کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5000332 | 1460684 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Incipient fault detection with smoothing techniques in statistical process monitoring
ترجمه فارسی عنوان
تشخیص گسل آغازین با تکنیک های هموار در نظارت بر روند آماری
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کلمات کلیدی
تشخیص گسل آغازگر، تشخیص گسل، شکل درجه دو، تکنیک صاف کردن مانیتورینگ فرایند آماری چند متغیره
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی هوافضا
چکیده انگلیسی
In modern industry, detecting incipient faults timely is of vital importance to prevent serious system performance deterioration and ensure optimal process operation. Recently, multivariate statistical process monitoring (MSPM) techniques have been extensively studied and widely applied to modern industrial systems. However, conventional fault detection indices utilized in statistical process monitoring are not sensitive to incipient faults with small magnitude. In this paper, by introducing two representative smoothing techniques, novel incipient fault detection strategies based on a generic fault detection index in MSPM are proposed. Fault detectability for each proposed strategy is analyzed. In addition, the effects of the smoothing parameters on fault detection, including advantages and disadvantages, are also investigated. Finally, case studies on a numerical example and two practical industrial processes are carried out to demonstrate the effectiveness of the proposed incipient fault detection strategies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Control Engineering Practice - Volume 62, May 2017, Pages 11-21
Journal: Control Engineering Practice - Volume 62, May 2017, Pages 11-21
نویسندگان
Hongquan Ji, Xiao He, Jun Shang, Donghua Zhou,