Monitoring of the crack propagation in welded joint of the tank using multi-class recognition

The numerical analysis of the vertical weld-fabricated steel tank is carried out taking into account the defects of the welds in the form of through-the-thickness cracks of different lengths and numbers, which are located in different zones of the object's ring. The influence of defects on the stress of the tank is estimated in the places of sensors installation under the action of vertical load. The usage of multi-class recognition is proposed by classifier based on Probabilistic Neural Network for monitoring of the crack propagation. Multidimensional vectors of diagnostic features are used for multi-class recognition. The training set of vectors is formed for defect-free and defect conditions, the classifier is trained and tested, the analysis of recognition efficiency is carried out by using the probability of correct multi-class recognition.