State Recognition And Signal Analysis Of Abnormal Vibration Of Wind Turbine Gearbox

With the progress of economy and society,the country pays more and more attention to the development of clean energy,and has repeatedly issued relevant policies to support its accelerated development.As one of the important representatives of clean energy,wind turbines have injected strong impetus into the country’s sustainable development.However,a wind turbine is a complex equipment that is completed by the combination of multiple components.Especially in recent years,as more and more high-power wind turbine facilities are connected to the grid,its troubleshooting and subsequent operation and maintenance have become an increasingly prominent issue.problem.As an important transmission component of a wind turbine,the gearbox is also the component with the most frequent failures.Therefore,its working state is of great significance to the normal operation of the whole machine.Quickly determining the failure mode of the gearbox also plays a critical role in improving the working efficiency of the unit.This paper takes the fault diagnosis of the wind turbine gearbox as the research purpose,based on the comprehensive analysis of the gearbox system,it focuses on improving the fault diagnosis accuracy and shortening the fault diagnosis cycle,and proposes a fault based on state recognition and signal analysis.diagnosis method.The specific research content is as follows:First,a patent search sample database based on gearbox fault diagnosis was constructed,and the patent layout trends of the gearbox fault diagnosis technology,such as the annual change trend of patent applications,the regional distribution of patent applicants,the distribution of main technical fields,and the distribution of technology life cycles,were analyzed.Through these characteristic elements that can more intuitively reflect engineering practice,the main fault types of wind turbine gearboxes and the applicability of fault diagnosis methods are summarized.Secondly,use the full association relationship matrix to comprehensively analyze the relationship between each component and the target part in the system from the four perspectives of connection,function,position,and energy transfer,divide the complex research object system into modules,and by rejecting domain to select the appropriate critical value to classify the system into modules,selects the module with the greatest relevance to the target part as the critical failure area,analyzes the functions of each component in the critical failure area,and establishes a functional model to make the divided discrete components a new study system.Reasonable determination of the critical value is of great significance to the module division of the research system.The divided modules should not only make the research system more streamlined,but also comprehensively cover the parts that are strongly related to the target part’s fault characteristics.Thirdly,analyze the data types and characteristics of the reliability calculation of the parts in the critical failure area,and respectively solve the stress and strength values of each component,construct the functional function of the part failure,and establish the reliability of the key failure area according to the working principle of the system and the connection structure Sexual block diagram.Sort the reliability of each component,and use the Monte Carlo method to simulate the reliability of each component to verify the rationality of the foregoing calculations.Finally,perform empirical modal decomposition of the vibration signals collected by each component in the critical fault area according to the reliability order,obtain the modal components decomposed into each sub-band,and calculate the energy value of each modal component,and select the energy value Envelope spectrum analysis is performed on the largest component to obtain the characteristic frequency of the vibration signal,thereby determining the fault type of the part.Based on the comprehensive analysis of the gearbox system,the diagnosis method further improves the diagnosis accuracy and shortens the diagnosis cycle at the same time.By analyzing and comparing the vibration data collected by the gearbox in real time,the feasibility of the above fault diagnosis method is verified,and it has strong practical value for the fault diagnosis of a large number of fan gearboxes of the same model.