Fault diagnosis model based on multi-manifold learning and PSO-SVM for machinery

• Fault diagnosis technology plays an important role in the industries due to the emergency fault of a machine could bring the heavy lost for the people and the company. A fault diagnosis model based on multi-manifold learning and particle swarm optimization support vector machine(PSO-SVM) is studied. This fault diagnosis model is used for a rolling bearing experimental of three kinds faults. The results are verified that this model based on multi-manifold learning and PSO-SVM is good at the fault sensitive features acquisition with effective accuracy.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Tillförlitlighets- och kvalitetsteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Reliability and Maintenance (hsv//eng)

Nyckelord

fault diagnosis

multi manifold learning

particle swarm optimization

support vector machine

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