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Investigation of the Hydraulic Unit Operation Features Based on Vibration System Data Mining

机译:基于振动系统数据挖掘的液压单元操作特征研究

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The software and hardware level used for on-line monitoring of the hydropower equipment functioning parameters as well as the large amounts of stored data create the necessary conditions for application of innovative methods and technologies of data analysis in the tasks of analytical assessment of equipment condition. This paper presents the results of detecting the operational patterns of the hydraulic unit in various modes and functioning conditions based on the data mining techniques - principal component analysis and cluster analysis - applied to the monitoring data of the vibration control system. In multidimensional data space, two principal components have been selected and interpreted taking into account the contribution of the data attributes to the principal components. On the plane of the first two principal components, a five-cluster structure has been constructed to define the moments of time when the system demonstrates a characteristic behaviour. In addition, the monitored parameters have been analysed in terms of time series at characteristic moments of time. As a result, the comprehensive multidimensional analysis of monitoring data has allowed us to discover the hydraulic unit operation patterns and dependencies, determine the character of the influence induced by its constructive elements and work out the ratio between the ranges of key parameters in various modes of equipment operation.
机译:软件和硬件电平用于水电设备的在线监控功能参数以及大量存储的数据为应用程序条件的分析评估任务中的创新方法和技术的应用创造了必要条件。本文介绍了在基于数据挖掘技术的各种模式中检测液压单元的操作模式的结果 - 主要成分分析和集群分析 - 应用于振动控制系统的监测数据。在多维数据空间中,已选择两个主组件并考虑到数据属性对主组件的贡献。在前两个主成分的平面上,已经构建了五簇结构以定义系统演示特征行为的时间的时刻。此外,在特征时刻的时间序列,已经分析了监测参数。结果,监控数据的综合多维分析使我们能够发现液压单元操作模式和依赖性,确定由其建设性元件引起的影响的特征,并在各种模式下工作的关键参数范围之间的比率。设备操作。

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