Multi-parameter Turntable Health Monitoring System Design And Implementation

Servo turntable,as a turntable system that can achieve high precision and high stability,is often applied to key equipment that requiring high performance,and the working state of the servo turntable will directly affect the operating state of the overall equipment.Therefore,health monitoring and fault diagnosis of the servo turntable are very important.Based on the actual needs of a specific project,this paper develops a turntable health monitoring system with fault diagnosis and health assessment functions.The main content of this article includes the following aspects:(1)The hardware platform of the turntable health monitoring system was built according to actual needs and actual conditions.Firstly,the servo turntable system is introduced from the aspects of components,working principles,performance indicators,etc.,and then the actual needs of the turntable health monitoring system are analyzed.According to the functional requirements and performance requirements of the turntable health monitoring system,the technical route of the turntable health monitoring system was determined.Then it analyzes the possible failure modes of the turntable system,determines the monitoring parameters according to the possible failure modes,and combines the previous experience of the project to determine the location of the monitoring parameters.Finally,the selection of the chassis,acquisition card and sensor was completed,and the hardware platform of the turntable health monitoring system was built.(2)In view of the non-stationary,non-linear,and multi-component characteristics of the signal of the servo turntable in the working state,this paper adopts the Local Projective Method(LPM)and the self-improvement Adaptive Variational Mode Decomposition(AVMD)based on JS divergence(Jensen-Shannon Divergence,JSD)method performs fault diagnosis on the system,and realizes the fault diagnosis function of the turntable health monitoring system.This article first uses the local projection algorithm to reduce the noise of the signal.In the local projection algorithm,the standard deviation of the signal is taken as the radius of the domain,which realizes the adaptive selection of the radius of the domain.The signal after the noise reduction preprocessing is then subjected to the adaptive variational modal decomposition modified by the JS divergence to decompose the signal into a number of intrinsic mode functions(IMF),and then extract the sensitive IMF based on the kurtosis criterion.Component,and then carry out envelope analysis on the component,and finally realize the fault diagnosis function of the system.Both the simulated signal and the measured signal prove the effectiveness of the method(3)Aiming at the problem that a single indicator is not sensitive to the early degradation of equipment,this paper adopts a feature fusion algorithm based on the minimum matching distance of the self-organizing map neural network(SOM)to perform multiple features on multiple parameters of the system.Feature fusion realizes the health assessment function of the turntable health monitoring system.This paper first extracts the time domain,frequency domain,and RQA(Recurrence Quantification Analysis)features of the various monitoring parameters of the turntable system,and then uses information theory and T-type grey correlation degrees(T-GCD)to reduce the feature set.Then use the feature set in the healthy state to train the SOM network,and finally use the feature fusion algorithm of the SOM minimum matching distance to calculate the health index of the system.When performing feature fusion,the vibration signals in three directions are first fused,and then the vibration signals,stress signals,and displacement signals are fused.After experiments,the effect of multi-parameter feature fusion is significantly better than single-parameter feature fusion.(4)Completed the software platform construction of the turntable health monitoring system according to the hardware selection,use requirements and data volume.First,the functional requirements of the software platform are analyzed,and then the software platform is systematically designed according to the functional requirements,the platform is decomposed into different levels,and the entire software platform is standardized.Then this article determines the development environment and development technology according to the actual situation and performance requirements.In the process of developing the software platform,a state machine framework JSCM(JSON Class State Machine)based on the improved JSON data format is proposed,which greatly improves the reusability of the code and greatly reduces the difficulty of development.After this,the database of the software platform was designed,including the design of the table structure and the design of the relationship between the table and the table.After the database is built,this article begins the design and development of specific software modules and software interfaces.Finally,the software platform and the hardware platform are jointly debugged and tested to verify the usability of the software platform.