Design Of Rotating Machinery Fault Diagnosis System Based On Improved HILBERT-HUANG Transform

Rotating machinery is the key equipment in the fields of medical treatment,electric power,aviation and so on,so it is very important to ensure their safe operation.As the mechanical vibration parameters can directly reflect the running state of the equipment,the vibration signal analysis is usually used in the maintenance and condition monitoring of rotating equipment.For most of the vibration signals have significant non-stationarity characteristics,making the fault detection difficult.A fault diagnosis system based on improved Hilbert-Huang transform(HHT)is developed in this paper.The system not only has many features such as multiple sampling channels,fast sampling speed,high precision,but also can be used for vibration signal analysis and fault diagnosis.The system includes three parts:external sensors,integrated vibration signal collector and host computer software.The vibration signal collector mainly uses ARM and FPGA as the core structure to realize the synchronous acquisition function of the 8 vibration signals.Each channel is designed with sensor interface switching circuit,signal conditioning circuit and analog to digital conversion(ADC)circuit.Interface switching circuit can access different types of sensors according to the actual demand.When the 8 signals are collected synchronously,the sampling rate is up to 150 KHz.In addition,the collector is designed with serial port,Ethernet card interface to achieve communication with the host computer.The host computer software is designed under the LabVIEW development environment,which mainly includes three functions:acquisition parameter setting,data saving and signal analysis and processing.The software transmit configuration parameters to the collector through the network port,and the collected data can be saved and played back by the mass storage resources of the computer.In the aspect of signal analysis and processing,this paper deeply studies the principle of the Hilbert-Huang transform algorithm,and proposes the correlation matching extension method and the adaptive ensemble empirical mode decomposition(EEMD)algorithm.These improved algorithms not only reduces the decomposition error caused by the empirical mode decomposition of the vibration signal,but also solves the problem of parameter selection in the ensemble empirical mode decomposition.At the same time these algorithms can effectively improve the effect of the Hilbert-Huang transform algorithm in fault diagnosis of rotating machinery.Finally,the fault diagnosis system is tested by building the vibration experimental platform.The test results show that the system can extract the fault characteristics of rotating machinery.