The Plasma Focus (PF) is a kind of dense transient plasmas in with high-pulsed voltage. To produce devices for eld application it is necessary to obtain PF equipment able to operate for a long period of time. Thus, a reliability analysis is indispensable. In this work a reliability analysis program for plasma focus devices is presented. The program considers a criticality analysis using Failure Modes and Effects Criticality Analysis (FMECA) to identify the most important failure modes of the system. Said failure modes are studied operating the Plasma Focus for many cycles, obtaining from them the characteristic curves of V(t) and İ(t). Feature Extraction (FE) techniques are applied to obtain a list of parameters that correlate to the degrading process. Furthermore, Machine Learning tools are used to learn from the obtained data, linking the changes in these parameters during its life cycle to the decay of the system in hope for future implementation of a predictive maintenance system and a reference for data analysis and prediction in PFs. The study was applied to a portable plasma focus device operated at 2 joules of stored energy.
Áreas temáticas de ASJC Scopus
- Física y astronomía (todo)