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.
提出了一种在模型参数变动和存在外部扰动条件下的控制系统故障检测与识别方法。
A method for fault detection and identification in control system under external disturbance and variations of plant parameters is presented.
将该自适应算法应用于驱动桥故障检测中，结果表明该算法能够区分和识别驱动桥存在的不同故障类型。
The algorithm was applied to faults diagnosis of driver axle. The result showed that the algorithm could distinguish and recognize different faults of driver axle.
传感器是卫星导航系统中的重要部件，其故障的检测和识别对提高系统可靠性具有重要意义。
Sensors are important components in a satellite navigation system, so both fault detection and identification for them are of great significance for the reliability improvement of system.
正确识别和检测线路故障后的行波信号是实现行波故障测距的关键。
Correct identification and detection of fault traveling wave essential to fault location.
其中着重使用PC A方法进行故障检测的研究，使用FDA方法进行故障分离和识别的研究，并将两种方法相互配合，构成完整的故障诊断系统。
The PCA method is mainly used to research on fault detection while FDA to fault isolation and identification. The two methods interact and make up a complete fault diagnosis system.
正确识别和检测线路故障后的行波信号是实现行波保护和故障测距的关键。
The key point to realize protective relaying and the fault location based on travelling wave is how to correctly distinguish and detect the travelling wave signal.
正确识别和检测线路故障后的行波信号是实现行波保护和故障测距的关键。
The key point to realize protective relaying and the fault location based on travelling wave is how to correctly distinguish and detect the travelling wave signal.
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