis. To do so, a Support Vector Machine (SVM)-based system is employed. Experimental tests evaluated this system by acquiring vibration data from a single point of an agric...

In this paper, a hybrid technique is proposed for detecting the vibration signal of electric motor. The proposed hybrid technique is the combination of S-transformation algorithm and radial basis function neural network (RBFNN) technique. Initially, the pre-processing is applied in the electric motor signal such as normal and vibration. Then, the features of the signal are extracted by using S-...

The gearbox is one of the critical subsystems in any rotating machinery, which plays a significant role machine-driven power transmission terms change speed and torque. It vital patching different industrial functionalities. advent developing gear technologies requirement to fulfil desired mechanical benefits lead add more importance health condition monitoring from various types fault occurren...