Study of plantwide disturbance diagnosis

Abstract

In the highly complex and integrated chemical process plants, it is a challenge to prevent disturbances from propagating from one unit to other interconnected un'its. Moreover, in today's world chemical process plant operation is relying highly on automated control systems, Automation tends to make the plant vulnerable to disturbances if the fault is not detected and diagnosed within the appropriate time scale in the context of process dynamics. Disturbances that propagate throughout the plant and create plantwide oscillations are originated due to various faults such as sensor faults, valve faults, process faults and controller tuning faults. One important characteristic of this kind of nonlinear faults is that they can create oscillation with a fundamental frequency and its harmonics. Once the frequencies, amplitudes and phases of the fundamental oscillation and its harmonics are estimated, these information can be utilized to diagnose the root-cause of plantwide or unitwide disturbances. For this thesis work, at first the Three Tank Level plus Temperature Control pilot plant set up of the Department of Chemical Engineering, BUET was brought under complete working condition, The utility section was serviced and several defective transmitters of the set up were repaired and replaced, A data acquisition system using ADAM 5000 TCPIIP Module was developed for the pilot plant set up to measure and log variables for the purpose of running the experiment and analyzing the logged data. A Human Machine Interface (HMI) was developed for the entire pilot plant set up using MatLab OPC toolbox and Simulink to control and monitor the pilot plant system. Models of the various part of the system were identified and PI controllers were designed accordingly. Both feedback controllers and cascade controllers were designed for the system. After preparing the laboratory set up for experimental work, fault in the form of valve stiction was introduced to create plantwide oscillation(s), Experiments were performed for varying amount of stiction and data were collected for plantwide oscillation diagnosis. In this study, a novel data driven off-line time domain method was developed to troubleshoot plantwide disturbances using harmonic analysis, Simple linear least square regression techniques and Fernando Quinn's technique were used to determine the amplitude, frequency and phase information of the time series data, Harmonically related components were then used to define a new index called Total Harmonic Contcnt (THC), which was used to quantify the harmonic information. The proposed THC index was evaluated usmg experimental data, simulated Nonlinear Dynamic Vinyl Acetate Process data and South East Asia Refinery industrial data. The proposed methodology was successful in identifying root-cause of plantwide oscillation for all cases of experimental, simulated and industrial data