Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

The Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind conditions.To suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray images.In this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(RS)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is maximized.Two assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus RSis nea rly equal to the radius of the magneto pause curvature.We create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson noise.We then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea ks.From the filte red images,we calculate RS and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground truth.Our method estimates RS with an accuracy of<0.3 RE when the solar wind density exceeds>10 cm-3.The accuracy improves for greater solar wind densities and during southward interplanetary magnetic fields.The method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field turnings.Consequently,the technique will enable quantitative analysis of the magnetopause motion and help reveal the dayside reconnection modes for dynamic solar wind conditions.This technique will suppo rt the LEXI and SMILE missions in achieving their scientific o bjectives.

A Passive Low-Pass Filter on Low-Loss Substrate

The loss mechanisms of different passive devices （on-chip inductors and capacitors） on different substrates are analyzed and compared. OPS （oxidized porous silicon） and HR （high-resistivity） substrates are used as low-loss substrates for on-chip planar LPF （low pass filter） fabrication. For the study of substrate loss, a planar coil inductor is also designed. Simulation results show that Q （the quality factor） of the inductor on both substrates is over 20. Measurements of the LPF on OPS substrate give a - 3dB bandwidth of 2.9GHz and a midband insertion loss of 0.87dB at 500MHz. The LPF on HR substrate gives a - 3dB bandwidth of 2.3GHz and a midband insertion loss of 0.42dB at 500MHz.

Design of a compact low-pass filter with wide stopband

This paper presents a novel low-pass filter （LPF） with sharp rejection, wide stopband and compact size, which are realized by the defected ground structure （DGS） and the defected microstrip structure （DMS）. The equivalent circuit model is proposed and the circuit parameters are extracted by the circuit simulation software. The parameters measured are 3 dB cutoff frequency fc of 5.2 GHz, the insertion loss less than 0.5 dB from DC to 4.0 GHz and S21 less than -20 dB within the wide stopband from 6 GHz to 16 GHz. The results of the circuit optimization agree well with those of the full wave simulation and the measured ones, which validate the effectiveness of the equivalent circuit model. The size of the proposed LPF is decreased compared with normal LPF. This LPF can be applied in rectennas to eliminate high order harmonics.

Design of low-pass filter based on a novel defected ground structure

A novel defected ground structure （DGS） for the microstrip line is proposed in this paper. The DGS lattice has more defect parameters so that it can provide better performance than the conventional dumbbell-shaped DGS. Selectivity is improved by 97.2% with a sharpness factor of 24.6%. The method is applied to the design of a low-pass filter to confirm validity of the proposed DGS.

Microstrip Low-Pass Elliptic Filter Design Based on Implicit Space Mapping Optimization

It is a time-consuming and often iterative procedure to determine design parameters based on fine, accurate but expensive, models. To decrease the number of fine model evaluations, space mapping techniques may be employed. In this approach, it is assumed both fine model and coarse, fast but inaccurate, one are available. First, the coarse model is optimized to obtain design parameters satisfying design objectives. Next, auxiliary parameters are calibrated to match coarse and fine models’ responses. Then, the improved coarse model is re-optimized to obtain new design parameters. The design procedure is stopped when a satisfactory solution is reached. In this paper, an implicit space mapping method is used to design a microstrip low-pass elliptic filter. Simulation results show that only two fine model evaluations are sufficient to get satisfactory results.

Compact Metamaterial Microstrip Low-Pass Filter

Complimentary hexagonal-omega structures are used to design compact, low insertion loss (IL), low pass filter with sharp cut-off. It has been designed for improvement of roll-off performance based on both μ and ε negative property of the complimentary hex-omega structure while maintaining the filter pass-band performance. By properly designing and loading the hexagonal-omega structure in the ground of microstrip line not only improve the roll-off of the low pass filter, but also reduced the filter size. The simulated results indicate that the proposed filter achieves a flat pass band with no ripples as well as selectivity of 19.68 dB/GHz, corresponding to 5-unit cells hex-omega structures. This significantly exceeds the 5.6 dB/GHz selectivity of the conventional low pass filter design, due to sub-lambda dimensions of the hex-omega structure. A prototype filter implementing area is: 0.712λg x 0.263λg, λg being the guided wavelength at 3-dB cut-off frequency (fc). The proposed filter has a size smaller by 36.2%.

