The Design and Implementation of a Log-structured file system, Mendel Rosenblum
Автор: Mendel Rosenblum Название: The Design and Implementation of a Log-structured file system ISBN: 1461359333 ISBN-13(EAN): 9781461359333 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers are organized in topical sections on variability & statistical timing, circuit level techniques, power management, low power circuits & technology, system level techniques, power & timing optimization techniques, self-timed circuits, low power circuit analysis & optimization, and low power design studies.
Описание: This book provides a starting point for the use of field programmable gate arrays in the design of embedded systems. It offers the industrial engineer and researcher a concise but self-contained round-up of the state-of-the-art in programmable logic devices.
Описание: This thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions. However the developed embedded wireless condition monitoring system leads itself very well for applications on any power transmission equipment in which the loads and speeds are not constant, and access is restricted. As such this provides significant scope for future development. Three significant achievements are presented in this thesis. First, the development of a condition monitoring algorithm based on vibration analysis of an industrial robot for fault detection and diagnosis. The combined use of a statistical control chart with time-domain signal analysis for detecting a fault via an arm-mounted wireless processor system represents the first stage of fault detection. Second, the design and development of a sophisticated embedded microprocessor base station for online implementation of the intelligent condition monitoring algorithm, and third, the implementation of a discrete wavelet transform, using an artificial neural network, with statistical feature extraction for robot fault diagnosis in which the vibration signals are first decomposed into eight levels of wavelet coefficients.
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