Study On Performance Degeradation And Life Prediction Of Mechanical Rotary Components

With the progress of society,the development of science and technology and the improvement of modem industrial,mechanical equipment also tends to be large-scale,high-speed,high-precision,systematization and automation.To meet the requirement of the production,the function of mechanical equipment becomes more complicated and the working environment becomes more abominable and changeable.Under long-term continuous operation,the equipment will gradually age and the remaining life will gradually decrease,leading to inevitable fault.The fault may result in huge economic losses and even catastrophic accidents,forming a serious social impact.Major mechanical equipment,such as gas turbines,aeroengines,wind turbines,are all indispensable for rotary components.As the key components,such as bearings,gears and shafts,their working status will influence the performance and safe operation of the equipment.If any individual component fails,it is possible to trigger a series of chain reactions,resulting in the breakdown of the equipment,even the paralysis of whole product line.Mechanical rotary components will go through a process from normal to degradation and then to failure during their service.In this period,a series of different performance degradation status are existed.The traditional fault diagnosis is mainly concerned about the binary mode of health and malfunction.When the fault is diagnosed,the performance of mechanical components may be severely degraded.In order to diagnose the fault as soon as possible,we should pay attention to the degradation processes of mechanical rotary components.The study on performance degradation and life prediction of mechanical rotary components is helpful to reduce the risk of equipment,avoid catastrophic accidents caused by equipment failure,reduce unnecessary equipment maintenance costs and improve equipment efficiency.It is of great significance for improving the economic and social benefits of enterprises and promoting the development of national economy.The traditional fault diagnosis technology usually only classifies and identifies the binary mode of health and malfunction.To overcome this problem,this paper focuses on the performance degradation of mechanical rotary components.Based on the study of the mechanism of performance degradation,the method of tracking and identifying the performance degradation status and the method of life prediction are studied.The main research contents include the following four aspects:(1)Study on mechanism of performance degradation of mechanical rotary components under vibration-damage coupling effect.A performance degradation model of mechanical rotary components under vibration-damage coupling effect is established,and an approximate numerical solution method of the coupling model is proposed based on the iterative operation.Then the cracked rotor is taken as an example to carry out a detailed analysis and study.The competing failure criterion of the crack rotor is analyzed and the performance degradation index is established.The influence of the nonlinear vibration behavior and the factors including the rotational speed,the unbalance eccentricity distance,the eccentricity angle and the damping coefficient on the performance degradation evolution of the crack rotor are analyzed.The research results show that ignoring the vibration-damage coupling effect leads to erroneous performance degradation life estimation.For a cracked rotor,when the speed is far away from the resonance region,it may also cause rapid degradation of the performance due to the bifurcation of vibration under some parameter families.Minimizing the unbalanced eccentricity and increasing damping can effectively slow down the degradation speed of the cracked rotor and prolong the performance degradation life.(2)Study on the method for tracking and identifying the degradation status of mechanical rotary components based on phase space warping.An improved phase space warping method is proposed based on the characteristics of mechanical rotating parts running periodically.In view of the shortage of the large calculation amount of the original phase space warping method and the poor resolution of the similar degenerate state,an improved method for calculating the damage tracking function and an improved degradation information extraction method are proposed.The results of numerical simulation and experiment verification show that compared with the original method,the improved phase space warping method effectively reduces the cost of calculation.The performance degradation status tracking results are more smooth and accurate.It is more able to distinguish the similar degradation status.It can be applied to real time tracking and identifying of the performance degradation status.(3)Study on life prediction under non-stationary loads based on physical model.A frequency domain method for predicting fatigue life under non-stationary random loading is proposed.The valid intrinsic mode functions(IMF)for fatigue damage are obtained through empirical mode decomposition and selection.A simplified method for calculating the rain-flow cycle distribution in non-Gaussian process is proposed,and the rain-flow cycle amplitude distribution of each valid IMF is calculated.By means of weighted average,the distribution of rain-flow cycle amplitude of valid IMF is synthesized to simulate the rain-flow cycle amplitude distribution of the original stress history.Combined with linear damage accumulation criterion,fatigue life prediction under non-stationary loading is realized.The simulation of various types of non-stationary loads shows that this method is suitable for various types of non-stationary loads in engineering practice and does not need to obtain prior knowledge of the original stress history.Compared with the traditional time domain method of fatigue life prediction,this method avoids a lot of statistical counting and complex dynamic calculation and greatly reduces the computational cost.(4)Study on life prediction based on physics-data hybrid model.A method for predicting residual life based on physics-data hybrid model is proposed.The damage evolution model is established by the qualitative analysis of the damage evolution process.The improved phase space warping method is used to extract the damage characteristics as the performance degradation index.The performance degradation process is automatically identified by the Z statistics and Chebyshev inequality.The state space model of the damage evolution model parameters is established.The model parameters are updated by unscented Kalman filtering to achieve the residual life prediction.The method is verified by bearing accelerated life test.The results show that the method can combine the advantages of the physical model and the data driven life prediction method organically,and make full use of the damage evolution information obtained from the study of the mechanism of performance degradation and from the historical data and real-time data.Compared to the method based on the single physical model and the single data driven method,the life prediction of the proposed method can converge to the real value faster,and the prediction results are more stable and accurate.