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Data-driven process monitoring and diagnosis with support vector data description.

机译：数据驱动的过程监控和诊断，支持向量数据描述。

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This thesis targets the problem of fault diagnosis of industrial processes with data-driven approaches. In this context, a class of problems are considered in which the only information about the process is in the form of data and no model is available due to complexity of the process.;Support vector data description is a kernel based method recently proposed in the field of pattern recognition and it is known for its powerful capabilities in nonlinear data classification which can be exploited in fault diagnosis systems.;The purpose of this study is to investigate SVDD applicability as a data-driven method in industrial process fault diagnosis. In this respect, a complete framework for fault diagnosis structure is proposed and studied. The results demonstrate that SVDD is a powerful method in process fault diagnosis.

机译：本文针对数据驱动方法对工业过程进行故障诊断的问题。在这种情况下，考虑了一类问题，其中有关过程的唯一信息是数据形式，由于过程的复杂性而没有模型可用。支持向量数据描述是最近在网络中提出的一种基于内核的方法。在模式识别领域中，它以其强大的非线性数据分类能力而闻名，可以在故障诊断系统中加以利用。本研究的目的是研究SVDD作为数据驱动方法在工业过程故障诊断中的适用性。在这方面，提出并研究了故障诊断结构的完整框架。结果表明，SVDD是一种有效的过程故障诊断方法。

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作者
Tafazzoli Moghaddam, Esmaeil.;
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作者单位

Simon Fraser University (Canada).;

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授予单位 Simon Fraser University (Canada).;
学科 Computer engineering.
学位 M.A.Sc.
年度 2011
页码 106 p.
总页数 106
原文格式 PDF
正文语种 eng
中图分类能源与动力工程;
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1. Development of Data-Driven In-Situ Monitoring and Diagnosis System of Fused Deposition Modeling (FDM) Process Based on Support Vector Machine Algorithm [J] . Jung Sub Kim, Chang Su Lee, Sung-Min Kim, International Journal Precision Engineering Manufacturing-Green Technology . 2018,第4期

机译：基于支持向量机算法的数据融合沉积建模（FDM）过程现场监测与诊断系统的开发。
2. Big data approach to batch process monitoring: Simultaneous fault detection and diagnosis using nonlinear support vector machine-based feature selection [J] . Onel Melis, Kieslich Chris A., Guzman Yannis A., Computers & Chemical Engineering . 2018,第JULa12期

机译：大数据方法用于批处理过程监控：使用基于非线性支持向量机的特征选择来同时进行故障检测和诊断
3. Reprint of: Big data approach to batch process monitoring: Simultaneous fault detection and diagnosis using nonlinear support vector machine-based feature selection [J] . Onel Melis, Kieslich Chris A., Guzman Yannis A., Computers & Chemical Engineering . 2018,第AUGa4期

机译：转载：大数据方法用于批处理过程监视：使用基于非线性支持向量机的特征选择来同时进行故障检测和诊断
4. Improved Fault Diagnosis in Online Process Monitoring of Complex JNetworked Processes: a Data-Driven Approach [C] . Tiago J. Rato, Marco S. Reis European Symposium on Computer Aided Process Engineering . 2017

机译：复杂的JNetworked进程的在线过程监控中的改善故障诊断：数据驱动方法
5. Data-driven approach for control performance monitoring and fault diagnosis. [D] . Yu, Jie. 2007

机译：数据驱动的方法，用于控制性能监视和故障诊断。
6. Big Data Approach to Batch Process Monitoring: Simultaneous Fault Detection and Diagnosis Using Nonlinear Support Vector Machine-based Feature Selection [O] . Melis Onel, Chris A. Kieslich, Yannis A. Guzman, -1

机译：大数据方法用于批处理过程监控：使用基于非线性支持向量机的特征选择同时进行故障检测和诊断
7. Data-driven process monitoring and diagnosis with support vector data description [O] . Tafazzoli Moghaddam Esmaeil 2011

机译：支持向量数据描述的数据驱动过程监控和诊断

Data-driven process monitoring and diagnosis with support vector data description.

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