Artificial Immune-Based Fault Detection System Developed with C# and MATLAB

Artificial immune-based fault detection systems are intelligent monitoring approaches that simulate biological immune system mechanisms, effectively identifying and responding to abnormal conditions in industrial systems. The combined development using C# and MATLAB leverages the strengths of both programming languages - C# handles system architecture and user interaction, while MATLAB focuses on algorithm implementation and data analysis.

In the C# implementation, developers typically construct user interfaces, data acquisition modules, and system control logic using the .NET framework for efficient communication and processing. Key C# components may include Windows Forms or WPF for GUI development, along with threading mechanisms for real-time data processing. The MATLAB portion contains core immune algorithms such as negative selection algorithms or clonal selection algorithms, which train models and identify fault patterns through functions like pattern recognition and statistical analysis. The two programming environments interact through COM components or DLLs generated by the MATLAB Compiler, ensuring seamless data flow between systems using data marshaling and interface contracts.

This hybrid programming approach combines MATLAB's powerful mathematical computation capabilities with C#'s flexibility in engineering applications, resulting in a fault detection system that achieves real-time performance, accuracy, and scalability. The integration allows for efficient matrix operations and signal processing in MATLAB while maintaining robust system control through C#'s object-oriented architecture.