2 resultados para Committees

em Cambridge University Engineering Department Publications Database


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This brief note reviews five papers which were presented at the 1993 IFAC World Congress, on the theme 'standards and guidelines for computer-aided control engineering (CACE)'. This session was organized as part of the CACE Software Standardization Initiative, a combined effort of the IFAC and IEEE Control System Society committees on standards. The motivation of this report is to note the substantial progress that was made in this initiative, and to provide the basis for further discussion and work. The papers under review were concerned with integrated design environments, the use of the EXPRESS language for defining standard data structures, database management, user interfaces, and the modeling and simulation of hybrid systems.

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Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.