کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
724286 892371 2006 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
SUB-SPACE PRINCIPAL COMPONENT ANALYSIS FOR POWER PLANT MONITORING
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
SUB-SPACE PRINCIPAL COMPONENT ANALYSIS FOR POWER PLANT MONITORING
چکیده انگلیسی

With increasing ease of access to plant-wide process signals in many power stations, operators face a growing challenge, particularly under alarm conditions, to monitor plant operations. However, recognizing that many of the signals are both highly correlated and collinear naturally lends itself to the adoption of data mining techniques. Typically, plant models are identified under normal conditions from historical data records. Subsequently, deviations from trained behaviour are used as indicators of poor plant performance and / or process faults. Both principal component analysis (PCA) and sub-space PCA have been applied to monitoring of a combined cycle gas turbine (CCGT). The capabilities of both approaches are demonstrated following a multi-block implementation, and the influence of external ambient conditions on CCGT performance are also examined.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC Proceedings Volumes - Volume 39, Issue 7, 2006, Pages 243–248
نویسندگان
, , ,