Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator labora...Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator laboratories has revealed that SRF faults are the leading cause of short machine downtime trips.When a cavity fault occurs,system experts analyze the time-series data recorded by low-level RF systems and identify the fault type.However,this requires expertise and intuition,posing a major challenge for control-room operators.Here,we propose an expert feature-based machine learning model for automating SRF cavity fault recognition.The main challenge in converting the"expert reasoning"process for SRF faults into a"model inference"process lies in feature extraction,which is attributed to the associated multidimensional and complex time-series waveforms.Existing autoregression-based feature-extraction methods require the signal to be stable and autocorrelated,resulting in difficulty in capturing the abrupt features that exist in several SRF failure patterns.To address these issues,we introduce expertise into the classification model through reasonable feature engineering.We demonstrate the feasibility of this method using the SRF cavity of the China accelerator facility for superheavy elements(CAFE2).Although specific faults in SRF cavities may vary across different accelerators,similarities exist in the RF signals.Therefore,this study provides valuable guidance for fault analysis of the entire SRF community.展开更多
The accurate measurement of parameters such as the cavity-loaded quality factor(Q_(L))and half bandwidth(f_(0.5))is essential for monitoring the performance of superconducting radio-frequency cavities.However,the conv...The accurate measurement of parameters such as the cavity-loaded quality factor(Q_(L))and half bandwidth(f_(0.5))is essential for monitoring the performance of superconducting radio-frequency cavities.However,the conventional"field decay method"employed to calibrate these values requires the cavity to satisfy a"zero-input"condition.This can be challenging when the source impedance is mismatched and produce nonzero forward signals(V_(f))that significantly affect the measurement accuracy.To address this limitation,we developed a modified version of the"field decay method"based on the cavity differential equation.The proposed approach enables the precise calibration of f_(0.5) even under mismatch conditions.We tested the proposed approach on the SRF cavities of the Chinese Accelerator-Driven System Front-End Demo Superconducting Linac and compared the results with those obtained from a network analyzer.The two sets of results were consistent,indicating the usefulness of the proposed approach.展开更多
Precise measurements of the cavity forward(Vf)and reflected signals(Vr)are essential for characterizing other key parameters such as the cavity detuning and forward power.In practice,it is challenging to measure V_(f)...Precise measurements of the cavity forward(Vf)and reflected signals(Vr)are essential for characterizing other key parameters such as the cavity detuning and forward power.In practice,it is challenging to measure V_(f) and V_(r) precisely because of cross talk between the forward and reflected channels(e.g.,coupling between the cavity reflected and forward signals in a directional coupler with limited directivity).For DESY,a method based on the cavity differential equation was proposed to precisely calibrate the actual V_(f) and V_(r).In this study,we verified the validity and practicability of this approach for the Chinese ADS front-end demo superconducting linac(CAFe)facility at the Institute of Modern Physics and a compact energy recovery linac(cERL)test machine at KEK.At the CAFe facility,we successfully calibrated the actual V_(f) signal using this method.The result demonstrated that the directivity of directional couplers might seriously affect the accuracy of V_(f) measurement.At the cERL facility,we calibrated the Lorentz force detuning(LFD)using the actual Vf.Our study confirmed that the precise calibration of V_(f) significantly improves the accuracy of the cavity LFD measurement.展开更多
In this paper, we present the design and optimization of a side-coupled accelerating structure with an energy switch. The beam parameters are optimized, and the electric field asymmetry in the first cell is analyzed. ...In this paper, we present the design and optimization of a side-coupled accelerating structure with an energy switch. The beam parameters are optimized, and the electric field asymmetry in the first cell is analyzed. The new structure we designed has an improvement of 10 times in the accelerating field symmetry. Thermo-mechanical analysis is performed based on the electromagnetic results. The highest temperature is 72.5 ℃ at the nose cone, and the maximal deformation is 73 μm at the outer edge of the coupling cavity.展开更多
In the Chinese ADS front-end demo superconducting radiofrequency linac(CAFe)at the Institute of Modern Physics,a burst-noise signal-triggered cavity fault frequently appears during beam commissioning.These events are ...In the Chinese ADS front-end demo superconducting radiofrequency linac(CAFe)at the Institute of Modern Physics,a burst-noise signal-triggered cavity fault frequently appears during beam commissioning.These events are characterized by a rapid burst noise in the cavity pick-up,which may lead to an unexpected low-level radiofrequency(LLRF)response that eventually causes a cavity fault.To eliminate the undesirable reaction of the LLRF control loop,we propose a method that uses a burstnoise detection and processing algorithm integrated into the LLRF feedback controller.This algorithm can prevent undesired regulations in LLRF systems.Data analysis revealed that some burst-noise events did not exhibit measurable energy loss.In contrast,the other events were accompanied by a rapid loss of cavity stored energy and exhibited similarities to the‘‘E-quench’’phenomena reported in other laboratories.A particle-in-cell simulation indicated that the suspected E-quench phenomenon may be related to a plasma formation process inside the cavity.Fortunately,the LLRF algorithm is robust to the two different types of burst-noise events and can significantly mitigate the corresponding cavity faults in CAFe beam commissioning.展开更多
基金supported by the studies of intelligent LLRF control algorithms for superconducting RF cavities(No.E129851YR0)the National Natural Science Foundation of China(No.U22A20261)Applications of Artificial Intelligence in the Stability Study of Superconducting Linear Accelerators(No.E429851YR0)。
文摘Superconducting radio-frequency(SRF)cavities are the core components of SRF linear accelerators,making their stable operation considerably important.However,the operational experience from different accelerator laboratories has revealed that SRF faults are the leading cause of short machine downtime trips.When a cavity fault occurs,system experts analyze the time-series data recorded by low-level RF systems and identify the fault type.However,this requires expertise and intuition,posing a major challenge for control-room operators.Here,we propose an expert feature-based machine learning model for automating SRF cavity fault recognition.The main challenge in converting the"expert reasoning"process for SRF faults into a"model inference"process lies in feature extraction,which is attributed to the associated multidimensional and complex time-series waveforms.Existing autoregression-based feature-extraction methods require the signal to be stable and autocorrelated,resulting in difficulty in capturing the abrupt features that exist in several SRF failure patterns.To address these issues,we introduce expertise into the classification model through reasonable feature engineering.We demonstrate the feasibility of this method using the SRF cavity of the China accelerator facility for superheavy elements(CAFE2).Although specific faults in SRF cavities may vary across different accelerators,similarities exist in the RF signals.Therefore,this study provides valuable guidance for fault analysis of the entire SRF community.
