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.
将多变量统计过程控制应用于过程监控与诊断，在学术研究中已经较为普遍，但在工业实践方面还未充分施行。
Multivariate statistical process control for process monitoring and diagnosis are becoming more common in academic re - search, but are still underutilized in industrial practice.
为了更好的对火电厂发电机组设备故障进行检测，运用多变量统计过程控制技术获得更为精确的机组设备参数模型。
For better detection to the thermal generating set equipment fault, using the multivariate statistical process control, a more precise equipment parameter model is obtained.
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