Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal fea...Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.展开更多
Due to wear and manufacturing tolerance,the freeplay is unavoidable in the hinges of folding fins,which exerts significant effects on the aerodynamic characteristics.This paper proposes a backbone-curve-based framewor...Due to wear and manufacturing tolerance,the freeplay is unavoidable in the hinges of folding fins,which exerts significant effects on the aerodynamic characteristics.This paper proposes a backbone-curve-based framework for the dynamical identification of folding fins containing the freeplay nonlinearity.With no need to measure the input force signal and the response signals of nonlinear related Degrees of Freedom(DOFs),the proposed method is more direct and elegant than most existing nonlinear identification approaches,and it contains three steps:Firstly,the underlying linear model of the folding fin structure is obtained through the modal test on its linear sub-parts,and then,the harmonic approximation solves the analytical expressions of the backbone curves of measurable DOFs.Secondly,response data measured from the sine-sweep test are used to extract the fitting points of backbone curves for these DOFs.Finally,the curve fitting approach is applied to identify the freeplay parameters.A series of numerical experiments verify the effectiveness of the proposed method.A real-life folding fin structure is also employed to illustrate how the method can be applied.These examples demonstrate that the identification framework can give an accurate dynamic model of the folding fin structure.展开更多
基金Supported by National Natural Science Foundation of China(No.50605065).
文摘Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.
基金financial supports from the Fundamental Research Funds for the Central Universities, China (No. HIT. NSRIF. 2020014)the National Natural Science Foundation of China (No. 12102103)
文摘Due to wear and manufacturing tolerance,the freeplay is unavoidable in the hinges of folding fins,which exerts significant effects on the aerodynamic characteristics.This paper proposes a backbone-curve-based framework for the dynamical identification of folding fins containing the freeplay nonlinearity.With no need to measure the input force signal and the response signals of nonlinear related Degrees of Freedom(DOFs),the proposed method is more direct and elegant than most existing nonlinear identification approaches,and it contains three steps:Firstly,the underlying linear model of the folding fin structure is obtained through the modal test on its linear sub-parts,and then,the harmonic approximation solves the analytical expressions of the backbone curves of measurable DOFs.Secondly,response data measured from the sine-sweep test are used to extract the fitting points of backbone curves for these DOFs.Finally,the curve fitting approach is applied to identify the freeplay parameters.A series of numerical experiments verify the effectiveness of the proposed method.A real-life folding fin structure is also employed to illustrate how the method can be applied.These examples demonstrate that the identification framework can give an accurate dynamic model of the folding fin structure.