基金supported by the project of Large Research Infrastructures"China initiative Accelerator-Driven System"(No.2017-000052-75-01-000590)"Studies of intelligent LLRF control algorithms for superconducting RF cavities"(No.E129851YR0)the National Natural Science Foundation of China(No.12205344).
文摘The accurate measurement of parameters such as the cavity-loaded quality factor(Q_(L))and half bandwidth(f_(0.5))is essential for monitoring the performance of superconducting radio-frequency cavities.However,the conventional"field decay method"employed to calibrate these values requires the cavity to satisfy a"zero-input"condition.This can be challenging when the source impedance is mismatched and produce nonzero forward signals(V_(f))that significantly affect the measurement accuracy.To address this limitation,we developed a modified version of the"field decay method"based on the cavity differential equation.The proposed approach enables the precise calibration of f_(0.5) even under mismatch conditions.We tested the proposed approach on the SRF cavities of the Chinese Accelerator-Driven System Front-End Demo Superconducting Linac and compared the results with those obtained from a network analyzer.The two sets of results were consistent,indicating the usefulness of the proposed approach.
基金supported by the project of “studies of intelligent LLRF control algorithms for superconducting RF cavities(No.E129851YR0)”。
文摘Precise measurements of the cavity forward(Vf)and reflected signals(Vr)are essential for characterizing other key parameters such as the cavity detuning and forward power.In practice,it is challenging to measure V_(f) and V_(r) precisely because of cross talk between the forward and reflected channels(e.g.,coupling between the cavity reflected and forward signals in a directional coupler with limited directivity).For DESY,a method based on the cavity differential equation was proposed to precisely calibrate the actual V_(f) and V_(r).In this study,we verified the validity and practicability of this approach for the Chinese ADS front-end demo superconducting linac(CAFe)facility at the Institute of Modern Physics and a compact energy recovery linac(cERL)test machine at KEK.At the CAFe facility,we successfully calibrated the actual V_(f) signal using this method.The result demonstrated that the directivity of directional couplers might seriously affect the accuracy of V_(f) measurement.At the cERL facility,we calibrated the Lorentz force detuning(LFD)using the actual Vf.Our study confirmed that the precise calibration of V_(f) significantly improves the accuracy of the cavity LFD measurement.
文摘In this paper, we present the design and optimization of a side-coupled accelerating structure with an energy switch. The beam parameters are optimized, and the electric field asymmetry in the first cell is analyzed. The new structure we designed has an improvement of 10 times in the accelerating field symmetry. Thermo-mechanical analysis is performed based on the electromagnetic results. The highest temperature is 72.5 ℃ at the nose cone, and the maximal deformation is 73 μm at the outer edge of the coupling cavity.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB34010000)Large Research Infrastructures China initiative Accelerator Driven System(2017-000052-75-01-000590)+1 种基金National Natural Science Foundation of China(No.12175283)Studies of intelligent LLRF control algorithms for SC RF cavities(No.E129851YR0).
文摘In the Chinese ADS front-end demo superconducting radiofrequency linac(CAFe)at the Institute of Modern Physics,a burst-noise signal-triggered cavity fault frequently appears during beam commissioning.These events are characterized by a rapid burst noise in the cavity pick-up,which may lead to an unexpected low-level radiofrequency(LLRF)response that eventually causes a cavity fault.To eliminate the undesirable reaction of the LLRF control loop,we propose a method that uses a burstnoise detection and processing algorithm integrated into the LLRF feedback controller.This algorithm can prevent undesired regulations in LLRF systems.Data analysis revealed that some burst-noise events did not exhibit measurable energy loss.In contrast,the other events were accompanied by a rapid loss of cavity stored energy and exhibited similarities to the‘‘E-quench’’phenomena reported in other laboratories.A particle-in-cell simulation indicated that the suspected E-quench phenomenon may be related to a plasma formation process inside the cavity.Fortunately,the LLRF algorithm is robust to the two different types of burst-noise events and can significantly mitigate the corresponding cavity faults in CAFe beam commissioning.
