| 基于Storm流处理的数控机床运行数据监测方法的设计与实现 |
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| 引用本文： | 孙顺苗,何彦,吴鹏程,王乐祥,凌俊杰,李军.基于Storm流处理的数控机床运行数据监测方法的设计与实现[J].工程设计学报,2019,26(3):245-251. |
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| 作者姓名： | 孙顺苗 何彦 吴鹏程 王乐祥 凌俊杰 李军 |
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| 作者单位： | 重庆大学机械工程学院,重庆,400044;陕西汉江机床有限公司,陕西汉中,723003 |
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| 基金项目： | 国家科技重大专项资金资助项目(2017ZX04019001) |
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| 摘 要： | 针对目前数控机床运行数据种类多、数量大且难以实现实时处理的问题,提出一种基于Storm流处理技术的数控机床运行数据监测方法。该方法采用实时大数据计算框架Storm作为核心,通过外置传感器和数控系统通信协议获取数控机床运行数据。使用Kafka作为消息队列将机床运行数据上传给Storm,然后在Storm框架中进行数据统计、数据异常检测等实时分析业务,之后将分析结果存储于数据库中,并实现分析结果的可视化展示。在实际生产环境中对基于Storm流处理的监测方法进行测试,实验结果表明:该方法能够实现对数控机床运行数据的实时监测与处理,具有强实时计算能力、高扩展性的优点;并且在处理相对复杂的数控机床运行数据监测业务时,该方法的优势更显著。研究结果为数控机床运行数据监测提供了新思路,该监测方法具有广阔的工程应用前景。
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| 关 键 词： | 数控机床 流处理 大数据 |
| 收稿时间： | 2018-12-21; |
Design and implementation of monitoring method for CNC machine tool operating data based on Storm flow processing |
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| SUN Shun-miao,HE Yan,WU Peng-cheng,WANG Le-xiang,LING Jun-jie,LI Jun.Design and implementation of monitoring method for CNC machine tool operating data based on Storm flow processing[J].Journal of Engineering Design,2019,26(3):245-251. |
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| Authors: | SUN Shun-miao HE Yan WU Peng-cheng WANG Le-xiang LING Jun-jie LI Jun |
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| Affiliation: | 1.Beijing Forestry Machinery Research Institute， State Forestry and Grassland Administration, Beijing 100029, China;
2.Forestry New Technology Research Institute, Chinese Academy of Forestry, Beijing 100091, China |
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| Abstract: | Aiming at the problem that the operating data of CNC (computer numerical control）machine tool are too heterogeneous to be processed in real time, a monitoring method for CNC machine tool operating data based on Storm flow processing technology is proposed. The method used big-data real-time computing framework Storm as the core, and obtained operating data of CNC machine tool through external sensors and communication protocol based on CNC system. Kafka was used as a message queue to upload operating data to Storm, and then real-time analysis services such as data statistics, data anomaly detection and so on were carried out in Storm framework. The analysis results were stored in the database, and the visual display of the analysis results was realized. The monitoring method based on Storm flow processing was tested in the actual production environment. The experiment results showed that the method could realize real-time monitoring and processing of CNC machine tool operating data, and had the advantages of strong real-time computing ability and high scalability. The advantages of this method were more significant when dealing with relatively complex CNC machine tool operating data monitoring services. The research provides a new idea for the monitoring of CNC machine tool operating data， and the monitoring method has a wide application prospect in engineering. |
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| Keywords: | CNC (computer numerical control） machine tool flow processing big data |
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