数控机床时序数据存储与查询系统研究
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摘要
针对大部分数控机床状态信息都为时序数据这一特点,设计了一套数控机床时序数据存储与查询系统。对不同采集频率的机床状态时序数据进行分类,基于Socket通讯协议分别采集。基于时序数据写入和查询需求分析,应用TimescaleDB数据库实现时序数据存储。进一步对TimescaleDB数据库信息进行存储和查询测试,验证了时序数据存储与查询系统能严格按照设定频率采集及存储数据,相比PostgreSQL平均缩短了31.3%查询时间。最后搭建了Web端的状态监测界面,实现数控机床状态实时监测。
In order to realize the five-axis tool grinding center operation state monitoring and health warning and fault diagnosis, the five-axis tool grinding center operation state data storage and management technology is studied. Based on the research purpose and data characteristics, the five-axis tool grinding center operating state data classification, using Socket communication protocol to achieve data acquisition, and then the five-axis tool grinding center operating state data acquisition and storage scheme. For the analysis of database requirements, it is proposed to store the machine running state data of TimescaleDB based on PostgreSQL database for time series data optimization. Create database, data collection and storage and query test, prove that the use of timing framework AlScheduler can collect and store data strictly according to the set frequency, while TimescaleDB shortens the query time compared to PostgreSQL, and finally builds the status monitoring web page to achieve status monitoring.
In order to realize the five-axis tool grinding center operation state monitoring and health warning and fault diagnosis, the five-axis tool grinding center operation state data storage and management technology is studied. Based on the research purpose and data characteristics, the five-axis tool grinding center operating state data classification, using Socket communication protocol to achieve data acquisition, and then the five-axis tool grinding center operating state data acquisition and storage scheme. For the analysis of database requirements, it is proposed to store the machine running state data of TimescaleDB based on PostgreSQL database for time series data optimization. Create database, data collection and storage and query test, prove that the use of timing framework AlScheduler can collect and store data strictly according to the set frequency, while TimescaleDB shortens the query time compared to PostgreSQL, and finally builds the status monitoring web page to achieve status monitoring.
引文
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[11] 张华伟,陈勇,李海斌,等.基于HBase的工业大数据时序数据存储实现[J].电信科学,2017(S1):21-27.
[2] Kwon T H,Kwak J H,Kim K.A study on the establishment of policies for the activation of a big data industry and prioritization of policies:Lessons from Korea [J].Technological Forecasting & Social Change,2015,96:144-152.
[3] 钟海.大数据在工业制造业的应用与研究[J].企业技术开发,2015(13):104-105,119.
[4] 孙守林,张龙,董惠敏,等.车床轻量化设计数据库系统研究[J].组合机床与自动化加工技术,2015(10):76-79.
[5] 刘自然,甄守乐,颜丙生,等.基于TDMS的海量振动数据快速存储和查询虚拟系统[J].组合机床与自动化加工技术,2013(9):88-91.
[6] 刘东洪.基于Hadoop的机床运行状态信息采集与存储平台研究[D].重庆:重庆大学,2016.
[7] 徐凡,黄道平,刘少君.数控监控系统中数据库系统的研究[J].组合机床与自动化加工技术,2013(3):70-73.
[8] 岳宇宾,韩秋实,李启光,等.基于Visual C++6.0的数控凸轮轴磨床工艺数据库开发[J].组合机床与自动化加工技术,2014(7):117-119.
[9] 王海涛,张艳蕊.数字化车间机床数据库的构建研究[J].机械设计与制造,2010(6):197-198.
[10] 高晓勇,郑敏利,孟安,等.通用切削数据库的设计与实现[J].哈尔滨理工大学学报,2001,6(2):50-53.
[11] 张华伟,陈勇,李海斌,等.基于HBase的工业大数据时序数据存储实现[J].电信科学,2017(S1):21-27.