基于内存计算的纺织生产设备电能耗分析方法
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摘要
节能减排影响着纺织生产企业的生存和发展,通过分析设备的耗电情况实现精细化管理是一种减少生产能耗的途径。但是,在针对电能耗大数据进行分析时,基于Hadoop的计算框架无法暂存分析的中间结果,分析效率低。文章采用Spark计算框架,提出一种基于内存计算的设备耗电情况分析模型和毛纺流水线电能耗分析方案,依据毛纺工艺流程设计电能耗分析的处理流程和电能耗分析管理系统,利用Mahout类库实现分析算法。实践证明,内存计算技术的应用在提高毛纺企业生产设备电能耗分析效率的同时,还提升了生产过程的精细化管理水平和企业的竞争力。
The survival and development of textile production enterprises is affected by energy conservation and emission reduction. By analyzing the electrical energy consumption of the equipment can reduce the energy consumption of the production process. However,it is difficult to meet analysis requirements of large energy consumption data based on Hadoop. This paper presented an energy consumption analysis management system for wool textile production equipment based on memory calculation,and designed the processing flow of electric energy consumption analysis program according to the wool spinning process flow. The analysis model of energy consumption was designed using Spark calculation framework. And the analysis algorithm was realized by class library of Mahout. Practice has proved that the application of memory computing technology is not only improves the efficiency of energy analysis of production equipment,but also improves the fine management level of the production process and the competitiveness of enterprises in the wool textile enterprises.
The survival and development of textile production enterprises is affected by energy conservation and emission reduction. By analyzing the electrical energy consumption of the equipment can reduce the energy consumption of the production process. However,it is difficult to meet analysis requirements of large energy consumption data based on Hadoop. This paper presented an energy consumption analysis management system for wool textile production equipment based on memory calculation,and designed the processing flow of electric energy consumption analysis program according to the wool spinning process flow. The analysis model of energy consumption was designed using Spark calculation framework. And the analysis algorithm was realized by class library of Mahout. Practice has proved that the application of memory computing technology is not only improves the efficiency of energy analysis of production equipment,but also improves the fine management level of the production process and the competitiveness of enterprises in the wool textile enterprises.
引文
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[2]王军,刘文化,于伟东.一种基于Hadoop的纺织海量生产数据存储设计[J].微型电脑应用,2013,30(6):53-54.
[3]邵景峰,贺兴时,王进富,等.大数据环境下的纺织制造执行系统设计[J].机械工程学报,2015(5):160-170.
[4]Gopalani S,Arora R.Comparing apache spark and map reduce with performance analysis using K-means[J].International Journal of Computer Applications,2015,113(1):8-11.
[5]Meng X,Bradley J,Yavuz B,et al.MLlib:machine learning in apache spark[J].Journal of Machine Learning Research,2016,17:1-7.
[6]Shanahan J G,Dai L,Cao L B.Large scale distributed data science using Apache Spark:In Proceedings of the 21th ACM SIGKDD Inter-national Conference on Knowledge Discovery and Data Mining[C].Sydney:ACM,2015:2323-2324.
[7]Eluri V R,Ramesh M,Al-Jabri A S M,et al.A comparative study of various clustering techniques on big data sets using Apache Mahout:3rdMEC International Conference on Big Data and Smart City[C].Muscat:IEEE,2016:1-4
[8]Gupta A.Learning apache mahout classification[M].Birmingham:Packt Publishing Ltd,2015.
[9]赵妍.物联网在纺织企业生产中的应用[J].纺织导报,2014(1):52-54.
[10]Zaharia M,Chowdhury M,Das T,et al.Resilient distributed datasets:a fault-tolerant abstraction for in-memory cluster computing:Steven D.In Proceedings of the 9th USENIX Conference on Networked Systems Design and Implementation[C].San Jose:USENIX Association,2012:15-28.