Institution
National Aerospace Laboratories
Facility•Bengaluru, India•
About: National Aerospace Laboratories is a facility organization based out in Bengaluru, India. It is known for research contribution in the topics: Coating & Corrosion. The organization has 1838 authors who have published 2349 publications receiving 36888 citations.
Topics: Coating, Corrosion, Mach number, Sputter deposition, Aerodynamics
Papers published on a yearly basis
Papers
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01 Jan 1997
TL;DR: In this paper, a supersonic combustor with perpendicular injections behind a backward facing step was simulated in cold flow tests with inert gas injection, to investigate the mechanism of the ignition enhancement observed in the ignition tests with the same combustor.
Abstract: Flow field at pre-ignition phase in a supersonic combustor with perpendicular injections behind a backward facing step was simulated in cold flow tests with inert gas injection, to investigate the mechanism of the ignition enhancement observed in the ignition tests with the same combustor. The interaction, namely the merging, of separation at step base with that upstream of the injector caused enlargement of ignition region and the enhancement. The change in ignition ability was estimated based on ignition parameters. Based on the experimentally obtained ignition parameters, the ignition limit for the interacted separation region was predicted and showed reasonable agreement with the experimental results.
14 citations
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08 Jul 200114 citations
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14 citations
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TL;DR: Wavelet based bearing health condition monitoring technique can be used for bearing fault diagnosis and it can be extended for prognosis.
Abstract: Background/Objectives: Condition monitoring is one of the important functions to be carried out in the maintenance of any machine. In condition monitoring, there are several techniques among which the most commonly used technique for rotating machines is the vibration analysis. Methods/Statistical analysis: Discrete Wavelet Transform is used to decompose the vibration signal into 9 levels. For each level, mean ±std (standard deviation) are computed for both approximated and detailed coefficients. Findings: Bearing data obtained from the bearing test rig of Case Western Reserve University are used to test the algorithm. The standard of coefficients in level to 3 shows distant classification of faults. The levels which show clear classification among the bearings are those frequency bands in which the characteristic defect frequencies of faults occur. It is inferred that, the wavelet decomposition classifies the ball defect clearly than the frequency domain methods. Application/Improvements: Wavelet based bearing health condition monitoring technique can be used for bearing fault diagnosis and it can be extended for prognosis.
14 citations
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TL;DR: In this article, an energy harvesting by lead zirconate titanate (PZT) multilayer (ML) stacks and bimorphs is presented, which were fabricated by a tape casting technique and were poled at 2 kV/mm for 30 min immersed in a silicone oil bath maintained at 60°C.
Abstract: Piezoelectric materials have a unique ability to interchange electrical and mechanical energy. This property allows the absorption of mechanical energy such as ambient vibration and its transformation into electrical energy. The electrical energy generated can be used to power low-power electronic devices. In the present study, energy harvesting by lead zirconate titanate (PZT) multilayer (ML) stacks and bimorphs is presented. The devices were fabricated by a tape casting technique and were poled at 2 kV/mm for 30 min immersed in a silicone oil bath maintained at 60°C. The energy harvesting characteristics of the fabricated devices were measured in a suitably assembled test setup. The output voltage obtained from the PZT bimorphs and ML stacks was 450 mV and 125 mV, respectively. The higher output voltage from the bimorph is due to its low capacitance.
14 citations
Authors
Showing all 1850 results
Name | H-index | Papers | Citations |
---|---|---|---|
Harish C. Barshilia | 46 | 236 | 6825 |
K.S. Rajam | 42 | 83 | 4765 |
Kozo Fujii | 39 | 411 | 5845 |
Parthasarathi Bera | 39 | 136 | 5329 |
R.P.S. Chakradhar | 36 | 166 | 4423 |
T. N. Guru Row | 36 | 309 | 5186 |
Takashi Ishikawa | 36 | 154 | 5019 |
Henk A. P. Blom | 34 | 168 | 5992 |
S. Ranganathan | 33 | 211 | 5660 |
S.T. Aruna | 33 | 101 | 4954 |
Arun M. Umarji | 33 | 207 | 3582 |
Vinod K. Gaur | 33 | 92 | 4003 |
Keisuke Asai | 31 | 350 | 3914 |
K. J. Vinoy | 30 | 240 | 3423 |
Gangan Prathap | 30 | 241 | 3466 |