Research On Preventive Maintenance And Reliability Of Wind Turbines Based On The Markov Process

As global environmental issues have become more and more concerned and focused,the reserves of primary energy are gradually decreasing,and there is an urgent need to develop new energy sources to alleviate the energy crisis.As a renewable energy source,wind power generation will be continuously developed and utilized in the future.Due to work needs,wind turbines are generally built in relatively remote areas and the environment is harsh,which makes maintenance work facing huge challenges.Therefore,the daily maintenance of wind turbines is very important.Based on the time-continuous Markov process,the traditional wind turbine system regular maintenance strategy is analyzed.This thesis studies the state-based maintenance strategy of wind turbines.While ensuring the long-term stable operation of the unit system,it must also consider the lowest cost of maintenance.Based on the above,the maintenance decision is optimized.The specific research content and methods of this article are as follows:(1)For the existing multi-state repairable equipment,according to the definition of multi-state components,there are complete maintenance and incomplete maintenance theories.By analyzing the life distribution and degradation laws of wind turbine equipment,the Markov process is used to construct the reliability analysis model of the equipment under different maintenance conditions.At the same time,the state transition differential equation and relationship matrix of each model can be obtained.Finally,several examples are analyzed,and the results show that condition-based maintenance has greater advantages in improving the reliability of components.(2)Aiming at the situation that the equipment cannot be restored to a new state with certain maintenance methods or measures under actual working conditions,based on the Markov process in the discrete state,the reliability of the equipment under different maintenance conditions is analyzed.Considering that certain maintenance measures cannot guarantee the complete recovery of the system,combined with the incomplete maintenance model,the system is repaired according to the state of the system,and a preventive maintenance model for wind turbine equipment is established.By recursively and analytically solving the model,the mathematical expression of the steady-state availability of the system can be obtained.On this basis,in order to make the system work stably and reliably,the optimal detection period and maintenance threshold of the system in this model can be obtained.Finally,use specific case data to verify the feasibility of the model and algorithm.(3)Aiming at the wind turbine system composed of multiple joint degraded components,considering the incompleteness theory of preventive maintenance measures,and adopting the condition-based-opportunity maintenance measures,the system state space division model is constructed,and the corresponding system joint is obtained by analyzing and solving.The steady-state probability density function,in order to ensure the lowest cost rate during the long-term operation of the system,constructs the corresponding optimization model,and finally obtains the optimal detection period of the system and the threshold of preventive maintenance.Finally,through simulation experiments on a certain series of equipment parameters of wind turbines,the effectiveness of the maintenance decision optimization model is verified.The results show that for repairable multi-component system equipment that cannot be com-pletely restored by repair measures,this model helps optimize the maintenance decision,thereby reducing the maintenance cost of the entire system.