Development Of Condition Monitoring System Of Motorized Spindle Based On LabVIEW

As one of the key parts of a machining center, the motorized spindle decides thereliability and machining precision of the whole machine. So it is of great applicablevalue to monitor conditions of the motorized spindle which is beneficial to forecast itsdefects, establish its maintenance strategies, and improve its reliability. However, mostof the existing condition-monitoring techniques on spindle take the mechanical spindleas the object of study, and the research work on condition monitoring of motorizedspindle has not been fully carried out.Therefore, this paper takes a domestic motorized spindle as the research object. Byanalyzing features of faults of bearing, rotor and stator, laws for theirfault characteristic frequency are gotten for improving the ability of wavelet packetdecomposition (WPD) algorithm to recognize conditions of the motorized spindle.Above all, a monitoring system for motorized spindle is developed. Meantime, thispaper carries out an experiment for monitoring conditions of the motorized spindle170XDS30Y22, which shows that this system can accurately monitor and identify thecondition of this motorized spindle. And the main content of this paper are as follows:1. Fault analysis of motorized spindle. Based on the analysis of structure andworking principle of motorized spindle, the motorized spindle was divided into amechanical system and an electrical system. Through investigations and field data, afault analysis of motorized spindle was conducted, and common failures and theirpositions were gotten.2. Fault characteristics analysis of motorized spindle. Based on the analysis offailure mode and vibration mechanism of bearing, this paper carried out a simulationof failure state of bearing by Abaqus software, of which the results are analyzed byDFT algorithm. Then the variation laws of fault characteristic frequency and conditioncharacteristics of bearing were obtained. On the other hand, this paper established theirfault simulation models by Ansoft Maxwell software, and analyzed the outputs of theabove models by DFT algorithm, and then fault characteristic frequency variation lawsand condition characteristics of rotor and stator were finally obtained.3. Research on algorithms for recognizing fault conditions of Motorized spindle.Based on the principle analysis of auto-correlation analysis, amplitude-domain analysis, spectral analysis, time-frequency analysis, and for improving the ability ofWPD algorithm to recognize status of motorized spindle, this paper put forward ainnovational method that the decomposition level of WPD algorithm was optimizedbased on the volatility of the rotate speed of spindle, and the results of WPD algorithmwere quantified by p-standard entropy.4. Designing an overall scheme for the condition monitoring system of motorizedspindle. This paper presented a scheme for monitoring conditions of motorized spindle.Meanwhile, the performance and working principle of devices selected in this paperwere introduced in detail. And this paper selected the LabVIEW software fordeveloping the software platform of condition monitoring system and the Matlabsoftware for developing algorithms for extracting fault features of motorized spindle.5. Development of condition monitoring system of motorized spindle and itsexperimental analysis. A system for monitoring conditions of motorized spindle wasdeveloped, and its structures and operations were given in detail in this paper.Meanwhile, it was used for monitoring conditions of the motorized spindle170XDS30Y22to verify its ability for monitoring and recognizing conditions ofmotorized spindle, which showed that this system could accurately monitor andidentify the condition of this motorized spindle.In the study of this article, a condition monitoring system of motorized spindlewhich is overall, real time, simple and practical is developed, providing the technicalsupport for analyzing and forecasting the defect of motorized spindle, and havingimportant practical value.