An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency...An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.展开更多
【目的】为及时发现海上风电机组发电机轴承的故障,提出一种基于蜣螂优化(Dung Beetle Optimizer,DBO)算法和极端梯度提升树(eXtreme Gradient Boosting,XGBoost)模型的DBO-XGBoost发电机轴承温度预测模型,并结合指数加权移动平均值(Exp...【目的】为及时发现海上风电机组发电机轴承的故障,提出一种基于蜣螂优化(Dung Beetle Optimizer,DBO)算法和极端梯度提升树(eXtreme Gradient Boosting,XGBoost)模型的DBO-XGBoost发电机轴承温度预测模型,并结合指数加权移动平均值(Exponentially Weighted Moving Average,EWMA)控制图实现发电机轴承的故障预测。【方法】首先,通过最大互信息系数(Maximal Information Coefficient,MIC)选取数据采集与监视控制(Supervisory Control And Data Acquisition,SCADA)系统中能准确表征发电机轴承状态的关键特征,并将其输入DBO-XGBoost模型中,对正常工况下的发电机轴承温度进行预测。其次,使用马氏距离(Mahalanobis Distance,MD)衡量真实值与预测值之间的偏差,并将MD序列输入基于EWMA控制图的变点检测算法中,以获取故障出现的变点,从而实现故障预测。最后,基于特征的重要性构建轴承故障模式知识图谱。【结果】结果表明,所提方法能对正常工况下发电机轴承的温度实现较为精准的预测,并能提前3天对故障进行预警,与通过设定单一阈值进行故障预警的方法相比,所提方法能更准确地检测到故障发生的时间。构建的轴承故障模式知识图谱为运维人员提供了可视化的运维决策支持。展开更多
A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To pr...A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution, and digital charge comparison, was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33-MeV γ-rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.展开更多
基金Project supported by the National Key R&D Program of China (Grant No. 2022YFF0607504)。
文摘An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.
文摘【目的】为及时发现海上风电机组发电机轴承的故障,提出一种基于蜣螂优化(Dung Beetle Optimizer,DBO)算法和极端梯度提升树(eXtreme Gradient Boosting,XGBoost)模型的DBO-XGBoost发电机轴承温度预测模型,并结合指数加权移动平均值(Exponentially Weighted Moving Average,EWMA)控制图实现发电机轴承的故障预测。【方法】首先,通过最大互信息系数(Maximal Information Coefficient,MIC)选取数据采集与监视控制(Supervisory Control And Data Acquisition,SCADA)系统中能准确表征发电机轴承状态的关键特征,并将其输入DBO-XGBoost模型中,对正常工况下的发电机轴承温度进行预测。其次,使用马氏距离(Mahalanobis Distance,MD)衡量真实值与预测值之间的偏差,并将MD序列输入基于EWMA控制图的变点检测算法中,以获取故障出现的变点,从而实现故障预测。最后,基于特征的重要性构建轴承故障模式知识图谱。【结果】结果表明,所提方法能对正常工况下发电机轴承的温度实现较为精准的预测,并能提前3天对故障进行预警,与通过设定单一阈值进行故障预警的方法相比,所提方法能更准确地检测到故障发生的时间。构建的轴承故障模式知识图谱为运维人员提供了可视化的运维决策支持。
基金supported by the Open Research Project of CAS Large Research InfrastructuresCAS Key Technology Talent ProgramNational Natural Science Foundations of China (Nos.U2031206 and 12273086)
文摘A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution, and digital charge comparison, was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33-MeV γ-rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.
