In this work,we propose a method using frequency-modulated continuous-wave(FMCW)self-mixing interferometry(SMI)and all-phase fast Fourier transform(APFFT)for simultaneous measurement of speed and distance.APFFT offers...In this work,we propose a method using frequency-modulated continuous-wave(FMCW)self-mixing interferometry(SMI)and all-phase fast Fourier transform(APFFT)for simultaneous measurement of speed and distance.APFFT offers superior accuracy in frequency determination by mitigating issues like the fence effect and spectrum leakage,contributing to the high-accuracy measurement for speed and distance.Both simulations and experiments have demonstrated relative errors at the levels of 10^(−4) and 10^(−3) for distance and speed measurements,respectively.Furthermore,factors impacting measurement performance have been discussed.The proposed method provides a high-performance and cost-effective solution for distance and speed measurements,applicable across scientific research and various industrial domains.展开更多
In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and freq...In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has become a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-convolved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window function is proposed to estimate the parameters of SsO.This method allows for phase-unbiased estimation while maintaining algorithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results validate the effectiveness and superiority of the proposed method.展开更多
To improve the dynamic balancing accuracy of the micro-motor rotor,an unbalanced vibration feature extraction based on an all-phase fast Fourier transform(APFFT)method is proposed.The amplitude and phase of the signal...To improve the dynamic balancing accuracy of the micro-motor rotor,an unbalanced vibration feature extraction based on an all-phase fast Fourier transform(APFFT)method is proposed.The amplitude and phase of the signal are extracted by spectrum analysis after windowing the unbalanced signal.The mathematical model is derived to simulate the weak signal of rotor unbalance.The simulation results show that this method is accurate in extracting the weak signal of the rotor under different noise levels.The micro-motor rotor unbalanced test system is developed for experimental validations.The accuracy and stability of the vibration amplitude and phase extracted by the APFFT are better than the accuracy and stability from the hardware filtering method.The rotor unbalance is reduced by more than 80%.Furthermore,secondary balance of the rotor after the first balance is carried out.The proposed method can still extract the residual unbalance of the rotor.The results demonstrated that the proposed method can achieve a reduction rate of 90%and the accuracy is within 5mg,verifying the effectiveness of the proposed method for high-precision rotor dynamic balance.展开更多
本文主要研究基于全相位快速傅里叶变换(All Phase Fast Fourier Transform,APFFT)的铁路信号频率检测算法。介绍铁路信号的基本概念,并对传统快速傅里叶变换与APFFT的理论基础进行深入分析。通过矩阵分析方法比较传统FFT和APFFT的性能...本文主要研究基于全相位快速傅里叶变换(All Phase Fast Fourier Transform,APFFT)的铁路信号频率检测算法。介绍铁路信号的基本概念,并对传统快速傅里叶变换与APFFT的理论基础进行深入分析。通过矩阵分析方法比较传统FFT和APFFT的性能差异。在实验分析部分,通过具体的数据模拟实验验证APFFT在频率检测方面相较于传统FFT的优势。针对铁路CPFSK(Continuous Phase Frequency Shift Keying)信号,提出基于APFFT的低频率和边缘频率检测技术。通过仿真实验验证所提方法的有效性。总结全相位FFT在铁路信号频率检测中的应用前景与研究价值。展开更多
基金supported by the National Natural Science Foundation of China(No.62005234)the China Scholarship Council Post-Doctoral Program(No.202107230002)the Natural Science Foundation of Hunan Province(No.2024JJ6434).
文摘In this work,we propose a method using frequency-modulated continuous-wave(FMCW)self-mixing interferometry(SMI)and all-phase fast Fourier transform(APFFT)for simultaneous measurement of speed and distance.APFFT offers superior accuracy in frequency determination by mitigating issues like the fence effect and spectrum leakage,contributing to the high-accuracy measurement for speed and distance.Both simulations and experiments have demonstrated relative errors at the levels of 10^(−4) and 10^(−3) for distance and speed measurements,respectively.Furthermore,factors impacting measurement performance have been discussed.The proposed method provides a high-performance and cost-effective solution for distance and speed measurements,applicable across scientific research and various industrial domains.
基金supported in part by Science and Technology Project of State Grid Corporation of China(No.5108-202299269A-1-0-ZB).
文摘In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has become a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-convolved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window function is proposed to estimate the parameters of SsO.This method allows for phase-unbiased estimation while maintaining algorithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results validate the effectiveness and superiority of the proposed method.
基金National Natural Science Foundation of China,Grant/Award Numbers:52202445,11602112。
文摘To improve the dynamic balancing accuracy of the micro-motor rotor,an unbalanced vibration feature extraction based on an all-phase fast Fourier transform(APFFT)method is proposed.The amplitude and phase of the signal are extracted by spectrum analysis after windowing the unbalanced signal.The mathematical model is derived to simulate the weak signal of rotor unbalance.The simulation results show that this method is accurate in extracting the weak signal of the rotor under different noise levels.The micro-motor rotor unbalanced test system is developed for experimental validations.The accuracy and stability of the vibration amplitude and phase extracted by the APFFT are better than the accuracy and stability from the hardware filtering method.The rotor unbalance is reduced by more than 80%.Furthermore,secondary balance of the rotor after the first balance is carried out.The proposed method can still extract the residual unbalance of the rotor.The results demonstrated that the proposed method can achieve a reduction rate of 90%and the accuracy is within 5mg,verifying the effectiveness of the proposed method for high-precision rotor dynamic balance.
文摘本文主要研究基于全相位快速傅里叶变换(All Phase Fast Fourier Transform,APFFT)的铁路信号频率检测算法。介绍铁路信号的基本概念,并对传统快速傅里叶变换与APFFT的理论基础进行深入分析。通过矩阵分析方法比较传统FFT和APFFT的性能差异。在实验分析部分,通过具体的数据模拟实验验证APFFT在频率检测方面相较于传统FFT的优势。针对铁路CPFSK(Continuous Phase Frequency Shift Keying)信号,提出基于APFFT的低频率和边缘频率检测技术。通过仿真实验验证所提方法的有效性。总结全相位FFT在铁路信号频率检测中的应用前景与研究价值。
