P. K. Kankar

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Bearings are amongst the frequently encountered components to be found in rotating machinery. Though inexpensive, their failure can interrupt the production in a plant causing unscheduled downtime and production losses. So the bearing prognosis plays a significant role in reducing plant down time and enhanced operation safety, by estimating the Remaining(More)
Brain Computer Interface creates a communication path way between brain and outside world. Brain signals are recorded and processed to translate Electroencephalogram activity to an external command. Brain signals recorded from the scalp or from inside the brain, enable users to control a variety of applications. This capability can be very useful for the(More)
In this work, two dimensional motions of a robot are controlled using brain computer interface. Motor Imagery signals for different mental activities are recorded using electroencephalography technique. Recorded electroencephalogram signals are filtered out for noise reduction and processed. Processed signals are further used to prepare the feature vector(More)
Vibration and Noise Control Laboratory Mechanical and Industrial Engineering Department Indian Institute of Technology Roorkee-247667 Abstract This paper presents a comparative study between soft computing techniques Artificial Neural networks (ANN) and Self-Organizing Maps (SOM) using continuous wavelet transform (CWT) for fault diagnosis of rolling(More)
This paper is focused on the rolling element bearing fault diagnosis using radial basis function (RBF) network and adaptive neuro fuzzy classifier (ANFC). Defect considered for the study are inner race defect, outer race defect and ball defect. Vibration data for healthy bearing is used as baseline data. Multi scale permutation entropy (MPE) is applied to(More)
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