Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and n...Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and noise subspaces,has been successfully applied for this purpose.However,conventional subspace selection methods relying on fixed thresholds are sensitive to variations in large eigenvalues.Furthermore,the complex disturbances during rotor operation and measurement complicate the identification of blade vibration characteristics.To overcome these challenges,this paper proposes Adaptive Subspace Separation(ASS)and Local Spectral Centroid(LSC)methods to improve the adaptability of subspace selection and the stability of frequency identification,respectively.The impacts of overestimating and underestimating the subspace dimensions on MUSIC's performance are derived mathematically.Simulation and experiments demonstrate the effectiveness of proposed approaches:ASS offers more accurate and stable subspace dimension selection and tracking,while LSC reduces the standard deviation of estimated frequencies by 30 percent.展开更多
The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then...The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude.Blade Tip Timing(BTT)method is one of the promising method to solve these problems.While,it need a high resolution Once Per Revolution(OPR)signal which is difficult to get for the aero-engine.Here,a Coupled Vibration Analysis(CVA)method for identifying blade vibration parameters by a none OPR BTT is proposed.The method assumes that every real blade has its own vibration performance at a given speed.Whereby,it can take any blade as the reference blade,and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying.The proposed method is validated by numerical model.Also,experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively.The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks,which lays a foundation for the reliability improvement of aero-engine.展开更多
Blade vibration monitoring can ensure the safe operation of aeroengine rotor blades.Among the methods of blade vibration monitoring,Blade Tip Timing(BTT)method has attracted more and more attention because of its adva...Blade vibration monitoring can ensure the safe operation of aeroengine rotor blades.Among the methods of blade vibration monitoring,Blade Tip Timing(BTT)method has attracted more and more attention because of its advantages of non-contact measurement.However,it is difficult to install the Once-Per-Revolution(OPR)probe in the confined space of aeroengine,and the failure and instability of the OPR signal will reduce the reliability of the blade vibration analysis results,which directly affects the accuracy of the blade vibration parameters identification.The Multi-Probe linear fitting and Time of Arrival(ToA)Linear Correction method based on the BTT(MP-LC-BTT)without OPR is proposed to reduce the errors of single probe linear fitting method for blade vibration displacement analysis.The proposed method can also correct the calculation error of blade vibration displacement due to the nonlinear change of rotation speed,which can improve the analysis accuracy of the blade vibration displacement.A new blade vibration model conforming to the actual vibration characteristics is established,and the effectiveness of the proposed method is verified by numerical simulation.Finally,the reliability and accuracy of the MP-LC-BTT method have been verified by the experiments which include two high-speed blade test-benches and an industrial axial fan.This method can be used in the actual aero-engine monitoring instead of the BTT method with OPR.展开更多
The noncontact blade tip timing(BTT)measurement has been an attractive technology for blade health monitoring(BHM).However,the severe undersampled BTT signal causes a significant challenge for blade vibration paramete...The noncontact blade tip timing(BTT)measurement has been an attractive technology for blade health monitoring(BHM).However,the severe undersampled BTT signal causes a significant challenge for blade vibration parameter identification and fault feature extraction.This study proposes a novel method based on the minimum variance distortionless response(MVDR)of the direction of arrival(DoA)estimation for blade natural frequency estimation from the non-uniformly undersampled BTT signals.First,based on the similarity between the general data acquisition model for BTT and the antenna array model in DoA estimation,the circumferentially arranged probes on the casing can be regarded as a non-uniform linear array.Thus,BTT signal reconstruction is converted into the DoA estimation problem of the non-uniform linear array signal.Second,MVDR is employed to address the severe undersampling issue and recover the BTT undersampled signal.In particular,spatial smoothing is innovatively utilized to enhance the estimation of covariance matrix of the BTT signal to avoid ill-condition or singularity,while improving efficiency and robustness.Lastly,numerical simulation and experimental testing are employed to verify the validity of the proposed method.Monte Carlo simulation results suggest that the proposed method behaves better than conventional methods,especially under a lower signal-to-noise ratio condition.Experimental results indicate that the proposed method can effectively overcome the severe undersampling problem of BTT signal induced by physical limitations,and has a strong potential in the field of BHM.展开更多
Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like freq...Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.展开更多
With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the uns...With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the unstable operating conditions brought by flexible operation.A vibration measuring method for the shrouded blades of a steam turbine based on eddy current sensors with high frequency response is proposed,meeting the requirements of non-contact heath monitoring.The eddy current sensors produce the signals which are related to the area changing of every blade’s shroud resulting from the rotation of stator.Then an improved blade tip timing(BTT)technique is proposed to detect the vibrations of shrouded blades by measuring the arrival time of each area changing signal.A structure of eddy current sensors is developed in steam turbines and an amplitude modulation/demodulation circuit is designed to improve the response bandwidth up to 250 kHz.Vibration tests for the last stage blades of a steam turbine were carried out and the results validate the efficiency of the improved BTT technique and the high frequency response of the eddy current sensors presented.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52405088 and 92360306)the Postdoctoral Fellowship Program of CPSF,China(No.GZC20241446)+2 种基金the Natural Science Basic Research Program of Shaanxi,China(No.2024JC-YBMS-402)the Fundamental Research Funds for the Central Universities,CHD(No.300102254102)the Foundation of Beilin District,China(No.GX2455)。
文摘Anti-aliasing spectrum analysis is essential for rotor blade condition monitoring based on Blade Tip Timing(BTT).The Multiple Signal Classification(MUSIC)algorithm,which exploits the orthogonality between signal and noise subspaces,has been successfully applied for this purpose.However,conventional subspace selection methods relying on fixed thresholds are sensitive to variations in large eigenvalues.Furthermore,the complex disturbances during rotor operation and measurement complicate the identification of blade vibration characteristics.To overcome these challenges,this paper proposes Adaptive Subspace Separation(ASS)and Local Spectral Centroid(LSC)methods to improve the adaptability of subspace selection and the stability of frequency identification,respectively.The impacts of overestimating and underestimating the subspace dimensions on MUSIC's performance are derived mathematically.Simulation and experiments demonstrate the effectiveness of proposed approaches:ASS offers more accurate and stable subspace dimension selection and tracking,while LSC reduces the standard deviation of estimated frequencies by 30 percent.
