The Need
Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretability, limiting their effectiveness during the design phase and in systems where operational transients are frequent.

The Technology
This technology introduces a propagation-based fault detection and discrimination (PFDD) method, leveraging qualitative system modeling to simulate fault propagation in both steady and transient states. Using the Integrated System Fault Analysis (ISFA) technique, PFDD characterizes faults by analyzing deviations, trends, and propagation order of system variables. The approach also includes algorithms—brute force and genetic—for optimizing sensor deployment, enabling early-stage design decisions that maximize diagnostic coverage while minimizing sensor costs.

Commercial Applications
• Nuclear power plant monitoring and diagnostics
• Advanced reactor management and control systems
• Industrial process control (chemical, oil & gas, manufacturing)
• Smart building and infrastructure fault detection

Benefits/Advantages
• Diagnoses faults in both steady and transient states, unlike traditional methods limited to steady-state analysis
• Requires minimal historical data, enabling use during system design and in data-scarce environments
• Highly interpretable results, facilitating regulatory compliance and operator trust
• Optimizes sensor placement, reducing hardware costs while maintaining or improving diagnostic accuracy