Name
Abstract | ||
|---|---|---|
Purpose - Crane plays a very important role in national economy with greatly reduced labor intensity, improved production efficiency and promoted social development as an indispensable auxiliary tool and process equipment. Therefore, its energy consumption becomes an unavoidable topic and in fact, energy consumption of crane is very huge. It has been proved to be the most cost-effective way for reducing energy consumption to establish and implement new energy efficiency standard. Thus, it is necessary to analyze and evaluate the energy efficiency for overhead crane so as to propose a new energy efficiency standard. The paper aims to discuss these issues. Design/methodology/approach - In this paper, four kinds of energy consumption sources of overhead crane is considered, based on which, an energy efficiency grading model for overhead crane based on BP neural network is proposed. Second, DS evidential theory is analyzed and based on it, an energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed. The evaluation procedure is discussed in detail. Then, a case is demonstrated how the evaluation is carried out. Findings - If overhead cranes with different energy consumptions need to be graded according to energy efficiency, the criterions to establish the energy efficiency labels for overhead cranes is proposed in this paper. Practical implications - The research results can provide energy efficiency standard proposal of overhead crane for relative departments to monitor the design, manufacturing and use of overhead crane. Originality/value - An energy efficiency grading model for overhead crane based on BP neural network is proposed. An energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1108/K-09-2015-0225 | KYBERNETES |
Keywords | Field | DocType |
BP neural network,DS evidential theory,Energy efficiency evaluation,Energy efficiency standard,Overhead crane | Production efficiency,Mathematical optimization,Efficient energy use,Computer science,Overhead crane,Simulation,National economy,Labor intensity,Artificial neural network,Energy consumption,Reliability engineering | Journal |
Volume | Issue | ISSN |
45 | 5 | 0368-492X |
Citations | PageRank | References |
1 | 0.36 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yifei Tong | 1 | 1 | 2.05 |
| Ruiwen Zhao | 2 | 1 | 0.36 |
| Wei Ye | 3 | 1 | 0.36 |
| Dongbo Li | 4 | 1 | 0.36 |