Application of Radial Basis Function Neural Network for Information Processing in Fiber Optical Distributed Measuring Systems

摘要

The paper discusses tomography reconstruction of distributed physical fields. The problem is shown to be solved by using distributed measuring networks based on optical fibre sensors. Special attention is paid to tomography measuring networks based on measuring elements with integrated sensitivity. The advantages of radial basis function neural networks (RBFNN) for data processing of signals in the distributed fiber optical measuring systems are studied. RBFNN specifics which enhance the efficiency of computations of physical fields and technical and technological objects under reconstruction are key issues. Comparative analysis of the operating efficiency of RBFNN method and standard analytical and algebraic method for fiber-optical tomography reconstruction is reported.