For the high dimensional chemical engineering processing data, an outlier detection method based on self-organizing map (SOM)networks and its visualization methods was proposed. Practically, it was applied for the observed data of preflash tower and the satisfactory result was obtained. Firstly, SOM was applied to obtain the topology-preserving plane for the high dimensional data. Then, based on the mapping plane and its visualization methods, the outliers were visualized clearly and easily. The results show that the proposed method does not need complex calculation, and the outliers in high dimensional data are effectively detected and eliminated.