A Comprehensive Experimental Liquid-Level Control System for Advancing Fault Diagnosis Research Innovation: Data, Models, and Procedures

This work addresses the development of a laboratory benchmark system designed for testing and comparing model-based fault diagnosis algorithms. We selected a liquid-level control system with three interconnected storage tanks as the physical process. We provide a detailed description of the first-principles mathematical modeling for deriving the state-space equations of the physical process. System identification was performed using elementary least squares to estimate the model parameters from input/output data. The primary contribution of this paper is the presentation of an open-access repository containing extensive sensor and actuator data from experiments on a physical process experiencing faults. This repository enables researchers to validate their algorithms using sensory data from a real-world process subjected to realistic uncertainty and measurement challenges. The validation of the identified dynamic model and its agreement with the collected data demonstrate the capabilities of the proposed system for testing and comparing model-based fault detection algorithms.