This paper presents a theoretical model for analyzing the dynamic characteristic such as natural frequencies and vibration mode shapes of cracked gears. The influence of crack position and crack size on the dynamic characteristic of gears is thoroughly investigated using the proposed theoretical model as well as the finite element method (FEM) for the sake of model validation. The theoretical analysis and numerical simulation show that the influence of crack size and crack position on the dynamic responses of cracked gears is significant and that the influence of crack position is larger than that of crack size. The natural frequencies drop with the increase of crack size and the low order natural frequencies drop more notably. The natural frequencies drop more significantly when crack is located at tooth root than at tooth tip. The vibration mode shapes of cracked gear tooth are very different from those of gear tooth without crack, and the vibration amplitude increases significantly in crack neighborhood. These observations are very valuable for damage detection and fault diagnosis of gear system.

Through investigating intelligent diagnosis method of Computational Intelligence (CI) and studying its application in fault feature extraction, a gear fault detection and Virtual Instrument Diagnostic System is developed by using the two hybrid programming method which combines both advantages of VC++ and MATLAB. The interface is designed by VC++ and the calculation of test data, signal processing and graphical display are completed by MATLAB. The pro-gram converted from M-file to VC++ is completed by interface software, and a various multi-functional gear fault di-agnosis software system is successfully obtained. The software system, which has many functions including the intro-duction of gear vibration signals, signal processing, graphical display, fault detection and diagnosis, monitoring and so on, especially, the ability of diagnosing gear faults. The method has an important application in the field of mechanical fault diagnosis