基金supported financially by Natural Science Foundation of China(Nos.51775030,91860126)the Fundamental Research Funds for the Central Universities(No.BHYC1703A)。
文摘The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude.Blade Tip Timing(BTT)method is one of the promising method to solve these problems.While,it need a high resolution Once Per Revolution(OPR)signal which is difficult to get for the aero-engine.Here,a Coupled Vibration Analysis(CVA)method for identifying blade vibration parameters by a none OPR BTT is proposed.The method assumes that every real blade has its own vibration performance at a given speed.Whereby,it can take any blade as the reference blade,and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying.The proposed method is validated by numerical model.Also,experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively.The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks,which lays a foundation for the reliability improvement of aero-engine.
基金supports of the National Science and Technology Major Project,China(No.2017-Ⅲ-0009-0035)the Major Program of National Natural Science Foundation of China(No.51790513).
文摘Blade vibration monitoring can ensure the safe operation of aeroengine rotor blades.Among the methods of blade vibration monitoring,Blade Tip Timing(BTT)method has attracted more and more attention because of its advantages of non-contact measurement.However,it is difficult to install the Once-Per-Revolution(OPR)probe in the confined space of aeroengine,and the failure and instability of the OPR signal will reduce the reliability of the blade vibration analysis results,which directly affects the accuracy of the blade vibration parameters identification.The Multi-Probe linear fitting and Time of Arrival(ToA)Linear Correction method based on the BTT(MP-LC-BTT)without OPR is proposed to reduce the errors of single probe linear fitting method for blade vibration displacement analysis.The proposed method can also correct the calculation error of blade vibration displacement due to the nonlinear change of rotation speed,which can improve the analysis accuracy of the blade vibration displacement.A new blade vibration model conforming to the actual vibration characteristics is established,and the effectiveness of the proposed method is verified by numerical simulation.Finally,the reliability and accuracy of the MP-LC-BTT method have been verified by the experiments which include two high-speed blade test-benches and an industrial axial fan.This method can be used in the actual aero-engine monitoring instead of the BTT method with OPR.
基金the National Natural Science Foundation of China(Grant Nos.52105117 and 51875433)the Funds for Distinguished Young Talent of Shaanxi Province,China(Grant No.2019JC-04).
文摘The noncontact blade tip timing(BTT)measurement has been an attractive technology for blade health monitoring(BHM).However,the severe undersampled BTT signal causes a significant challenge for blade vibration parameter identification and fault feature extraction.This study proposes a novel method based on the minimum variance distortionless response(MVDR)of the direction of arrival(DoA)estimation for blade natural frequency estimation from the non-uniformly undersampled BTT signals.First,based on the similarity between the general data acquisition model for BTT and the antenna array model in DoA estimation,the circumferentially arranged probes on the casing can be regarded as a non-uniform linear array.Thus,BTT signal reconstruction is converted into the DoA estimation problem of the non-uniform linear array signal.Second,MVDR is employed to address the severe undersampling issue and recover the BTT undersampled signal.In particular,spatial smoothing is innovatively utilized to enhance the estimation of covariance matrix of the BTT signal to avoid ill-condition or singularity,while improving efficiency and robustness.Lastly,numerical simulation and experimental testing are employed to verify the validity of the proposed method.Monte Carlo simulation results suggest that the proposed method behaves better than conventional methods,especially under a lower signal-to-noise ratio condition.Experimental results indicate that the proposed method can effectively overcome the severe undersampling problem of BTT signal induced by physical limitations,and has a strong potential in the field of BHM.
基金the National Natural Science Foundation of China(Nos.52105117,52222504&51875433)the Funds for Distinguished Young talent of Shaanxi Province,China(No.2019JC-04)。
文摘Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.
基金National Natural Science Foundation of China(No.51775377)National Key Research and Development Plan(No.2017YFF0204800)+2 种基金Natural Science Foundation of TianJin City(No.17JCQNJC01100)Young Elite Scientists Sponsorship Program by Cast of China(No.2016QNRC001)Open Project of Key Laboratory of Underwater Information and Control(No.6142218081811)
文摘With the development of power plants towards high power and intelligent operation direction,the vibrations or failures of blades,especially the last stage blades in steam turbines,happen more frequently due to the unstable operating conditions brought by flexible operation.A vibration measuring method for the shrouded blades of a steam turbine based on eddy current sensors with high frequency response is proposed,meeting the requirements of non-contact heath monitoring.The eddy current sensors produce the signals which are related to the area changing of every blade’s shroud resulting from the rotation of stator.Then an improved blade tip timing(BTT)technique is proposed to detect the vibrations of shrouded blades by measuring the arrival time of each area changing signal.A structure of eddy current sensors is developed in steam turbines and an amplitude modulation/demodulation circuit is designed to improve the response bandwidth up to 250 kHz.Vibration tests for the last stage blades of a steam turbine were carried out and the results validate the efficiency of the improved BTT technique and the high frequency response of the eddy current sensors presented.
