The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor d...The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.展开更多
基金supported by the National Natural Science Foundation of China(Nos.11975060,12005026,and 12075038)the Major Science and Technology Project in Sichuan Province(No.19ZDZD0137)the Sichuan Science and Technology Program(No.2020YFG0019).
文摘The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.