There are many active substances in natural resources.After years of research,researchers at home and abroad have extracted active compounds and proved that these compounds have low toxicity and high efficiency,but th...There are many active substances in natural resources.After years of research,researchers at home and abroad have extracted active compounds and proved that these compounds have low toxicity and high efficiency,but the toxicity of these compounds cannot be ignored.In this paper,the research progress on the toxicity of compounds isolated from various natural substances is reviewed,which provides a reference for the further development and rational utilization of natural compounds.展开更多
Condition monitoring and fault diagnosis of gearboxes play an important role in the maintenance of mechanical systems.The vibration signal of gearboxes is characterized by complex spectral structure and strong time va...Condition monitoring and fault diagnosis of gearboxes play an important role in the maintenance of mechanical systems.The vibration signal of gearboxes is characterized by complex spectral structure and strong time variability,which brings challenges to fault feature extraction.To address this issue,a new demodulation technique,based on the Fourier decomposition method and resonance demodulation,is proposed to extract fault-related information.First,the Fourier decomposition method decomposes the vibration signal into Fourier intrinsic band functions(FIBFs)adaptively in the frequency domain.Then,the original signal is segmented into short-time vectors to construct double-row matrices and the maximum singular value ratio method is employed to estimate the resonance frequency.Then,the resonance frequency is used as a criterion to guide the selection of the most relevant FIBF for demodulation analysis.Finally,for the optimal FIBF,envelope demodulation is conducted to identify the fault characteristic frequency.The main contributions are that the proposed method describes how to obtain the resonance frequency effectively and how to select the optimal FIBF after decomposition in order to extract the fault characteristic frequency.Both numerical and experimental studies are conducted to investigate the performance of the proposed method.It is demonstrated that the proposed method can effectively demodulate the fault information from the original signal.展开更多
文摘There are many active substances in natural resources.After years of research,researchers at home and abroad have extracted active compounds and proved that these compounds have low toxicity and high efficiency,but the toxicity of these compounds cannot be ignored.In this paper,the research progress on the toxicity of compounds isolated from various natural substances is reviewed,which provides a reference for the further development and rational utilization of natural compounds.
基金supported by the National Key R&D Program of China(No.2019YFB2004604)the National Natural Science Foundation of China(No.52075477)the Key R&D Program of Zhejiang Province(No.2021C01139),China。
文摘Condition monitoring and fault diagnosis of gearboxes play an important role in the maintenance of mechanical systems.The vibration signal of gearboxes is characterized by complex spectral structure and strong time variability,which brings challenges to fault feature extraction.To address this issue,a new demodulation technique,based on the Fourier decomposition method and resonance demodulation,is proposed to extract fault-related information.First,the Fourier decomposition method decomposes the vibration signal into Fourier intrinsic band functions(FIBFs)adaptively in the frequency domain.Then,the original signal is segmented into short-time vectors to construct double-row matrices and the maximum singular value ratio method is employed to estimate the resonance frequency.Then,the resonance frequency is used as a criterion to guide the selection of the most relevant FIBF for demodulation analysis.Finally,for the optimal FIBF,envelope demodulation is conducted to identify the fault characteristic frequency.The main contributions are that the proposed method describes how to obtain the resonance frequency effectively and how to select the optimal FIBF after decomposition in order to extract the fault characteristic frequency.Both numerical and experimental studies are conducted to investigate the performance of the proposed method.It is demonstrated that the proposed method can effectively demodulate the fault information from the original signal.