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Equipment Quality Condition Assessment Based on Improved PCABP

Abstract— Development of monitoring technologies and computer equipment makes test data acquisition be more real-time and complete, which provides better qualification to obtain the real-time equipment condition. In this paper, research status of equipment quality condition assessment is analyzed. Two aspects are expounded from dimensionality reduction and the selection of index system to the choice of assessment methods. Firstly, the condition level is divided and the raw test data is standardized. Then the PCA method is used to select the vectors to be evaluated and reduce the dimension. After that, the improved BP neural network algorithm is applied to assess the equipment quality condition. Finally, the applicability and advancement of the method are verified by an example.

Index Terms— test data, quality condition assessment, PCA, BP neural network.

Jin An, Ting-xue Xu, Xiang Zeng, Zhi-qiang Li, Gui-fang Zhu
Naval Aeronautical and Engineering University Department of Ordnance Science and Technology, CHINA
Gui-fang Zhu
Shandong High-tech Institute, CHINA

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Cite: Jin An, Ting-xue Xu, Xiang Zeng, Zhi-qiang Li, Gui-fang Zhu, "Equipment Quality Condition Assessment Based on Improved PCABP," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1004-1009, Beijing, 25-27 June, 2017.