The Application Of Fractal In Fault Diagnosis Of Gear Box

In modern society, it is an important problem to condition monitoring and fault diagnosis of mechanical equipment system and has being paid more and more attention to, for it has great economy and project value. In recent years, many scholars have made a lot of job on it, and put up some new methods and technologies of fault diagnosis. It is a new trend in academic circle of the world that fractal theory being applied in the field of machinery fault diagnosis. Used with fractal theory, the running state of the system can be analyzed not qualitatively but also quantitatively, and then the faults lf complex machinery system can be diagnosed. Rolling bearing and gear are common components in gear box. Their running state will influence the performance of the whole machine directly. In this paper, on the base of analyzing the vibration mechanism of rolling bearing and gear, the types of typical fault were generalized. The methods of vibration signal analysis and fault diagnosis for gear box were introduced in detail. To the basis of easy diagnosis for the gear box, the method of precise diagnosis was put forward. Based on the fractal theory, from fractal fundamental theory, the computing method of binary fractal of gridding dimension was put forward and dimension computing program was worked out. Fine results of dimension computation of pure sinusoidal and cosine signal were obtained. Fractal filtering using short-time fractal dimension as the parametric function was put forward, by which Weirestrass function was fractal filtered. The result was showed that fractal filtering was good in both reducing noise and maintaining time-domain signal. Based on gridding dimension of vibration signal of various sampling rate, a new fractal diagnostic method using dimension distance for the identification of the system condition was established, and got fine identifiable results of this method. In this paper, the type of JZQ250 for gear box is as the research object, and introduced the laboratorial equipments and models of signal collection in detail, and depicted the disposal and election of the observational points simply. The fractal diagnoses of rolling bearings and gears have been shown that the diagnosis result was correct in time-domain. The outsider conditions of fractal diagnosis requests little, as long as in time-domain the diagnosis can immediately attain the diagnosis purpose. There is a good versatility in the judgement that realizes systematic state accurately.