Hello,
I am going to begin my thesis this semester. The thesis involve the use of machine learning in order to predict fault in power electronic converter. The first task is to create a good model for the IGBT failure and another analytical model for the aging of capacitor. I just want to know if their is a book that shows the experiments needed in order create these models.
Any Black Box (arbitrary) can have it's transfer function measured through an impulse response with a dirac delta. It's used for channel gauging when there are unknown gas quantities and humidities at play.
If it were me I would inject multiple diracs of slight variation and determine association analytically.
Perhaps:
http://libgen.io/book/index.php?md5=336F5337C1FBD4E5F35BA6BA2B872156
I haven't read it, but that's what I'd look through if I didn't already know it by osmosis.
you can use this book ( Enhancing Software Fault Prediction With Machine Learning) this book is an ideal reference source for engineers, it is very useful.
i think this book will be helpful
Power Electronic Converters Modeling and Control: with Case Studies
https://books.google.dz/books?isbn=1447154789 -
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