Damage identification using support vector machines

Abstract

Support vector machines have recently been established as a powerful tool for classification and regression problems. Their use in the field of damage identification is illustrated here with reference to two problems which can be naturally cast in terms of classification. The first is a fault classification problem for ball bearings and the second looks at locating damage within a framework structure. The performance is compared to more established means of engineering pattern recognition.