Measurement of locked mode (LM) is important for the physical research of Magnetohydrodynamic (MHD) instabilities and plasma disruption. The n = 0 pick-up need to be extracted and subtracted to calculate the amplitude and phase of the LM. A new method to extract this pick-up has been developed by predicting the n = 0 pick-up brn=0 by the LM detectors based on Neural Networks (NNs) in J-TEXT. An approach called Power Multiple Time Scale (PMTS) has been developed with outstanding regressing effect in multiple frequency ranges. Three models have been progressed based on PMTS NNs. PMTS could fit the brn=0 on the LM detectors with little errors both in time domain and frequency domain. The n>0 pick-up brn>0 generated by resonant magnetic perturbations (RMPs) can be obtained after subtracting the extracted brn=0. This new method uses only one LM instead of 4 LM detectors to extract brn=0. Therefore, the distribution of the LM detectors can also be optimized based on this new method.

通过神经网络（NNs）预测锁定模式（LM）探测器上的 n = 0 信号，提出了一种新的方法来提取并计算 LM 的幅值和相位，进而将 n = 0 信号减去，以获取由共振磁扰动（RMPs）产生的 n > 0 信号。此方法使用一种 LM 检测器而不是四种 LM 检测器提取 n = 0 信号，并可根据此方法优化检测器的分布。

基于神经网络的J-TEXT锁定模式探测器挑选出n=0抽出