Pulsed power, used to produce underwater discharges, has been the subject of numerous studies to elucidate its mechanisms and applications. This paper reports on observation by a high-speed camera of the production and progress of streamer discharges created using a magnetic pulse compression pulsed power generator with maximum output energy of 40 Joules per shot in the medium of both tap and distilled water. Bubble production along streamers, bubble collapse, generation of shock waves, and extinction of bubbles was also observed by a high-speed camera.

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Condition based maintenance (CBM) is becoming more and more popular in equipment maintenance. A prerequisite to widespread deployment of CBM technology and practice in industry is effective diagnostics and prognostics. A dynamic Bayesian network (DBN) based prognosis method was investigated to predict the remaining useful life (RUL) for an equipment. First, a DBN based prognosis framework and specific steps for building a DBN based prognosis model were presented. Then, the corresponding inference algorithms for DBN based prognosis were provided. Finally, a prognosis procedure based on particle filtering algorithms was used to predict the RUL of drill-bits of a vertical drilling machine, which is commonly used in industrial process. Preliminary experimental results are promising.

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