Extraction and Visualization of Multi-Parameter Spatio-Temporal Patterns of Multiproduct Pipeline Operation

Abstract: The operation process of a multiproduct pipeline not only has typical spatio-temporal characteristics, but also its operation mode needs to be comprehensively characterized by multiple monitoring parameters. However, the existing spatio-temporal pattern analysis methods make it difficult to reveal the comprehensive spatio-temporal characteristics of multi-parameters. Therefore, a tensor decomposition method based on multi-parameter fusion is proposed to extract the multi-parameter spatio-temporal pattern of multiproduct pipeline operation. This method realizes grouping fusion by analyzing the information quantity and correlation of multi-dimensional monitoring parameters of pipeline operation from different analysis aspects, and then models the fused spatio-temporal data as tensors and uses tensor decomposition and clustering methods to obtain the multi-dimensional spatio-temporal pattern of the data set. Finally, through the comparative analysis of the changing trend of the original multi-parameter under different modes, the spatial and temporal law of the operation mode is further found. Based on this method, a visualization system is designed to support the user in extracting and visualizing the comprehensive spatial and temporal patterns of multi-parameter representation from different perspectives, and the case study is carried out through the real multiproduct pipeline data. The experimental results are recognized by field experts, which shows that this method provides a new idea and tool for the subsequent multiproduct pipeline data analysis.