An online approach for fault detection and diagnosis of gas pressure reduction stations based on DCS-PCS7

Abstract

Monitoring is at top of the automation system pyramid and is of great importance in almost every industry process. One critical index for a safe process operation is fast and online recognition of the system faults which must necessarily be removed at incipient moments. Distributed control systems (DCS) are supplanted the conventional automation systems to eliminate the existing infirmities. Although DCSs are being widely used in the industry, but monitoring of industrial systems is still very problematic in case of complicated systems. This paper presents a simple method for online fault detection and fault diagnosis on DCS-PCS7. The method utilizes multivariable statistics and data projection by using Principal Component Analysis (PCA) method. At first, the data are transferred from PCS7 to an interface software (MATLAB) for ease of processing. When the data are processed, they are sent back to PCS7 by means of OPC communication protocol. The KepServerEX is used to implement the OPC communication protocol. Secondly, this paper proposes a fault diagnosis method to effectively monitor the different process conditions for Fars Province Gas Pressure Reduction Station. The model data of a real gas pressure reduction station under various operating conditions is utilized to validate the superiority of the proposed approach. It is shown that the proposed method is capable of monitoring of the process status with desirable performance.