ABSTRACT
Model-based processing is a theoretically sound methodology to address difficult objectives in complex physical problems involving multi-channel sensor measurement systems. It involves the incorporation of analytical models of both physical phenomenology (complex vibrating structures, noisy operating environment, etc.) and the measurement processes (sensor networks and including noise) into the processor to extract the desired information. In this paper, a model-based methodology is developed to accomplish the task of online failure monitoring of a vibrating cylindrical shell externally excited by controlled excitations. A model-based processor is formulated to monitor system performance and detect potential failure conditions. The objective of this paper is to develop a real-time, model-based monitoring scheme for online diagnostics in a representative structural vibrational system based on controlled experimental data.
ABSTRACT
An x-ray streak camera platform has been characterized and implemented for use at the National Ignition Facility. The camera has been modified to meet the experiment requirements of the National Ignition Campaign and to perform reliably in conditions that produce high electromagnetic interference. A train of temporal ultra-violet timing markers has been added to the diagnostic in order to calibrate the temporal axis of the instrument and the detector efficiency of the streak camera was improved by using a CsI photocathode. The performance of the streak camera has been characterized and is summarized in this paper. The detector efficiency and cathode measurements are also presented.
