A system has been designed which can provide summary information about specific noisy electric pulses that are generated during flight testing. This is important from a telemetry viewpoint, since limited bandwidth often rules out transmitting all of the pulse data. The system is based on a neural network processing paradigm. The neural network serves as a mapping between pulse data inputs and pulse category outputs. Output categories correspond to presence or type of component failure. Extensive computer simulations have shown that the system can recognize qualitative pulse features which are useful for diagnostic purposes. A second version of the system, also using a neural network, was designed to perform data compression. In this case, an entire pulse is efficiently coded for transmission and the original signal is reconstructed upon receiving the coded transmission. Successful simulations for both systems have demonstrated feasibility and have led to a hardware development effort aimed at prototyping a fieldable system. Based on these results, it appears that the neural network approach may be applicable to other diagnostic and data analysis problems arising in component or system testing. 3 refs., 16 figs., 2 tabs
