کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
790073 1466404 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault detection and diagnosis method for cooling dehumidifier based on LS-SVM NARX model
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
پیش نمایش صفحه اول مقاله
Fault detection and diagnosis method for cooling dehumidifier based on LS-SVM NARX model
چکیده انگلیسی


• A nonlinearly ARX model is proposed for cooling dehumidifier diagnosis.
• The proposed NARX model is identified by LS-SVM.
• Both the penalty C and kernel function width σ in the LS-SVM model are automatically optimized by AGA.
• Two level models are built respectively for cooling dehumidifier fault detection and diagnosis.

Developing fault detection and diagnosis (FDD) for the cooling dehumidifier is very important for improving the equipment reliability and saving energy consumption. Due to the precise mathematic physical model for cooling dehumidifier FDD is difficult to build, a novel Nonlinear Autoregressive with Exogenous (NARX) method for the cooling dehumidifier FDD based on Least Squares Support Vector Machine (LS-SVM) is proposed. Firstly, the dehumidifier system is divided into two level models. Secondly, the parameters of the NARX model are identified by LS-SVM, and the parameters C and σ of the LS-SVM are optimized by adaptive genetic algorithm (AGA) in order to improve the model building precision. Lastly, two faults in condenser and compressor component are diagnosed by the built models. The experiment result indicates this proposed method is effective for cooling dehumidifier FDD and the model generalization ability is favorable.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Refrigeration - Volume 61, January 2016, Pages 69–81
نویسندگان
, , , ,