详细介绍了主元分析方法、其存在的缺点及相应的改善方法。
Principal Component Analysis (PCA) is studied and some modifications are discussed to improve the performance of PCA.
对于连续生产过程，可以采用普通的主元分析方法进行过程数据分析；
For continuous process, the normal PCA can be used to analyze the process data.
根据现实过程测量数据的时序相关特点，提出了一种动态主元分析方法；
To meet the needs of timely responses of process parameter measurements on paper machine operations, an analytical method based on the major dynamic components is applied on a paper process model.
实验结果表明，基于主元分析方法的图像序列融合能更好地提取木板表面缺陷特征。
The emulated resups show that more distinct features can be extracted from the four images of a same surface by fusing the image series with PCA.
应用主元分析方法将高维数据转换到低维数据空间，这使得过程监测可以在低维的空间内进行。
High dimension was changed into low dimension by using principal component analysis method, process detecting could be carried out in the low dimension space.
建立以Fisher判别函数为优化目标的适应度，利用粒子群算法中多个随机粒子实现核函数参数的优化，改善了核主元分析方法的性能。
Firstly, it constructs a fitness function which Fisher discriminate function is optimized object, then WCPSO is used to optimize it by its many random particles to improve the performance of KPCA.
本文针对主元分析（PCA）方法在故障检测和诊断应用中的特点，对其进行拓展性研究，提出一种逆投影主元分析方法，意在提高故障检测灵敏度和诊断准确性。
In this paper, inverse projection principal component analysis (IPPCA) method is presented by way of research on PCA characteristics for improving its monitor sensitivity and diagnosis accuracy.
在多变量统计过程控制中，传统的方法主要包括主元分析和偏最小二乘，这些方法存在着诸多缺陷。
Principal component analysis (PCA) and partial least squares (PLS) are the conventional techniques of multivariate statistical process control but exist some defects.
根据超声多普勒血流信号和血管壁搏动信号的统计特性，提出了一种基于主元分析的非线性滤波方法。
A nonlinear filtering method based on principle component analysis (PCA) was proposed according to the statistical characteristics of the Doppler ultrasound blood flow signal and wall thump signal.
应用基于主元分析的故障诊断方法对浮式油轮生产储油卸油系统进行故障检测与诊断研究。
Used fault diagnosis method based on Principal Components Analysis to research the fault monitoring and diagnosis of Floating Production Storage and Off-loading system.
尝试性地将基于主元分析的多变量统计方法应用于连铸结晶器过程的监测。
The authors try to use multivariate statistics method based on principal component analysis (PCA) to monitor continuous casting mould process.
为解决机动车牌图像倾斜将对其字符分割与识别带来不利的影响，提出一种基于主元分析(PCA)的车牌图像倾斜校正新方法。
The authors present a new method to remedy the negative effect arising from slant vehicle license plates character segmentation and recognition based on principal component analysis (PCA).
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。
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.
主元分析(PCA)作为数据驱动的一种统计建模方法，在化工产品质量控制与故障诊断方面得到广泛研究和应用。
Principal component analysis (PCA) has found wide application in chemical process monitoring and product quality control as a data-driven modeling method.
为此，提出了基于主元分析法和FRF的井架损伤识别方法。
Therefore, the derrick damage identification method based on principal component analysis and FRF is put forward.
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。
One new method for fault diagnosis of steam turbine based on kernel principal component analysis (KPCA) and multistage neural network ensemble was proposed.
基于有限元方法，对Y7125型磨齿机的砂轮主轴进行模态分析，得出了四阶主振动频率，并对数据进行了处理。
This paper analyzes the modal of Y7125 gear grinder spindle, gets out the main four stages of spindle vibration frequency and deals with the data.
在具体分析了多种建模方法的基础上，提出了核主元分析结合最小二乘支持向量机软测量建模方法。
On the basis of analysis of several methods for modeling, a soft sensor based on kernel principal component analysis (KPCA) and least square support vector machine (LSSVM) is proposed.
该方法首先利用核主元分析对人脸图像进行特征提取，然后依据支持向量机与最近邻准则对所提取的核主元特征进行分类识别。
Firstly KPCA is used to extract the features of human face image, and then SVM combined with the nearest distance rule is used for classification, which depends on the kernel principal components.
对多元统计过程控制常用的分析方法进行了介绍和总结，如主元分析、多向主元分析。
Conventional analytical methods used in Multivariate Statistical Process Control, such as Principal Component Analysis, Multi-way Principal Component Analysis are summarized.
提出利用主元分析（PCA）和学习矢量量化神经网络（LVQ）相结合的方法进行人脸识别。
This paper proposes a face recognition method based on PCA and LVQ neural networks.
该方法可辨识系统中相关性较高的若干传感器，并为之建立主元分析模型。
The main element analysis model was established with the several sensors highly related in the identification system of the diagnosis method.
研究了基于高阶谱（主要是三阶谱）和主元分析的故障特征提取方法。
The extracting fault features approach based on high-order spectral for pump valves of reciprocating pump was investigated, especially third order spectral analysis.
介绍了多变量统计投影方法的主要理论基础，包括：主元分析(PCA)、主元回归(PCR)、偏最小二乘(PLS)。
The paper briefly introduced the theoretical foundation of MSP method, which include Principle Component Analysis (PCA), Principle Component Regression (PCR), and Partial Least Squares (PLS).
提出一种基于人脸肤色统计模型和主元分析(pca)的人脸检测和定位方法。
This paper presents a human face detection and localization approach which is based on skin color detection and principle component analysis (PCA).
介绍了汽轮机转子、主蒸汽管道、汽缸和阀壳稳态蠕变应力和非稳态蠕变应力的计算方法，采用大型有限元分析计算程序计算汽轮机部件的非稳态蠕变应力和稳态蠕变应力。
The method takes into consideration both for steady and unsteady creep stresses of rotors, pipes, casings and valve housings to be determined with the help of finite element analysis programs.
该方法由三部分组成：主元分析pca、时间延迟神经网络、软测量模型的在线校正。
It is composed of three elements: PCA, time-delay neural network and model updating, where the offline model is trained through the algorithm GABP.
利用有限元方法，完成对望远镜主转动框架的结构静力分析和模态分析。
Static analysis and modal analysis on the structure of telescope main rotary frame was achieved by means of finite element method.
主要内容如下：对基于主元分析的方法进行了综合的研究：从故障检测、故障诊断、故障重构以及基于核主元分析的故障检测方法。
Completed work is summarized as following: The paper gives a integrated research based on PCA from fault detection, fault diagnosis, reconstruction fault to a new fault detection method based on 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).
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