In experiments searching for rare signals,background events from the detector itself are some of the major factors limiting search sensitivity.Screening for ultra-low radioactive detector materials is becoming ever mo...In experiments searching for rare signals,background events from the detector itself are some of the major factors limiting search sensitivity.Screening for ultra-low radioactive detector materials is becoming ever more essential.We propose to develop a gaseous time projection chamber(TPC)with a Micromegas readout for radio screening.The TPC records three-dimensional trajectories of charged particles emitted from a flat sample placed in the active volume of the detector.The detector can distinguish the origin of an event and identify the particle types with information from trajectories,which significantly increases the screening sensitivity.For a particles from the sample surface,we observe that our proposed detector can reach a sensitivity higher than 100 l Bq m-2 within two days.展开更多
Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature ex...Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature extraction of wind turbine rolling bearings and to strengthen the feature information, a new structural element and an adaptive algorithm based on the peak energy are proposed,which are combined with spectral correlation analysis to form a fault diagnosis algorithm for wind turbine rolling bearings. The proposed method firstly addresses the problem of impulsive signal omissions that are prone to occur in the process of fault feature extraction of traditional structural elements and proposes a "W" structural element to capture more characteristic information. Then, the proposed method selects the scale of multi-scale mathematical morphology, aiming at the problem of multi-scale mathematical morphology scale selection and structural element expansion law. An adaptive algorithm based on peak energy is proposed to carry out morphological scale selection and structural element expansion by improving the computing efficiency and enhancing the feature extraction effect.Finally, the proposed method performs spectral correlation analysis in the frequency domain for an unknown signal of the extracted feature and identifies the fault based on the correlation coefficient. The method is verified by numerical examples using experimental rig bearing data and actual wind field acquisition data and compared with traditional triangular and flat structural elements. The experimental results show that the new structural elements can more effectively extract the pulses in the signal and reduce noise interference,and the fault-diagnosis algorithm can accurately identify the fault category and improve the reliability of the results.展开更多
基金the Ministry of Science and Technology of China(No.2016YFA0400302)the National Natural Sciences Foundation of China(Nos.11775142 and U1965201)the Chinese Academy of Sciences Center for Excellence in Particle Physics(CCEPP).
文摘In experiments searching for rare signals,background events from the detector itself are some of the major factors limiting search sensitivity.Screening for ultra-low radioactive detector materials is becoming ever more essential.We propose to develop a gaseous time projection chamber(TPC)with a Micromegas readout for radio screening.The TPC records three-dimensional trajectories of charged particles emitted from a flat sample placed in the active volume of the detector.The detector can distinguish the origin of an event and identify the particle types with information from trajectories,which significantly increases the screening sensitivity.For a particles from the sample surface,we observe that our proposed detector can reach a sensitivity higher than 100 l Bq m-2 within two days.
基金supported by National Natural Science Foundation of China (No. 61763037)Inner Mongolia Autonomous Region Natural Science Foundation of China(No. 2019LH06007)Science and Technology Plan Project of Inner Mongolia (No. 2019,2020GG028)。
文摘Working conditions of rolling bearings of wind turbine generators are complicated, and their vibration signals often show non-linear and non-stationary characteristics. In order to improve the efficiency of feature extraction of wind turbine rolling bearings and to strengthen the feature information, a new structural element and an adaptive algorithm based on the peak energy are proposed,which are combined with spectral correlation analysis to form a fault diagnosis algorithm for wind turbine rolling bearings. The proposed method firstly addresses the problem of impulsive signal omissions that are prone to occur in the process of fault feature extraction of traditional structural elements and proposes a "W" structural element to capture more characteristic information. Then, the proposed method selects the scale of multi-scale mathematical morphology, aiming at the problem of multi-scale mathematical morphology scale selection and structural element expansion law. An adaptive algorithm based on peak energy is proposed to carry out morphological scale selection and structural element expansion by improving the computing efficiency and enhancing the feature extraction effect.Finally, the proposed method performs spectral correlation analysis in the frequency domain for an unknown signal of the extracted feature and identifies the fault based on the correlation coefficient. The method is verified by numerical examples using experimental rig bearing data and actual wind field acquisition data and compared with traditional triangular and flat structural elements. The experimental results show that the new structural elements can more effectively extract the pulses in the signal and reduce noise interference,and the fault-diagnosis algorithm can accurately identify the fault category and improve the reliability of the results.