The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Neverthele...The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.展开更多
The chirplet transform is the generalization form of fast Fourier transform , short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. How...The chirplet transform is the generalization form of fast Fourier transform , short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. However, the chirplet transform has not inherent inverse transform, and can not overcome the signal reconstructing problem. In this paper, we proposed the improved chirplet transform (ICT) and constructed the inverse ICT. Finally, by simulating the harmonic voltages, The power of the improved chirplet transform are illustrated for harmonic detection. The contours clearly showed the harmonic occurrence time and harmonic duration.展开更多
In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the s...In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.展开更多
基金National Natural Science Foundation(NNSF)of China under Grant 61771059National Natural Science Foundation(NNSF)of China under Grant 61471046Beijing Natural Science Foundation under Grant 4172022 to provide fund for conducting experiments。
文摘The roll angular rate is much crucial for the guidance and control of the projectile.Yet the high-speed rotation of the projectile brings severe challenges to the direct measurement of the roll angular rate.Nevertheless,the radial magnetometer signal is modulated by the high-speed rotation,thus the roll angular rate can be achieved by extracting the instantaneous frequency of the radial magnetometer signal.The objective of this study is to find out a precise instantaneous frequency extraction method to obtain an accurate roll angular rate.To reach this goal,a modified spline-kernelled chirplet transform(MSCT)algorithm is proposed in this paper.Due to the nonlinear frequency modulation characteristics of the radial magnetometer signal,the existing time-frequency analysis methods in literature cannot obtain an excellent energy concentration in the time-frequency plane,thereby leading to a terrible instantaneous frequency extraction accuracy.However,the MSCT can overcome the problem of bad energy concentration by replacing the short-time Fourier transform operator with the Chirp Z-transform operator based on the original spline-kernelled chirplet transform.The introduction of Chirp Z-transform can improve the construction accuracy of the transform kernel.Since the construction accuracy of the transform kernel determines the concentration of time-frequency distribution,the MSCT can obtain a more precise instantaneous frequency.The performance of the MSCT was evaluated by a series of numerical simulations,high-speed turntable experiments,and real flight tests.The evaluation results show that the MSCT has an excellent ability to process the nonlinear frequency modulation signal,and can accurately extract the roll angular rate for the high spinning projectiles.
基金This work was supported by U.S. Department of Defense Science Research Fund （Grant No. DAAD 19-03-1-0375） and the National Natural Science Foundation of China （Grant No. 40774055）.
文摘The chirplet transform is the generalization form of fast Fourier transform , short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. However, the chirplet transform has not inherent inverse transform, and can not overcome the signal reconstructing problem. In this paper, we proposed the improved chirplet transform (ICT) and constructed the inverse ICT. Finally, by simulating the harmonic voltages, The power of the improved chirplet transform are illustrated for harmonic detection. The contours clearly showed the harmonic occurrence time and harmonic duration.
基金funded by the National Natural Science Foundation of China(Grant No.11172131 and 11232007)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.
文摘【目的】深度学习在鸟类物种识别的应用是目前的研究热点,为了进一步提高识别效果,提出一种基于鸟鸣声的Chirplet语图特征和深度卷积神经网络的鸟类物种识别方法。【方法】引入线性调频小波变换(Chirplet transform,CT)计算鸟鸣声信号的语图,输入深度卷积神经网络VGG16模型中,通过对语图进行分类实现鸟类物种的识别。以北京市松山国家自然保护区实地采集的18种鸟类为研究对象,利用Chirplet变换、短时傅里叶变换(short-time fourier transform,STFT)和梅尔频率倒谱变换(Mel frequency cepstrum transform,MFCT)计算得到3个不同的语图样本集,对比分别采用不同的语图样本集作为输入时鸟类物种识别模型的性能。【结果】结果表明:Chirplet语图作为输入时,测试集的平均识别准确率(mean average precision,MAP)达到0.987 1,相对于其他两种输入,得到了更高的MAP值,而且在训练时达到最大MAP值的迭代次数最小。【结论】采用不同的语图特征作为输入,直接影响深度学习模型的分类性能。本文计算的Chirplet语图的鸣声区域相比STFT语图和Mel语图更为集中,特征更明显。因此,Chirplet语图更适合于基于VGG16模型的鸟类物种识别,可以得到更高的MAP值和更快的识别效率。
