基于全局局部保留投影与测地距离的气化炉故障检测方法

高温、高压、强腐蚀工作环境下的气化炉易发生仪表测量故障，进而影响煤制油、煤制甲醇等生产工艺，甚至危及人员安全。针对上述问题，提出了一种基于全局局部保留投影（global-local preserving projection, GLPP）算法与测地距离的气化炉故障检测方法。首先，采用GLPP算法提取样本邻域确定的数据局部特征；然后，提出一种基于测地距离度量样本的非近邻关系的数据全局特征提取方法；进一步，利用提取的全局特征构建相应的统计量来进行故障检测。最后，分别通过田纳西伊斯曼（Tennessee Eastman, TE）与真实气化炉2个案例验证所提出方法的有效性和可行性。

Global-Local Preserving Projection and Geodesic Distance Based Gasifier Fault Detection

Gasifiers operating in high-temperature, high-pressure, and highly corrosive working environments are prone to instrument measurement failures. The failure affects production processes such as coal-to-liquids and coal-to-methanol, and even endangers personnel safety. In order to solve the above problems, a global local preserving projection and geodesic distance gasifier based fault detection method were proposed in this paper. Firstly, the GLPP algorithm was adopted to extract the local features of the data determined by the sample neighborhood. Then, a geodesic distance measurement sample''s non-neighbor relationship-based data global feature extraction method was proposed. Further, the extracted global features were used to construct corresponding statistics for fault detection. Finally, the effectiveness and feasibility of the proposed method were verified through two cases which were Tennessee Eastman (TE) and a real gasifier.