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Author

Satish C. Sharma

Other affiliations: Indian Institutes of Technology
Bio: Satish C. Sharma is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Bearing (mechanical) & Reynolds equation. The author has an hindex of 30, co-authored 233 publications receiving 3639 citations. Previous affiliations of Satish C. Sharma include Indian Institutes of Technology.


Papers
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Proceedings ArticleDOI
01 Jan 2010
TL;DR: The methodology proposed in this paper for fault diagnosis of rolling element bearings, utilizes autocorrelation of raw vibration signals to reduce the dimension of vibration signals with minimal loss of significant frequency content.
Abstract: This paper is focused on fault diagnosis of bearings due to localized defects i.e. spall on the bearing components, which is essential to the design of high performance rotor bearing system. The methodology proposed in this paper for fault diagnosis of rolling element bearings, utilizes autocorrelation of raw vibration signals to reduce the dimension of vibration signals with minimal loss of significant frequency content. Dimension of vibration signal is reduced to 10% with negligible loss of information. To extract most appropriate features from auto-correlated vibration signals and for effective classification of faults, vibration signals are decomposed using complex Gaussian wavelet. Total 150 signals of healthy and defective bearings at rotor speeds 250, 500, 1000, 1500 and 2000 rpm with three loading conditions are considered. 1-D continuous wavelet coefficients of these samples are calculated at the seventh level of decomposition (27 scales for each sample). Maximum Energy to Shannon Entropy ration criterion is used to determine scale corresponding to characteristic defect frequency. Statistical features are extracted from the wavelet coefficients corresponding to selected scales. Finally, bearing faults are classified using Support Vector Machine (SVM) method. The test results show that the SVM can be used efficiently for bearing fault classification. It is also observed that classification accuracy is improved by using autocorrelation.© 2010 ASME

1 citations

Journal ArticleDOI
TL;DR: In vitro bioassay of the seventy rhizobacterial isolates revealed that the isolate I-58 was the most effective rhizOBacterial isolate, followed by I-30 and I-55 isolates in inhibiting the radial growth of test pathogens.
Abstract: Studies were carried out from 2013 to 2015 with the objectives to isolate and identify some indigenous rhizobacterial strains against major soil-borne pathogens of brinjal. Seventy thizobacterial isolates were characterized based on colony characters, morphological and biochemical test and identified as Pseudomonas flourescens (30), P. aeruginosa (13), P. aureofaciens (2) and Bacillus subtilis (25). In vitro bioassay of the seventy rhizobacterial isolates revealed that the isolate I-58 was the most effective rhizobacterial isolate, followed by I-30 and I-55 isolates in inhibiting the radial growth of test pathogens.

1 citations

Journal ArticleDOI
TL;DR: In this article, a generic capsule method is presented for stack up of geometrical tolerances of components and their assembly using graphical approach and angularity tolerance has been considered for illustration of the methodology.

1 citations

Journal ArticleDOI
TL;DR: In this article, a vertical U-tube is made to pass through a vertical shaker and at the same time it is vibrated by a shaker, the rotary motion produced as a result of vibration causes Coriolis force to act on the tube and causes it to twist.
Abstract: In many process industries, mass flow rate is the desired parameter rather than the volume flow rate. There are two approaches to measure mass flow rate. In the first approach, volume flow rate is measured and then it is multiplied with density. The second approach utilizes the flow metering concepts which are sensitive to mass flow rate. The work presented here falls in the second category. Here, the fluid is made to pass through a vertical U-tube and at the same time it is vibrated by a shaker. The rotary motion produced as a result of vibration causes Coriolis force to act on the tube and causes it to twist. Because of the twisting action, the two limbs of the tube do not pass through the mean position simultaneously. The resulting time lag (Δt) is measured with the help of an 8085 microprocessor and two proximity pick-ups. Mass flow rate is directly proportional to time lag (Δt) and is calculated and displayed subsequently after multiplying time lag (Δt) with a constant of proportionality. The work pr...

1 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper attempts to present a comprehensive review of AI algorithms in rotating machinery fault diagnosis, from both the views of theory background and industrial applications.

1,287 citations

Journal ArticleDOI
TL;DR: Current applications of wavelets in rotary machine fault diagnosis are summarized and some new research trends, including wavelet finite element method, dual-tree complex wavelet transform, wavelet function selection, newWavelet function design, and multi-wavelets that advance the development of wavelet-based fault diagnosed are discussed.

1,087 citations

Journal ArticleDOI
TL;DR: A feature learning model for condition monitoring based on convolutional neural networks is proposed to autonomously learn useful features for bearing fault detection from the data itself and significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier.

871 citations

Journal ArticleDOI
TL;DR: This review covers advances in electrochemical and biochemical sensor development and usage during 2010 and 2011 and focuses on novel methods and materials, with a particular focus on the increasing use of graphene sheets for sensor material development.
Abstract: This review covers advances in electrochemical and biochemical sensor development and usage during 2010 and 2011 In choosing scholarly articles to contribute to this review, special emphasis was placed on work published in the areas of reference electrodes, potentiometric sensors, voltammetric sensors, amperometric sensors, biosensors, immunosensors, and mass sensors In the past two years there have been a number of important papers, that do not fall into the general subsections contained within the larger sections Such novel advances are very important for the field of electrochemical sensors as they open up new avenues and methods for future research Each section above contains a subsection titled “Other Papers of Interest” that includes such articles and describes their importance to the field in general For example, while most electrochemical techniques for sensing analytes of interest are based on the changes in potential or current, Shan et al1 have developed a completely novel method for performing electrochemical measurements In their work, they report a method for imaging local electrochemical current using the optical signal of the electrode surface generated from a surface plasmon resonance (SPR) The electrochemical current image is based on the fact that the current density can be easily calculated from the local SPR signal The authors demonstrated this concept by imaging traces of TNT on a fingerprint on a gold substrate Full articles and reviews were primarily amassed by searching the SciFinder Scholar and ISI Web of Knowledge Additional articles were found through alternate databases or by perusing analytical journals for pertinent publications Due to the reference limitation, only publications written in English were considered for inclusion Obviously, there have been more published accounts of groundbreaking work with electrochemical and biochemical sensors than those covered here This review is a small sampling of the available literature and not intended to cover every advance of the past two years The literature chosen focuses on new trends in materials, techniques, and clinically relevant applications of novel sensors To ensure proper coverage of these trends, theoretical publications and applications of previously reported sensor development were excluded We want to remind our readers that this review is not intended to provide comprehensive coverage of electrochemical sensor development, but rather to provide a glimpse of the available depth of knowledge published in the past two years This review is meant to focus on novel methods and materials, with a particular focus on the increasing use of graphene sheets for sensor material development For readers seeking more information on the general principles behind electrochemical sensors and electrochemical methods, we recommend other sources with a broader scope2, 3 Electrochemical sensor research is continually providing new insights into a variety of fields and providing a breadth of relevant literature that is worthy of inclusion in this review Unfortunately, it is impossible to cover each publication and unintentional oversights are inevitable We sincerely apologize to the authors of electrochemical and biochemical sensor publications that were inadvertently overlooked

727 citations