基于机器学习的故障分析专家系统综述

Hongjian Wang, Liyuan Liu, Youliang Wang, Zeya Peng
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引用次数: 1

摘要

机器学习是当今最有效、最流行的工具和理论之一,影响了许多工程领域。传统的失效分析也是基于统计学习和可靠性数据,这些方法可以用于评估设计寿命期间的特性、预测可靠性、评估交换效应、产品寿命预测和帮助进行失效分析。这两个主题有着天然的联系,因此本文对可靠性和机器学习进行了非常全面的概述,并将演示如何将机器学习工具用于经典可靠性系统和故障分析。重点介绍了贝叶斯网络及其方法等可靠性方面的一些算法。然后我们可以看到一个典型的工程领域是如何从机器学习中受益的。
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An Overview of Failure Analysis Expert System Based on Machine Learning
Machine learning is nowadays one of the most efficient and popular tool and theory which has influenced many of the engineering fields. The traditional failure analysis is also based on statistical learning and reliability data, these methods can be used to assess characteristics over the design life, predict reliability, assess the exchange effect, product life prognosis and help to failure analysis. These two subjects have the natural connection, so this paper presents a very general overview on reliability and machine learning, which will demonstrate how the machine learning tools used for classical reliability system and failure analysis. We especially state some algorithms such as Bayesian networks and its’ method to reliability area. Then we can see how a typical engineering area can benefit from the machine learning.
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