Fault Diagnosis Method Based On Immune Dominant Clone Cultural Algorithm And Its Application

Immune dominant clone selection algorithm is a novel immune algorithm with strong global search capabilities. It combined with cultural algorithm, then come out Immune Dominant Clone Cultural Algorithm (IDCCA). It can make better use of a priori knowledge to guide the evolution of populations. And design a new dynamical gorithm accepts a function to promote a culture of internal knowledge update and improve the algorithm’s search capabilities. The algorithm for support vector classifier skernel parameter optimization, structure classifier of good properties for data classification of Wine dataset and fault diagnosis of chemical processes in TE. And making compared with fault diagnosis method based on immune dominant clone select algorithm (IDCSA), and the experimental results show that the algorithm can search optimization kernel function parameters of SVM accurately. It can improve the accuracy of fault diagnosis with application value.Finally, the fault diagnosis method based on immune dominant clone cultural algorithm (IDCCA) applied to fault ethylene cracking furnace, and compared with the fault diagnosis based on immune dominant clone select algorithm (IDCSA). It turns out that whether in two-category or multi-category classification, fault diagnosis accuracy rate of IDCCA is far better than IDCSA.