کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381720 1437502 2007 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault detection in catalytic cracking converter by means of probability density approximation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Fault detection in catalytic cracking converter by means of probability density approximation
چکیده انگلیسی

The paper deals with a model-based fault diagnosis for a catalytic cracking converter process realized using artificial neural networks. Modelling of the considered process is carried out by using a locally recurrent neural network. Decision making about possible faults is performed using statistical analysis of a residual. A neural network is applied to density shaping of a residual. After that, assuming a significance level, a threshold is calculated. The proposed approach is tested on the example of a catalytic cracking converter at the nominal operating conditions as well as in the case of faults.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 20, Issue 7, October 2007, Pages 912–923
نویسندگان
, ,