Comparative Study of Low-Pass Filter and Phase-Locked Loop Type Speed Filters for Sensorless Control of AC Drives

High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase-locked loop(PLL)type filters with respect to ramp speed reference tracking and steady-state performances,as well as the achievement of adaptive cutoff frequency control.An improved LPF-based filter structure with no ramping and steady-state errors caused by filter parameter quantization effects is proposed,which is suitable for applying LPF for sensorless drives of AC machines,especially when fixed-point digital signal processor is selected e.g.in mass production.Furthermore,the potential of adopting PLL for speed filtering is explored.It is demonstrated that PLL type filters can well maintain the advantages offered by the improved LPF.Moreover,it is found that the PLL type filters exhibit almost linear relationship between the cutoff frequency of the PLL filter and its proportional-integral(PI)gains,which can ease the realization of speed filters with adaptive cutoff frequency for improving the speed transient performance.The proposed filters are verified experimentally.The PLL type filter with adaptive cutoff frequency can provide satisfactory performances under various operating conditions and is therefore recommended.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

基于sigmoid滤波器的永磁轮毂电机自抗扰控制

相比燃油拖拉机,电动拖拉机具有节能高效、绿色清洁的优点。分布式驱动电动拖拉机结构简单、控制维度多,能进一步提高电动拖拉机的工作效率和作业精度。但是电机检测转速噪声导致轮毂电机速度波动严重,复杂路面及多种作业工况下进一步加剧了上述问题,严重降低了拖拉机的作业质量。针对上述问题,该研究提出一种基于sigmoid滤波器的线性自抗扰控制(linear active disturbance rejection control,LADRC)以提高轮毂电机的转速稳定性和抗扰动能力。该控制策略在传统LADRC的基础上引入sigmoid滤波器至扩张状态观测器(extended state observer,ESO),根据输入噪声信号误差变化改变滤波器带宽,以抑制观测误差中的中高频干扰信号,同时避免滤波器积分环节对轮毂电机速度跟踪快速性的影响,具有较快的收敛性。搭建试验平台对所提出控制策略进行试验验证,结果表明:与传统LADRC策略相比,本文所提控制策略在变速和变载工况下的转速脉动分别减小了32%和41.67%,iq电流脉动分别减小了6.25%和4.17%,可在快速、准确跟踪给定转速的同时,大幅提高轮毂电机驱动系统的噪声抑制性能,为复杂环境下电动拖拉机高精度作业提供技术参考。

低电容CHB型混合动力中压电机调速系统

针对氢燃料电池大功率电机驱动系统,提出一种以燃料电池为主动力源的轻量化级联H桥(cascadedH-bridge,CHB)型混合动力中压电机调速系统。所提系统由燃料电池/蓄电池/超级电容的混合动力源供电,基于四有源桥(quad activebridge,QAB)与CHB子模块互联的两级变换器(cascaded H-bridges with quad active bridge,CHB-QAB)作为调速变换器。CHB-QAB通过四绕组高频变压器将各子模块进行内部互联,采用单边同步双边移相调制的策略,使得所有子模块呈现开关电容特性,在不依赖复杂控制的前提下,减小子模块电容的容值,提升系统的功率密度。针对三类动力源,采用基于低通滤波(lowpassfilter,LPF)的能量管理策略,保证电机实际运行过程中的有效功率分配,解决燃料电池对电机动态响应缓慢和燃料饥饿现象等问题。最后通过仿真与实验对所提轻量化电机调速系统进行验证。

基于手机内置MEMS传感器的行人步数检测方法

手机内置微机电系统(MEMS)传感器具有零偏不稳定性和误差发散快等缺点。为了提高行人步数检测的准确性,基于图形用户界面(GUI),建立零偏校正、低通滤波和卡尔曼(Kalman)滤波3种误差处理模型。采用峰值域和时间域共同约束峰值的双特征检测方法,设计平稳前进和摆臂前进两种动态实验场景,检测行人步数。实验结果表明:在不同动态场景下,双特征检测行人步数的准确率均在95%以上,验证了所提算法的准确性和鲁棒性,满足行人步数检测的要求。

