Analysis of stable functioning of objects using machine learning

V. Klyachkin, D. A. Zhukov, E. Zentsova
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引用次数: 1

Abstract

Stable functioning of the technical objects is estimated using methods of the statistical process control. However this approach does not always provide the timely detection of violations. It is suggested using machine learning methods for the binary classification of object states (stable or unstable). A program has been developed for calculation in the Matlab environment which allows for analysis of impact of the learning method, classification quality criteria, method of validation set as well as methods of selection of significant indicators on the object’s stable functioning forecast precision. Stable operation of the water treatment management system, stable vibration of the hydraulic unit, machining operation process are taken as examples.
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使用机器学习分析对象的稳定功能
利用统计过程控制的方法估计技术对象的稳定功能。然而,这种方法并不总是能够及时发现违规行为。建议使用机器学习方法对对象状态(稳定或不稳定)进行二元分类。开发了Matlab环境下的计算程序,分析了学习方法、分类质量标准、验证集方法以及重要指标选择方法对对象稳定功能预测精度的影响。以水处理管理系统的稳定运行、液压单元的稳定振动、机加工操作过程为例。
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