He Xufei1, Deng Zhongmin2, Song Zhitao1
Structural Durability & Health Monitoring, Vol.8, No.3, pp. 193-208, 2012, DOI:10.32604/sdhm.2012.008.193
Abstract This paper describes an information optimizing scheme which is developed by integrating rough set and hierarchical data fusion. The novel structural damage indices are extracted using the information from different sources and then imported into probabilistic neural network (PNN) for classification and health assessment. In order to enhance the accuracy of diagnosis, results from separate PNN classification are fused to achieve comprehensive decision. Rough set is employed to decrease the spatial dimension of data. The predictive accuracy of optimizing scheme is demonstrated on a helicopter, taken as an example, with varied sensors, for multiple damage identification. More >
Login
Register
