کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10628056 | 990167 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Breaking load and bending strength prediction in manufacture of fibre cement composites using artificial neural networks and a flocculation sensor
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
سرامیک و کامپوزیت
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چکیده انگلیسی
The optimisation of the flocculation process during fibre cement production is a new key issue for the fibre cement industry. Many companies face difficulties in optimising the flocculant dosage in real time, which leads to product strength losses. This paper shows the feasibility of using artificial neural networks (ANNs) to establish correlations between flocculation data, in-line measured in a Hatschek machine by a focused beam reflectance measurement (FBRM) sensor, and mechanical properties of final composites. The results show a clear relationship between the mechanical properties of fibre cement composites and the flocculation process and that these are determined in real time. Three ANNs have been created to predict breaking load for 48Â h and 7 days and bending strength for 7 days, to obtain good correlations between the predicted and the real values.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Composites Part A: Applied Science and Manufacturing - Volume 36, Issue 12, December 2005, Pages 1617-1626
Journal: Composites Part A: Applied Science and Manufacturing - Volume 36, Issue 12, December 2005, Pages 1617-1626
نویسندگان
C. Negro, A. Alonso, A. Blanco, J. Tijero,