A fault detection method for heat loss in a tyre vulcanization workshop using a dynamic energy consumption model and predictive baselines

被引:12
作者
Guo, Jianhua [1 ,2 ]
Yang, Haidong [2 ]
机构
[1] Guangdong Polytech Normal Univ, Dept Comp Sci, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Univ Technol, Dept Mechatron Engn, Guangzhou, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Fault detection; Heat loss; Tyre vulcanization; Energy consumption model; Thermodynamics; Prediction; LEAKAGE DETECTION; ANOMALY DETECTION; EFFICIENCY; FRAMEWORK; TIRE;
D O I
10.1016/j.applthermaleng.2015.07.064
中图分类号
O414.1 [热力学];
学科分类号
摘要
In a tyre vulcanization workshop (TVWS), the faults of steam traps and insulating layers usually lead to great heat loss and significantly lower energy efficiency. These faults tend to be difficult to detect in practice, and hence often got ignored. This paper presents a fault detection method for heat loss at a workshop level. A dynamic and hierarchical energy consumption model (DHECM) for a TVWS is proposed to establish the expected energy consumption of the vulcanizing process from thermodynamic theory. This model allows the separation of the heat loss and the technical energy consumption from the actual energy usage. The LMBP algorithm and energy consumption factors are adopted to estimate the baselines for the heat loss and help detect the faults. This method is validated in a large TVWS in Guangzhou China. Test results show that the heat loss of the TVWS was reasonably evaluated and it accounted for as much as 44.78% of the energy consumption under its regular operations. The heat loss estimation facilitated better detection performance, and helped identify the faults at a low level. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:711 / 721
页数:11
相关论文
共 36 条
[31]   Statistical Modeling for Energy Consumption and Anomaly Detection in Rubber Vulcanization Process [J].
Yang, Hai-Dong ;
Liu, Guo-Sheng ;
Huang, George Q. ;
Chen, Xin .
JOURNAL OF ENERGY ENGINEERING, 2013, 139 (02) :65-71
[32]  
Yang HD, 2012, J SCI IND RES INDIA, V71, P385
[33]  
Yang S., 2006, Heat Transfer Theory, P246
[34]  
Zhang Q.C., 2010, PROCESS AUTOM INSTRU, V131
[35]   A statistical fault detection and diagnosis method for centrifugal chillers based on exponentially-weighted moving average control charts and support vector regression [J].
Zhao, Yang ;
Wang, Shengwei ;
Xiao, Fu .
APPLIED THERMAL ENGINEERING, 2013, 51 (1-2) :560-572
[36]  
Zhu Liang, 2014, Advanced Materials Research, V1037, P169, DOI 10.4028/www.scientific.net/AMR.1037.169