1. Novel Causal Network Modeling Method Integrating Process Knowledge with Modified Transfer Entropy: A Case Study of Complex Chemical Processes
- Author
-
Qian-Qian Meng, Qunxiong Zhu, Ping-Jiang Wang, and Yan-Lin He
- Subjects
Chemical process ,0209 industrial biotechnology ,Mathematical optimization ,Computer science ,General Chemical Engineering ,Reliability (computer networking) ,02 engineering and technology ,General Chemistry ,Industrial and Manufacturing Engineering ,Variable (computer science) ,020901 industrial engineering & automation ,020401 chemical engineering ,Production (economics) ,Transfer entropy ,0204 chemical engineering ,Root cause analysis ,Network model - Abstract
With the increasing development of modern industries, ensuring the safety and reliability of production processes becomes a more and more urgent task. Alarm root cause analysis plays a very significant role in preventing faults of complex industrial processes. Causal network modeling is an important part of alarm root cause analysis. For building a good causal network model, transfer entropy is usually adopted as an effective method. However, there are some problems in determining prediction horizons of transfer entropy. In order to solve these problems and further enhance the performance of the original transfer entropy method, a modified transfer entropy method taking the prediction horizon from one variable to another and to itself simultaneously into consideration is proposed. Moreover, based on data-driven and process knowledge based modeling methods, an approach integrating transfer entropy with superficial process knowledge is designed to correct the false calculation of transfer entropy and then o...
- Published
- 2017