Research On Damage Identification Of Helicopter Rotor Blades And Transmission Shafts Based On Fuzzy C-means

Rotorcraft is more and more widely used in the current transportation,rescue,military and other fields,in which the blade structure and transmission shaft structure of autogyro play a very important role,and will be accompanied by many fatal and critical problems.As an important component of aircraft,the working environment of these two components is complex and variable.They often operate for long periods in harsh working environments such as high rotational speed,high strength,high load,and high torque,and are often affected by such factors as wear,impact,cracks,external impact,and rust corrosion.If damage to these key parts of the aircraft is not detected in a timely manner,unpredictable consequences may occur.Therefore,it is of great significance to study and adopt some methods that can obtain data of key parts and develop identification and monitoring methods to determine the operational status of aircraft.This article focuses on the study of single blade structure and transmission shaft structure.The single blade is abstractly simplified as a rotating cantilever beam structure,while the transmission shaft is simplified as a rotating cylindrical shell structure.For cantilever beam structures,the frequency domain values of the cantilever beam in normal and damaged states are first detected through experiments,and compared with the results obtained from simulation and numerical simulation,in order to verify the correctness of the numerical model and improve the dynamic analysis process.For the transmission shaft structure,the time-domain signals of the cylindrical shell under normal,impact rotating imbalance,and crack generation states are detected through experiments,and the vibration response signals of the shaft body are analyzed through modeling.Time domain signals contain a lot of information,which can describe damage from multiple aspects.In order to make the description more intuitive,time domain indicators have been introduced to regroup time domain signals.Before clustering,samples are needed to learn.In this case,it is necessary to use dimensional time domain indicators and non dimensional time domain indicators to describe and express the information contained in the signal from different perspectives,These original time-domain signals redefined and arranged through time-domain indicators will be identified and judged by fuzzy clustering algorithms as samples.The use of fuzzy clustering algorithm based recognition technology for damage identification can make damage identification more intuitive,which is an unsupervised machine learning method.For beams,three types of damage levels were simulated during the process(damage levels of 30%,50%,and 60%,respectively).The results indicate that different degrees of damage to the beam can be reflected in the frequency response function when the external conditions are the same.Specifically,as the damage intensifies,the image gradually moves to the left;When the structure is in a rotating state,the stiffness generated by the stress stiffening effect increases the overall stiffness of the structure,increases the natural frequency of the structure,and the overall frequency response curve shifts to the right.The method based on the curvature of the frequency response function can identify whether the structure has undergone damage in both stationary and rotating states,and can effectively identify the location of the damage,as well as reflect the degree of damage.For cylindrical shell structures,three typical types of axial damage were set up in the article,and the time-domain signals of the shafts were obtained through experimental testing.The results were clustered using a fuzzy clustering algorithm based identification method.The results indicate that this method can effectively separate damage in different states.The different damage states of cylindrical shells in a fixed state have specific locations,which can effectively and intuitively reflect different damages and have a high recognition accuracy;In addition,for cantilever beam structures,this method is also applicable.The time-domain response signals obtained from experiments and numerical simulations can be well matched,and the identification method based on fuzzy clustering algorithm accurately reflects the damage results of the beam.