In order to better identify the fault of rotor system, one new method based on kernel orthogonal local fisher
discriminant (KOLFD) is proposed.Considering kernel mapping and iteration-orthgonal idea,training data with
supervision information was mapped to kernel space, computed local with-class scatter and between-class scatter,
constructed kernel fisher discriminant function. To ensure the minimum reconstruction error during deimensionality
reduction, algorithm joined the orthonormal constraints condition,found optimal basic projection vector by iterative
orthogonal approach.Then testing data was mapped by this vector and got new data's class information by neighbor
classifier,and eventually realize fault diagnosis.The experiment of rotor fault diagnosis shows, KOLFD algorithm has
better effect to other manifold learning algorithm.
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