PCA-SDG Based Process Monitoring and Fault Diagnosis: Application to an Industrial Pyrolysis Furnace

Abstract

Ethylene cracking furnace is a key unit in the ethylene production process, whose operating condition is subject to changes with fluctuation in feed condition, the aging of equipment, and other possible disturbances. To promptly and correctly identify the root causes of process changes, an online process monitoring system based on Principal Component Analysis (PCA) and Signed Directed Graph (SDG) method is proposed for multiple operational conditions monitoring and fault detection. Active process adjustments or passive fluctuations are first differentiated, then the root cause is isolated by SDG reasoning based on the contribution percentage of principal variables in PCA. The True Positive Rate (TPR) of fault detection is 98%, and False Alarm Rate (FAR) is 1.56%. The root causes of fault match very well with operation records.