Ground Proximity Warning Computer Automated Test System Development

The Ground Proximity Warning Computer System is a kind of electronics warning equipments, which is widely installed in various transporter currently. It receives the data, which is sent out by inertia! navigation system, wireless altitude instrument, the atmosphere data computer and so. Then the GPWC compared these data with the extreme limit data within the mold processing piece. If there are dangerous during the airplane approaching ground, the GPWC can warn the airplane pilot to adopt the valid measure using two kinds of warning signals of displaying signals and sounding signals. Whether the function of GPWC is normal, directly affect the safety of an airplane. So it is very important to make sure the function of GPWC is normal before the GPWC installed in airplane.Along with the time, the old GPWC testing system has exposured many problems during actual usage, for example the function is not perfect, the level of intelligence is lowly and the credibility is not perfect. Aiming to these problems, in this project we have adopted the virtual instrument technique, general purpose and integration technique, expert knowledge system technique and remote accessing technique. Put forward the solution to the kind of GPWC according to integration auto-testing technique. The aim is substituting the old half-handle testing equipment and realize automatic, intelligently, network testing.First, this text introduces the development of the testing system. Then the text particularly introduces the principle of GPWC and the intercommunion with other aviation electron equipments. On these foundations, we analyses the demanding of testing, and get a certain hardware mode of GPWC testing system, and particularly introduces the hardware constitution.According to the software engineering principle, in this project, we develop the automatic testing software with virtual instrument and the expert systems.Examination and diagnosis of fault is one of the most important work. Based on the foundation of analyzing the GPWC fault tree, we develop the expert systems with C++ language.One of most important research item is using the neural network in fault diagnosis. Firstly, this text introduced the basic knowledge of neural network, then described how to carry the BP network on GPWC fault diagnosis. At last take mode 1 as an example giving actual diagnosis.