Research On Condition Diagnosis Technology Of Hydrodynamic Bearing Based On Acoustic Emission Detection Method

Hydrodynamic bearing is one of important support parts for steam turbine in power plant; bearing fault is a direct threat to the normal operation of the turbo-generator unit. Hydrodynamic bearings operate in complex environment, the current lubrication monitoring methods have some limitations in on-time and accurate diagnose of bearing lubrication condition. Developing a technology used for on-time diagnosing of hydrodynamic bearings condition is an important measure to enhance the safety and economy of power plant operation.Acoustic emission detection technology for monitoring hydrodynamic bearing lubrication condition is mainly studied in this dissertation. At first, using wavelet transform to do detailed analysis for bearing acoustic emission signals. Study results show that the detailed layer signals have obvious characteristics after multi-layer wavelet decomposition, and different detailed layer signals show different characteristics; the adaptive noise reduction effect of wavelet is obvious, which can be able to filter out the noise well and make bearing acoustic emission signal more apparent after wavelet decomposition and reconstruction.Secondly, according to the bearing characteristics of acoustic emission signal, a specific identification method based on the analysis of acoustic emission parameters for hydrodynamic bearing is proposed, which is by comparing hits, events and energy of acoustic emission to the bearing power loss and then three characteristic indicators, the hits power ratio, the events power ratio and the energy power ratio can be obtained.Based on calculation and analysis of experimental data, we can come to the determination interval of new acoustic emission characteristic indicators, and the new criterion and its determination interval are tested through different experimental test data. Compared to the traditional methods of acoustic emission parameters analysis, the new discrimination method is targeted, accurate and more suitable for judgment of bearing lubrication state.Finally, in this thesis, on the base of software platform of LabVIEW, a prototype system based on acoustic emission signal for hydrodynamic bearing online monitoring is designed and developed, in which the new signal analysis methods and the new lubrication condition discrimination methods are integrated. Compared to PCI-2 acoustic emission detection system, this system is simple, reliable, accurate, and responsive on detection of hydrodynamic bearing fault.