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Journal of Scientific and Industrial Research (JSIR) >
JSIR Vol.71 [2012] >
JSIR Vol.71(06) [June 2012] >
| Title: | Energy anomaly detection in tire curing by using data integration and forecasting techniques |
| Authors: | Yang, Hai-dong
Guo, Jian-hua
Liu, Guo-sheng |
| Keywords: | Artificial neural network (ANN)
Data integration
Energy consumption anomaly
Energy saving
Support vector machine (SVM)
Tire curing |
| Issue Date: | Jun-2012 |
| Publisher: | NISCAIR-CSIR, India |
| Abstract: | This
study proposed a method of energy anomaly detection by using data integration
and forecasting techniques to improve energy efficiency in tire curing.
Proposed method integrates energy consumption with different factors (environments,
equipments, operators, tire blanks and tire types). Artificial neural network
model and Support Vector Machine model were used to forecast normal interval
for energy efficiency ratio; instances dropping out of this interval indicate
potential anomaly affairs. Compared with traditional method, proposed method is
robust against environment changes, highly correlated to curing process and can
discover curing energy anomalies (leakage of steam or nitrogen, idling, and
improper curing parameters configuration) effectively. |
| Page(s): | 385-391 |
| CC License: |  CC Attribution-Noncommercial-No Derivative Works 2.5 India |
| ISSN: | 0975-1084 (Online); 0022-4456 (Print) |
| Source: | JSIR Vol.71(06) [June 2012]
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