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Optimal Observability Analysis of Gimbled Inertial Navigation System on the Moving Base
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作者 于家城 陈家斌 《Journal of Beijing Institute of Technology》 EI CAS 2004年第4期369-372,共4页
To investigate the observability of gimbled inertial navigation system when the base moves on the basis of piece-wise constant system's observability theory and singular value decomposition, the variation of the s... To investigate the observability of gimbled inertial navigation system when the base moves on the basis of piece-wise constant system's observability theory and singular value decomposition, the variation of the singular value in the observability matrix with time is discussed. The simulation results reveal that only if orientation angle is 60° and the flight route is S-figure in initial alignment, the optimal observability is obtained, thus a theoretical foundation for fast and accurate alignment of GINS is provided. 展开更多
关键词 gimbled inertial navigation system (GINS) OBSERVABILITY sigular value condition number
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Shafting misalignment fault diagnosis by means of motor speed signal and SVD-HT method
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作者 YU Zhen AN Qi +1 位作者 SUO Shuangfu QIU Zurong 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第3期352-370,共19页
Aiming at the deficiency of diagnosis method based on vibration signal,a novel method based on speed signal with singular value decomposition and Hilbert transform(SVD-HT)is proposed.The fault diagnosis mechanism base... Aiming at the deficiency of diagnosis method based on vibration signal,a novel method based on speed signal with singular value decomposition and Hilbert transform(SVD-HT)is proposed.The fault diagnosis mechanism based on the speed signal is obtained by constructing the shaft misalignment fault model firstly.Then the SVD-HT method is applied to the processing of the speed signal.The accuracy of the SVD-HT method is verified by comparing the diagnosis results of the order spectrum method and the SVD-HT method.After that,the diagnosis results based on vibration signal and speed signal under no-load and load patterns are compared.Under the no-load pattern,the amplitudes of the speed signal components f_(r),2f_(r) and 4f_(r) are linear with the misalignment.In addition,under the load pattern,the amplitudes of the speed signal components f_(r),2f_(r) and 4f_(r) have a linear relationship with the load.However,the diagnosis result of the vibration signal does not have the above characteristics.The comparison results verify the robustness and reliability of the speed signal and SVD-HT method.The method presented in this paper provides a novel way for misalignment fault diagnosis. 展开更多
关键词 servo motor speed signal misalignment fault sigular value decomposition(SVD) Hilbert transform(HT)
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Characteristic Analysis and Harmonic Feature Identification of Micro-Vibration on Flywheels
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作者 YIN Xianbo SHENG Xiaowei +1 位作者 XU Yang SHEN Yan 《Journal of Donghua University(English Edition)》 CAS 2021年第1期28-35,共8页
To avoid the negative effects of disturbances on satellites,the characteristics of micro-vibration on flywheels are studied.Considering rotor imbalance,bearing imperfections and structural elasticity,the extended mode... To avoid the negative effects of disturbances on satellites,the characteristics of micro-vibration on flywheels are studied.Considering rotor imbalance,bearing imperfections and structural elasticity,the extended model of micro-vibration is established.In the feature extraction of micro-vibration,singular value decomposition combined with the improved Akaike Information Criterion(AIC-SVD)is applied to denoise.More robust and self-adaptable than the peak threshold denoising,AIC-SVD can effectively remove the noise components.Subsequently,the effective harmonic coefficients are extracted by the binning algorithm.The results show that the harmonic coefficients have great identification in frequency domain.Except for the fundamental frequency caused by rotor imbalance,the harmonics are also caused by the coupling of imperfections on bearing components. 展开更多
关键词 FLYWHEEL MICRO-VIBRATION sigular value decomposition comined with the improved Akaike Information Criterion(AIC-SVD) harmonic coefficient binning algorithm
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