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
