| New methodologies for the automation of vibration monitoring and for information fusion are introduced in this dissertation. The foundation of all the techniques is neural network technology, and most of them also utilize fuzzy logic and genetic algorithms. The combination of these paradigms contributes to high speed and flexibility of the systems developed and allows us to take advantage of the strong features of each paradigm.; For classification of vibration data gathered by one sensor exclusively, a hybrid neuro-fuzzy system was developed that extensively utilizes the traditional vibration analysis methods. The presence of peaks at characteristic frequencies of faults, their harmonics and their immediate neighborhood is assessed. Then the amplitudes, transformed by membership functions, constitute the input to a Kohonen self-organizing map with categorization. The output of the network is the fault present.; The methodologies devised for information fusion can be subdivided into techniques consisting of one fusion step and techniques consisting of multiple fusion steps. The one-level fusion methods developed include a probabilistic neural network-based technique and a neuro-fuzzy-genetic technique. The foundation of the first method is Bayesian decision theory as implemented by probabilistic neural networks. The second technique uses fuzzy set theoretic aggregation connectives, the parameters of which are established by a genetic algorithm. These connectives are capable of combining information not only by union and intersection used in traditional theories but also by compensatory connectives that mimic closely the human reasoning process.; Among the multi-step fusion techniques devised, the most general one is a hierarchical scheme, intended for the particularly difficult case, when no knowledge about the reliability, degree of redundancy/complementarity or the structure of the fusion hierarchy exists. The scheme developed determines all those parameters on the sole basis of the training data without any supplementary knowledge about the fusion hierarchy. The methodologies developed were applied to the problem of classification of vibration data from laminar flow table rolls in a steel sheet manufacturing mill and rolling element bearings data, and the results are described. |
