کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
273405 | 505044 | 2009 | 6 صفحه PDF | دانلود رایگان |
The present understanding of disruption physics has not gone so far as to provide a mathematical model describing the onset of this instability. A disruption prediction system, based on a statistical analysis of the diagnostic signals recorded during the experiments, would allow estimating the probability of a disruption to take place. A crucial point for a good design of such a prediction system is the appropriateness of the data set. This paper reports the details of the database built to train a disruption predictor based on neural networks for ASDEX Upgrade. The criteria of pulses selection, the analyses performed on plasma parameters and the implemented pre-processing algorithms, are described. As an example of application, a short description of the disruption predictor is reported.
Journal: Fusion Engineering and Design - Volume 84, Issues 2–6, June 2009, Pages 534–539