The Electron Cyclotron Resonance(ECR)ion source is a critical device for producing highly charged ion beams in various applications.Analyzing the charge-state distribution of the ion beams is essential,but the manual ...The Electron Cyclotron Resonance(ECR)ion source is a critical device for producing highly charged ion beams in various applications.Analyzing the charge-state distribution of the ion beams is essential,but the manual analysis is labor-intensive and prone to inaccuracies due to impurity ions.An automatic spectrum recognition system based on intelligent algorithms was proposed for rapid and accurate chargestate analysis of ECR ion sources.The system employs an adaptive window-length Savitzky-Golay(SG)filtering algorithm,an improved automatic multiscale peak detection(AMPD)algorithm,and a greedy matching algorithm based on the relative distance to accurately match different peaks in the spectra with the corresponding charge-state ion species.Additionally,a user-friendly operator interface was developed for ease of use.Extensive testing on the online ECR ion source platform demonstrates that the system achieves high accuracy,with an average root mean square error of less than 0.1 A for identifying charge-state spectra of ECR ion sources.Moreover,the system minimizes the stand-ard deviation of the first-order derivative of the smoothed signal to 81.1846 A.These results indicate the capability of the designed system to identify ion beam spectra with mass numbers less than Xe,including Xe itself.The proposed automatic spectrum recognition system represents a significant advancement in ECR ion source analysis,offering a rapid and accurate approach for charge-state analysis while enhancing supply efficiency.The exceptional performance and successful imple-mentation of the proposed system on multiple ECR ion source platforms at IMPCAS highlight its potential for widespread adoption in ECR ion source research and applications.展开更多
In this paper a real-time peak detection method based on modified Automatic Multiscale Field Detection (AMPD) algorithm and Field Programmable Gate Arrays (FPGA) technologies of a time series data is studied, and opti...In this paper a real-time peak detection method based on modified Automatic Multiscale Field Detection (AMPD) algorithm and Field Programmable Gate Arrays (FPGA) technologies of a time series data is studied, and optimum scaling is highlighted after testing several scales. To validate the results obtained from modified algorithm, they are compared with the results of original AMPD method. As data of this study, three-phase voltage values of a power station are used. A detail detective sensitivity analysis of phase-to-phase voltage values is tried at different scales. Moreover, the original algorithm is tested regarding the off-line mode to obtain optimum scaling for real-time peak point detection. It is concluded that the peak detection of minimum and maximum points of data series achieved by modified algorithm is very close to the results of original AMPD algorithm.展开更多
文摘The Electron Cyclotron Resonance(ECR)ion source is a critical device for producing highly charged ion beams in various applications.Analyzing the charge-state distribution of the ion beams is essential,but the manual analysis is labor-intensive and prone to inaccuracies due to impurity ions.An automatic spectrum recognition system based on intelligent algorithms was proposed for rapid and accurate chargestate analysis of ECR ion sources.The system employs an adaptive window-length Savitzky-Golay(SG)filtering algorithm,an improved automatic multiscale peak detection(AMPD)algorithm,and a greedy matching algorithm based on the relative distance to accurately match different peaks in the spectra with the corresponding charge-state ion species.Additionally,a user-friendly operator interface was developed for ease of use.Extensive testing on the online ECR ion source platform demonstrates that the system achieves high accuracy,with an average root mean square error of less than 0.1 A for identifying charge-state spectra of ECR ion sources.Moreover,the system minimizes the stand-ard deviation of the first-order derivative of the smoothed signal to 81.1846 A.These results indicate the capability of the designed system to identify ion beam spectra with mass numbers less than Xe,including Xe itself.The proposed automatic spectrum recognition system represents a significant advancement in ECR ion source analysis,offering a rapid and accurate approach for charge-state analysis while enhancing supply efficiency.The exceptional performance and successful imple-mentation of the proposed system on multiple ECR ion source platforms at IMPCAS highlight its potential for widespread adoption in ECR ion source research and applications.
文摘In this paper a real-time peak detection method based on modified Automatic Multiscale Field Detection (AMPD) algorithm and Field Programmable Gate Arrays (FPGA) technologies of a time series data is studied, and optimum scaling is highlighted after testing several scales. To validate the results obtained from modified algorithm, they are compared with the results of original AMPD method. As data of this study, three-phase voltage values of a power station are used. A detail detective sensitivity analysis of phase-to-phase voltage values is tried at different scales. Moreover, the original algorithm is tested regarding the off-line mode to obtain optimum scaling for real-time peak point detection. It is concluded that the peak detection of minimum and maximum points of data series achieved by modified algorithm is very close to the results of original AMPD algorithm.
