Failure Behavior Identification for a Space Antenna via Neural Networks

Using neural networks, a method for the failure behavior identification of a space antenna model is investigated. The proposed method employs three stages. If a fault is suspected by the first stage of fault detection, a diagnostic test is performed on the antenna. The diagnostic test's results are used by the second and third stages to identify which fault occurred and to diagnose the extent of the fault, respectively. The first stage uses a multi-layer perceptron, the second uses a multi-layer perceptron and neural networks trained with the quadratic optimization algorithm, a novel training procedure, and the third stage uses back-propagation trained neural networks.