Fault Detection and Isolation Based on Artificial Immune System for Injection Molding Machine

A new algorithm of fault diagnosis for injection molding machine based on artificial immune system is proposed. Firstly, the sample data collected from the injection molding machine in different working conditions is analyzed, and the eigenvalues such as mean and variance are obtained and converted into binary strings. These binary strings are called as self-strings. Based on the self-strings, the negative selection algorithm is combined with the clonal selection algorithm to generate a fault detector, which is used for fault detection; and the positive selection algorithm and the clonal selection algorithm are combined to produce a series of separators, which are then used for fault isolation. Finally, simulations are conducted to verify the effectiveness of the proposed method.