中圖分類號： TP393 文獻(xiàn)標(biāo)識碼： A DOI： 10.19358/j.issn.2096-5133.2020.10.012 引用格式： 李曉昌,，徐哲壯,，謝仁栩，等. 基于云平臺的壓磚設(shè)備健康狀態(tài)分析方法設(shè)計[J].信息技術(shù)與網(wǎng)絡(luò)安全,，2020,，39(10)：61-66.
Design of health status analysis method for brick pressing machine based on cloud platform
Li Xiaochang1,，Xu Zhezhuang1，Xie Renxu1,，Wang Yi1,，Liu Xing1，Wang Hongfei1,，Xia Yuxiong2
1.School of Electrical Engineering and Automation,Fuzhou University,，F(xiàn)uzhou 350108，China,； 2.Fujian Huading Intelligent Manufacturing Technology Co.,，Ltd.，F(xiàn)uzhou 350003,，China
Abstract： The analysis of the health status of the brick pressing machine based on the operating data is of great significance for reducing the failure rate of the machine and improving the quality of the finished brick press. Most existing solutions are limited to offline manual analysis, which has poor real-time performance and low promotion efficiency. In response to the above problems, this paper designed an analysis method of the health status of brick press machine based on the Alibaba Cloud machine learning platform. Based on the clustering method, the health state model of the brick press machine was constructed. Without prior knowledge, the health status of the brick press machine such as work, standby, and abnormality was modeled. Furthermore, the model was deployed on a cloud computing platform, and the online analysis of the health status of brick press machine was realized through periodic data import and analysis. An example was provided to prove the effectiveness of the proposed method.
Key words : machine health status analysis,；industrial big data；machine learning,；cloud platform,；brick pressing machine
