Process Monitoring Using Principal Components in Parallel Coordinates

作者：Dunia Ricardo^*; Edgar Thomas F; Nixon Mark

来源：AICHE Journal, 2013, 59(2): 445-456.

DOI：10.1002/aic.13846

• process monitoring
• parallel coordinates
• principal component analysis
• fault detection
• multivariable statistical process control
• data visualization
• PCA

Parallel coordinates is a recognized visualization technique in which data points, each defined by multiple coordinates, are represented by an unlimited number of adjoining parallel axes. This type of visualization technique is suitable for process monitoring applications in industrial facilities where a significant number of sensors are used to detect and identify abnormal operating conditions. This work makes use of principal component monitoring methods implemented in parallel coordinates plots, named PC2. The PC2 capabilities to visualize confidence regions of operations, evaluate models with different number of principal components, compare faulty events and determine the frequency of false alarms are here demonstrated. The monitoring visualization technology presented by PC2 was successfully used for early detection of compressor surge and column flooding using actual process data.

• 出版日期2013-2