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Variogram-based fault diagnosis in an interconnected tank system
Abdelmalek Kouadri1, Mohanad Amokrane Aitouche, Mimoun Zelmat
1Applied Control Laboratory, University of Boumerdes, Av. de l'indépendance, 35000 Boumerdès, Algeria. a_kouadri@hotmail.com
ISA Transactions
|February 29, 2012
Summary
This study introduces a novel fault diagnosis method for the DTS-200 pilot plant using variogram analysis to detect sensor faults. The approach effectively extracts fault parameters by fitting mathematical models to empirical data for improved process monitoring.
Area of Science:
- Process control and automation
- Data analysis and modeling
- Fault detection and diagnosis
Background:
- Industrial process monitoring relies on accurate sensor data.
- Sensor malfunctions can lead to incorrect process assessments and operational issues.
- The DTS-200 pilot plant presents a relevant case study for evaluating fault diagnosis techniques.
Purpose of the Study:
- To develop and validate a fault diagnosis method for sensor faults in a three-tank system (DTS-200 pilot plant).
- To utilize variogram analysis for extracting sensor fault parameters.
- To demonstrate the applicability of the proposed method in real-time process monitoring.
Main Methods:
- Variogram analysis to characterize data distribution and extract fault parameters.
- Nonlinear regression techniques for estimating model coefficients.
- Application to the DTS-200 pilot plant for experimental validation.
Main Results:
- Successfully extracted sensor fault parameters using variogram analysis.
- Identified the best-fitting mathematical models for empirical data.
- Demonstrated the method's potential for effective process monitoring.
Conclusions:
- Variogram analysis is a viable technique for sensor fault diagnosis in complex systems.
- The proposed method offers a robust approach for identifying and characterizing sensor faults.
- This technique can enhance the reliability and safety of industrial process control.
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