Abstract: Fluid machinery is widely used in petroleum machinery industry, so the condition monitoring, diagnosis and maintenance of rotating machinery are of important practical value. Taking the typical fault characteristics of rotary fluid machinery as the object, a set of intelligent fault diagnosis system suitable for rotary fluid machinery is designed using LabVIEW software and MATLAB software. In addition to signal acquisition and processing and dynamic balance human-computer interaction system of common fault diagnosis of rotary fluid machinery, an intelligent fault identification system based on BP neural network optimized by genetic algorithm is designed in order to improve the intelligent level of the system. The test results based on the multi-functional rotor test-bed show that this diagnostic system has good fault recognition rate and accuracy rate in the fault diagnosis of rotary fluid machinery. The test system has the characteristics of high precision, complete functions, portability and expansibility, which can be better applied to the fault diagnosis of rotary fluid machinery.

Key words: rotary fluid machinery, fault diagnosis, signal processing, LabVIEW, MATLAB, artificial neural network