Valve Stiction Detection and Quantification Using a K-Means Clustering Based Moving Window Approach

• DOI: 10.1021/acs.iecr.0c05609
• Publication Date: 2021-02-05T18:49:45Z
• Authors: Da Zheng; Xi Sun; Seshu K. Damarla; Ashish Shah; Joseph Amalraj; Biao Huang
• Keywords: Stiction; Benchmark (surveying); Control valves; Static friction

In this paper, a novel and effective stiction detection method is proposed by combining K-means clustering the moving window approach. As byproduct, offers an estimation for band in sticky control valves. The tested industrial case studies consisting of benchmark loops from oil sands industry. loops, results are compared with some existing methods. This comparison shows superior performance method. It noticed through simulation study that not only provides but also can detect severe valve or unexpected closures.