小型巨磁阻/隧穿磁电阻(GMR/TMR)磁传感器在弱磁信号的高分辨率测量中扮演重要角色。针对小型GMR/TMR磁传感器输出响应存在磁滞现象,影响探测精度的问题,提出了一种基于数字信号处理器(DSP)控制低噪声电流源进行磁滞补偿的方案:基于DSP...小型巨磁阻/隧穿磁电阻(GMR/TMR)磁传感器在弱磁信号的高分辨率测量中扮演重要角色。针对小型GMR/TMR磁传感器输出响应存在磁滞现象,影响探测精度的问题,提出了一种基于数字信号处理器(DSP)控制低噪声电流源进行磁滞补偿的方案:基于DSP平台控制高稳定电流源产生补偿电流,并通过磁补偿线圈产生补偿磁场,使得GMR/TMR敏感体处产生恒定磁场,实现对磁敏感体磁滞均方根误差抑制;通过低噪声电流源设计,降低电流补偿导致系统引入的额外噪声。实验结果表明:搭建的高精密电流源的均方根误差(RMSE)为(3~5)×10-6,通过对GMR/TMR磁传感器补偿,磁滞降低了90%,同时仅仅产生250 p T的噪声。展开更多
Hysteresis widely exists in civil structures,and dissipates the mechanical energy of systems.Research on the random vibration of hysteretic systems,however,is still insufficient,particularly when the excitation is non...Hysteresis widely exists in civil structures,and dissipates the mechanical energy of systems.Research on the random vibration of hysteretic systems,however,is still insufficient,particularly when the excitation is non-Gaussian.In this paper,the radial basis function(RBF)neural network(RBF-NN)method is adopted as a numerical method to investigate the random vibration of the Bouc-Wen hysteretic system under the Poisson white noise excitations.The solution to the reduced generalized Fokker-PlanckKolmogorov(GFPK)equation is expressed in terms of the RBF-NNs with the Gaussian activation functions,whose weights are determined by minimizing the loss function of the reduced GFPK equation residual and constraint associated with the normalization condition.A steel fiber reinforced ceramsite concrete(SFRCC)column loaded by the Poisson white noise is studied as an example to illustrate the solution process.The effects of several important parameters of both the system and the excitation on the stochastic response are evaluated,and the obtained results are compared with those obtained by the Monte Carlo simulations(MCSs).The numerical results show that the RBF-NN method can accurately predict the stationary response with a considerable high computational efficiency.展开更多
文摘小型巨磁阻/隧穿磁电阻(GMR/TMR)磁传感器在弱磁信号的高分辨率测量中扮演重要角色。针对小型GMR/TMR磁传感器输出响应存在磁滞现象,影响探测精度的问题,提出了一种基于数字信号处理器(DSP)控制低噪声电流源进行磁滞补偿的方案:基于DSP平台控制高稳定电流源产生补偿电流,并通过磁补偿线圈产生补偿磁场,使得GMR/TMR敏感体处产生恒定磁场,实现对磁敏感体磁滞均方根误差抑制;通过低噪声电流源设计,降低电流补偿导致系统引入的额外噪声。实验结果表明:搭建的高精密电流源的均方根误差(RMSE)为(3~5)×10-6,通过对GMR/TMR磁传感器补偿,磁滞降低了90%,同时仅仅产生250 p T的噪声。
基金the National Natural Science Foundation of China(No.12072118)the Natural Science Funds for Distinguished Young Scholar of Fujian Province of China(No.2021J06024)the Project for Youth Innovation Fund of Xiamen of China(No.3502Z20206005)。
文摘Hysteresis widely exists in civil structures,and dissipates the mechanical energy of systems.Research on the random vibration of hysteretic systems,however,is still insufficient,particularly when the excitation is non-Gaussian.In this paper,the radial basis function(RBF)neural network(RBF-NN)method is adopted as a numerical method to investigate the random vibration of the Bouc-Wen hysteretic system under the Poisson white noise excitations.The solution to the reduced generalized Fokker-PlanckKolmogorov(GFPK)equation is expressed in terms of the RBF-NNs with the Gaussian activation functions,whose weights are determined by minimizing the loss function of the reduced GFPK equation residual and constraint associated with the normalization condition.A steel fiber reinforced ceramsite concrete(SFRCC)column loaded by the Poisson white noise is studied as an example to illustrate the solution process.The effects of several important parameters of both the system and the excitation on the stochastic response are evaluated,and the obtained results are compared with those obtained by the Monte Carlo simulations(MCSs).The numerical results show that the RBF-NN method can accurately predict the stationary response with a considerable high computational efficiency.
