کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
381376 | 1437497 | 2008 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Genetically programmed-based artificial features extraction applied to fault detection
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper presents a novel application of genetically programmed artificial features, which are computer crafted, data driven, and possibly without physical interpretation, to the problem of fault detection. Artificial features are extracted from vibration data of an accelerometer sensor to monitor and detect a crack fault or incipient failure seeded in an intermediate gearbox of a helicopter's main transmission. Classification accuracies for the artificial feature constructed from raw data exceeded 99% over training and independent validation sets. As a benchmark, GP-based artificial features constructed from conventional ones underperformed those derived from raw data by over 2% over the training and over 11% over the testing data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 21, Issue 4, June 2008, Pages 558–568
Journal: Engineering Applications of Artificial Intelligence - Volume 21, Issue 4, June 2008, Pages 558–568
نویسندگان
Hiram Firpi, George Vachtsevanos,