The principal component analysis (PCA) approach for sensor fault detection, identification and reconstruction in HVAC system is presented.
提出了空调系统传感器故障检测、故障识别、故障重构的主成分分析方法。
This thesis presents principal component analysis (PCA) approach for sensor fault detection, identification and reconstruction in HVAC system.
本文提出了用主成分分析法(PCA)进行空调系统传感器故障检测与诊断的基本思想。
The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
An actuator fault diagnosis method based on component signals analysis is proposed.
提出了一种基于部件信号分析的执行器故障诊断方法。
Importance analysis is a significant component of fault tree quantitative analysis and an important concept in reliability engineering.
重要度分析是故障树定量分析中的重要组成部分，是可靠性工程中的一个重要概念。
The fault diagnosis and property testing process of the electronic component of photovoltaic radar base on the testing of all important signal and analysis of fault trees are detailed introduced.
通过对光电雷达电子部件所有关键信号的实验测试和部件故障树结构分析，阐述了光电雷达电子部件性能检测和故障诊断的实现过程。
The waveforms of the current fault component of two phases are symmetrical according to an analysis of wrong-phase-coupling. This characteristic can be quickly extracted by correlation analysis.
基于对异相短路的分析，发现两相电流故障分量波形呈现反向对称性，可利用相关分析法快速提取此特征。
Numerous statistical process monitoring methods based on principal component analysis (PCA) have been developed and applied to various chemical processes for fault detection and identification.
基于主元分析(pca)的统计检测方法已经被广泛应用于各种化工过程的故障检测和识别。
For the sake of better carrying on fault detection and diagnosis, introduced the theory of principal component analysis (PCA) and the mechanism and strategy based on PCA for the fault of process.
为了更好的进行故障检测与诊断，介绍了主元分析(PCA)理论，给出了基于主元分析的过程故障辨识机理及策略。
One new method for fault diagnosis of steam turbine based on kernel principal component analysis (KPCA) and multistage neural network ensemble was proposed.
提出一种基于核主元分析(KPCA)和多级神经网络集成的汽轮机故障诊断方法。
The combination of curvilinear component analysis (CCA) and self-organizing feature map (SOFM) were applied to a diagnosis for fault feature extraction of bearing.
提出曲元分析(CCA)和自组织特征映射(SOFM)相结合的方法用于轴承的故障诊断特征提取。
This paper presents monitoring and fault diagnosis of a PVC batch process using multi way principal component analysis (MPCA).
将多方向主元分析（MPCA）理论应用到一个实际的PVC间歇反应过程的性能监测与故障诊断中。
In this paper, the principle component analysis (PCA) theory is introduced, and the theory is used for fault diagnosis of lock of actuator.
文中介绍了主元分析算法以及在故障检测方面的应用。
Based upon the model established here, a square prediction error is used to detect that the sensor fault for SPE (Principle component analysis) is sensitive to the sensor fault.
在所建立模型的基础上，根据平方预报误差(SPE)对传感器故障敏感的特点利用其进行传感器的故障检测。
In order to improve the accuracy of aero-engine component fault diagnosis ability, a method of two layers fault diagnosis based on gray relational analysis was proposed.
为了改善对航空发动机气路部件故障诊断能力，提出了一种基于灰色关联分析的两层诊断方法。
Wavelet transform was utilized to get coefficients of each scale. Based the coefficient matrix, principal component analysis model was established to diagnose sensor fault.
利用小波变换得到传感器信号在各个尺度上的系数，然后根据尺度系数矩阵建立主元分析模型进行传感器故障诊断。
An approach to gear fault diagnosis is presented, which bases on kernel principal component analysis (KPCA).
提出了基于核函数主元分析的齿轮故障诊断方法。
An approach to gear fault diagnosis is presented, which bases on kernel principal component analysis (KPCA).
提出了基于核函数主元分析的齿轮故障诊断方法。
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