Fault detection and isolation of ECG process using kernel principal components

机译：使用内核主要组件进行故障检测和ECG进程隔离

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In this paper, a study of the regularity of the electrocardiogram is given by the integration of a process diagnostic tool that is kernel principal components. It is a question of detecting the defects which exist in the set of parameters of the process of the electrical activity of the cardiovascular system: segments of the ECG and amplitude of the waves. The kernel ACP which is a powerful tool in fault detection is applied to a multivariable matrix of data from the ECG process. Exceeding the control thresholds of the SPE statistic proves the existence of a defect in the data studied. The calculation of contributions is introduced for the isolation of defects.

机译：在本文中，通过集成作为内核主要组件的过程诊断工具，对心电图的规律性进行了研究。这是检测存在于心血管系统电活动过程的参数集中的缺陷的问题：心电图的分段和波幅。内核ACP是故障检测的有力工具，被应用于来自ECG流程的多变量数据矩阵。超过SPE统计量的控制阈值证明了所研究数据中存在缺陷。引入贡献的计算是为了隔离缺陷。

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《International Conference on Engineering MIS》|2017年|1-6|共6页
会议地点 Monastir(TN)
作者
Hanen Chaouch;
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作者单位

Electric engineering department Engineers school of Monastir Ibn aljazzar city Monastir Tunisia;

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关键词
Principal component analysis; Electrocardiography; Kernel; Eigenvalues and eigenfunctions; Fault detection; Tools; Process control;

机译：主成分分析；心电图；核心;特征值和特征函数；故障检测；工具；过程控制;

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1. Fault detection and isolation in nonlinear systems with partial Reduced Kernel Principal Component Analysis method [J] . Ines Jaffel, Okba Taouali, Mohamed Faouzi Harkat, Transactions of the Institute of Measurement and Control . 2018,第4期

机译：部分减少内核主成分分析方法非线性系统故障检测与隔离
2. Unsupervised Fault Detection for Refrigeration Showcase Systems with Kernel Principal Component Analysis based Multivariate Statistical Process Control using Feature Selection with Maximal Information Coefficient [J] . Kiyo Arai, Yoshikazu Fukuyama, Kenya Murakami, IEEJ Journal of Industry Applications . 2021,第5期

机译：使用具有最大信息系数的特征选择，基于多变量统计过程控制的内核主成分分析的制冷展示系统无监督故障检测
3. Kernel Generalization of Multi-Rate Probabilistic Principal Component Analysis for Fault Detection in Nonlinear Process [J] . Donglei Zheng, Le Zhou, Zhihuan Song 自动化学报（英文版） . 2021,第008期
4. Fault detection and isolation of ECG process using kernel principal components [C] . Hanen Chaouch International Conference on Engineering MIS . 2017

机译：使用内核主组件的ECG过程的故障检测与隔离
5. Principal component analysis based fault detection and isolation. [D] . Cao, Jin. 2004

机译：基于主成分分析的故障检测和隔离。
6. Between Nonlinearities Complexity and Noises: An Application on Portfolio Selection Using Kernel Principal Component Analysis [O] . Yaohao Peng, Pedro Henrique Melo Albuquerque, Igor Ferreira do Nascimento, 2019

机译：非线性复杂性和噪声之间：使用内核主成分分析的组合选择应用
7. Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes [O] . Xiaogang Deng, Peipei Cai, Jiawei Deng, 2019

机译：主要辅助统计本地内核主成分分析及其在非线性工业过程中初期故障检测的应用
8. Documentation of the current fault detection, isolation and reconfiguration software of the AIPS fault-tolerant processor [R] . Lanning, David T., Shepard, Allen W., Johnson, Sally C. 1987

机译：有关aIps容错处理器的当前故障检测，隔离和重新配置软件的文档

Fault detection and isolation of ECG process using kernel principal components

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