rotating machines in particular induction electrical machines are important industry instruments. in manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. in this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using...

Arti cial Neural Networks (ANNs) can be used successfully to detect faults in rotating machinery, using statistical estimates of the vibration signal as input features. One of the main problems facing the use of ANNs is the selection of the best inputs to the ANN, allowing the creation of compact, highly accurate networks that require comparatively little preprocessing. This paper examines the ...

Rotating machinery vibration analysis involves a convolute mixture because of the propagation medium, and the signals recorded by sensors in an industrial application are often disrupted by the environment. Deconvolution is a signal processing method for convolution of vibration sources, spectral kurtosis is a statistical tool which can indicate the presence of series of transients and their lo...

To process the vibration signal fault diagnosis automatically and effectively, a method to calculate the generalized fractal dimension (Dq) based on the traditional G-P correlation dimension algorithm is presented. First, the vibration signal, a kind of random fractal that meets the statistical self-similarity, is reconstructed according to the phase space reconstruction theory. Second, for var...

The methodology of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. The ability of wavelet analysis to efficiently detect non-stationary, non-periodic, transient features of the vibration signal makes it a demanding tool for condition monitoring. In this paper, the vibra...

ARTICLE INFO Tool wear and tool life are the principle areas are focus in any machining activity, the production rate, surface finish of the machined component and the service life of machine are directly related to the defects in the tool. Vibration signals and expert system like decision tree algorithm can be used to prevent the damage on cutting tools and work pieces when the defect in the t...

electro encephalography is one of the reliable sources to detect sleep onset while driving. in this study we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. so first of all we have recorded eeg signals from 10 volunteers. they were obliged to be sleep deprived about 20 hours before the test. we recorded th...

The normal functioning of induction motors depend largely on ball bearing. Proper functioning and operation of ball bearing is the result of its maintenance by condition monitoring. Out of the various measures of condition monitoring vibration monitoring is the most extensively used and economical technique to detect, identify and distinguish fault in induction motors. In this research paper in...

This paper presents an efficient approach to machine condition monitoring and health diagnosis, based on the Discrete Harmonic Wavelet Packet Transform (DHWPT). Specifically, vibration signals measured from a bearing test bed were decomposed into a number of frequency sub-bands, and key features associated with each sub-band were selected, based on the Fisher linear discriminant criterion. The ...