ISBN: 9786139913619 - fault detection of gear box using artificial neural network (ann) (7 resultados)

Paperback. Condición: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.

Taschenbuch. Condición: Neu. Fault Detection of Gear Box using Artificial Neural Network (ANN) | Rohit Ghulanavar (u. a.) | Taschenbuch | 64 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139913619 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Fault diagnosis plays an important role in condition monitoring to enhance the machine time. In view of this, the present investigation focused on the development of Fault diagnosis system of gear boxes based on the vibration signatures and Artificial Neural Networks. In the present investigation to generate the vibration signatures an experimental set-up has been fabricated with sensing and measuring equipment. The four prominent faults wear,crack, broken tooth and insufficient lubrication of the gear were practically induced in the present investigation. Vibration signatures of the gearbox were collected by transmitting the motion at constant speed with gears having no fault, without applying any load.By inducing one fault at a time, vibration signatures were collected with different faults. Further, it was decided to use ANN based fault diagnosis system for the present investigation. The set of statistical features were extracted based on data pertaining to maximum amplitudes of vibration. The lower frequency of vibration Signal (RMS) is used as input to the ANN based fault diagnosis system designed and developed in MATLAB. 64 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fault diagnosis plays an important role in condition monitoring to enhance the machine time. In view of this, the present investigation focused on the development of Fault diagnosis system of gear boxes based on the vibration signatures and Artificial Neural Networks. In the present investigation to generate the vibration signatures an experimental set-up has been fabricated with sensing and measuring equipment. The four prominent faults wear,crack, broken tooth and insufficient lubrication of the gear were practically induced in the present investigation. Vibration signatures of the gearbox were collected by transmitting the motion at constant speed with gears having no fault, without applying any load.By inducing one fault at a time, vibration signatures were collected with different faults. Further, it was decided to use ANN based fault diagnosis system for the present investigation. The set of statistical features were extracted based on data pertaining to maximum amplitudes of vibration. The lower frequency of vibration Signal (RMS) is used as input to the ANN based fault diagnosis system designed and developed in MATLAB.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghulanavar Rohit1.Prof. Rohit D. Ghulanavar, 2.Prof.M.G.Mulla Authors1&2-Working as an Asst.Prof.in Department of Mechanical Engineering at Sant Gajanan Maharaj College of Engineering Mahagaon,MS,India and Research Scholar of Koneru .…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fault diagnosis plays an important role in condition monitoring to enhance the machine time. In view of this, the present investigation focused on the development of Fault diagnosis system of gear boxes based on the vibration signatures and Artificial Neural Networks. In the present investigation to generate the vibration signatures an experimental set-up has been fabricated with sensing and measuring equipment. The four prominent faults wear,crack, broken tooth and insufficient lubrication of the gear were practically induced in the present investigation. Vibration signatures of the gearbox were collected by transmitting the motion at constant speed with gears having no fault, without applying any load.By inducing one fault at a time, vibration signatures were collected with different faults. Further, it was decided to use ANN based fault diagnosis system for the present investigation. The set of statistical features were extracted based on data pertaining to maximum amplitudes of vibration. The lower frequency of vibration Signal (RMS) is used as input to the ANN based fault diagnosis system designed and developed in MATLAB.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…