Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early d...Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early diagnosis and subsequent disease-modifying therapies for PD patients, there is an urgent need to identify sensitive and specific biomarkers. Biomarkers can be divided into four categories： clinical, imaging, biochemical, and genetic. Ideal biomarkers not only improve our under- standing of PD pathogenesis and progression, but also provide benefits for early risk evaluation and clinical diagnosis of PD. Although many efforts have been made and several biomarkers have been extensively investigated, few if any have been found useful for early diagnosis. Here, we summarize recent developments in the discovered biomarkers of PD and discuss their merits and limitations for the early diagnosis of PD.展开更多
In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncer...In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncertainty are assumed to be unknown but bounded.The radial basis function (RBF) neural network is used to approximate the sensor fault.Based on the output of the RBF neural network,the sliding mode observer is presented.Using the Lyapunov method,a criterion for stability is given in terms of matrix inequality.Finally,an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.展开更多
A new time-resolved shifted dual transmission grating spectrometer （SDTGS） is designed and fabricated in this work. This SDTGS uses a new shifted dual transmission grating （SDTG） as its dispersive component, which...A new time-resolved shifted dual transmission grating spectrometer （SDTGS） is designed and fabricated in this work. This SDTGS uses a new shifted dual transmission grating （SDTG） as its dispersive component, which has two sub transmission gratings with different line densities, of 2000 lines/mm and 5000 lines/mm. The axes of the two sub transmission gratings in SDTG are horizontally and vertically shifted a certain distance to measure a broad range of 0.1-5 keV time-resolved X-ray spectra. The SDTG has been calibrated with a soft X-ray beam of the synchrotron radiation facility and its diffraction efficiency is also measured. The designed SDTGS can take full use of the space on a record panel and improve the precision for measuring spatial and temporal spectrum simultaneously. It will be a promising application for accurate diagnosis of the soft X-ray spectrum in inertial confinement fusion.展开更多
A new approach is advanced based on wavelet transform in tandem with autoregressive technique. Wavelets and wavelet packets decompose dynamic signal into different bands and pro- vide multiresolution or multiscale vie...A new approach is advanced based on wavelet transform in tandem with autoregressive technique. Wavelets and wavelet packets decompose dynamic signal into different bands and pro- vide multiresolution or multiscale view of signal. Autoregressive technique possesses effective function for short data processing. The approach is abopted to analyse nonstationary vibration sig- nals of mining excavator. The results indicate that nonstationary operating condition can be moni- tored and diagnosed. Transient toothmeshing frequency and rotating speed are measured. Weak vibration signal of defective ball bearing is extracted from strong vibration of gearbox and diag- nosed successfully. This approach is effective for nonstationary condition monitoring and early di- agnosis of latent fault.展开更多
基金supported by grants from the National Natural Science Foundation of China (81430021 and 81370470)the Program for Liaoning Provincial Innovative Research Team in Universities (LT2015009)+1 种基金the Liaoning Provincial Science and Technology Project (2015225008)a Research Project of Dalian Science and Technology (2014E14SF175) of Liaoning Province, China
文摘Parkinson＇s disease （PD） is a complex neurode- generative disease with progressive loss of dopamine neurons. PD patients usually manifest a series of motor and non-motor symptoms. In order to provide better early diagnosis and subsequent disease-modifying therapies for PD patients, there is an urgent need to identify sensitive and specific biomarkers. Biomarkers can be divided into four categories： clinical, imaging, biochemical, and genetic. Ideal biomarkers not only improve our under- standing of PD pathogenesis and progression, but also provide benefits for early risk evaluation and clinical diagnosis of PD. Although many efforts have been made and several biomarkers have been extensively investigated, few if any have been found useful for early diagnosis. Here, we summarize recent developments in the discovered biomarkers of PD and discuss their merits and limitations for the early diagnosis of PD.
基金Natural Science Foundation of Jiangsu Province (No.SBK20082815)Aeronautical Science Foundation of China (No.20075152014)
文摘In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncertainty are assumed to be unknown but bounded.The radial basis function (RBF) neural network is used to approximate the sensor fault.Based on the output of the RBF neural network,the sliding mode observer is presented.Using the Lyapunov method,a criterion for stability is given in terms of matrix inequality.Finally,an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.
基金supported by National Natural Science Foundation of China(Nos.11405158 and 11435011)Development Foundation of China Academy of Engineering Physics(Nos.2014B0102011 and 2014B0102012)
文摘A new time-resolved shifted dual transmission grating spectrometer （SDTGS） is designed and fabricated in this work. This SDTGS uses a new shifted dual transmission grating （SDTG） as its dispersive component, which has two sub transmission gratings with different line densities, of 2000 lines/mm and 5000 lines/mm. The axes of the two sub transmission gratings in SDTG are horizontally and vertically shifted a certain distance to measure a broad range of 0.1-5 keV time-resolved X-ray spectra. The SDTG has been calibrated with a soft X-ray beam of the synchrotron radiation facility and its diffraction efficiency is also measured. The designed SDTGS can take full use of the space on a record panel and improve the precision for measuring spatial and temporal spectrum simultaneously. It will be a promising application for accurate diagnosis of the soft X-ray spectrum in inertial confinement fusion.
文摘A new approach is advanced based on wavelet transform in tandem with autoregressive technique. Wavelets and wavelet packets decompose dynamic signal into different bands and pro- vide multiresolution or multiscale view of signal. Autoregressive technique possesses effective function for short data processing. The approach is abopted to analyse nonstationary vibration sig- nals of mining excavator. The results indicate that nonstationary operating condition can be moni- tored and diagnosed. Transient toothmeshing frequency and rotating speed are measured. Weak vibration signal of defective ball bearing is extracted from strong vibration of gearbox and diag- nosed successfully. This approach is effective for nonstationary condition monitoring and early di- agnosis of latent fault.