基于虚拟阻抗VPI谐振控制器的MMC环流抑制策略

针对MMC相间环流包含的二倍频以及偶次高倍频问题,该文提出了基于虚拟阻抗VPI谐振控制器的新型环流抑制策略,该策略通过虚拟阻抗与VPI谐振控制器结合,从而有效抑制环流中二倍频及偶次高倍频。首先建立了模块化多电平换流器(modular multilevel converter,MMC)的数学模型,分析了内部环流;其次将环流二倍频分量利用陷波器精准提取之后采用VPI谐振控制器进行抑制;最后设计了虚拟阻抗,抑制环流中的高频谐波分量。利用Matlab/Simulink搭建三相MMC仿真模型并进行验证。

基于暂态响应时间分析与暂稳态模式识别的锁相环参数自适应方法

锁相环的设计对保障交流网络中设备安全运行有着重要意义,锁相环实现方法与参数设计对锁相环的响应时间、抗扰能力等控制特性起到重要影响。本文通过结合小信号频域模型与大信号状态空间模型,分析同步坐标系锁相环的暂稳态响应特性,得出各参数设计对于锁相环控制特性的影响;在理论分析基础上,提出了基于响应时间与暂稳态模式识别的锁相环参数自适应框架。仿真与实验结果验证了所提出的参数自适应方法可以通过实现参数动态调节,达到对锁相环暂态快速响应与稳态抗扰的设计要求。

双同步坐标系解耦滤波器复变量建模与分析

针对解耦双同步坐标系锁相环(DDSRF-PLL)传统实变量模型阶数较高、序分量响应不易观察、滤波性能评估困难等问题,提出了一种基于复变量的DDSRF-PLL建模方法。首先,建立了其复变量模型,分析了序分量响应特性,该复变量模型表明正序基波输出模型对负序基波分量实现负无穷大的衰减,同时可得到其他频率序分量的衰减增益;然后,基于提出的复变量模型,设计了二阶低通滤波器以显著增强解耦网络的滤波性能,并进一步分析了高阶低通滤波器的可行性与必要性。研究表明采用二阶低通滤波器即可满足大部分场景下的谐波抑制要求,且具有计算量小、模型阶数低、易于数字实现的优点。实验结果验证了所提复变量模型的正确性与有效性。

基于高速ADC的数字双混频时差测量系统

使用双混频时差法进行时间和频率测量时,模拟部分引入的噪声会干扰信号过零点的判断,降低测量精度,而使用数字信号处理技术后不再需要判断过零点,量化噪声成为系统内的主要噪声来源,可以通过数字滤波器对其进行抑制。同时有利于设计结构紧凑的系统,更易于小型化,测量速度也可以进行灵活配置。通过引入高速模数转换器、数控振荡器、低通抽取滤波器、数字鉴相器等,设计了数字双混频时差测量系统,并研制了4通道的原理样机。测试结果表明,当频率源为10 MHz的信号时,原理样机中属于同片ADC(analog-to-digital converter)的两个通道间的本底噪声约为5×10^(-14)@1 s,属于不同片ADC的两个通道间的本底噪声约为8×10^(-14)@1 s,满足原子振荡器的测量要求。并以主动型氢钟VCH-1003M为参考,使用原理样机分别对Microchip的5071A铯原子钟和SRS的FS725铷原子钟的稳定度进行测量,测量结果与Microchip的相噪分析仪53100A和5120A无显著差异。

基于残差生成器的Buck双向变换器改进模型预测控制

在以光伏储能装置为主体的直流微网中,外部扰动容易引起直流母线电压波动,导致系统输出电能质量下降。为提升系统动态响应性能,针对直流微网中常用的Buck型双向DC-DC变换器,提出一种基于残差生成器的改进电流补偿模型预测控制策略。首先,对模型预测控制(MPC)环节进行线性等效,证明采用校正前PI+MPC控制时,系统在0 rad/s时存在失稳风险。然后,由此设计负低-高通滤波器校正环节,并从调节系数变化和模型参数不确定性等角度进行分析,验证改进后系统的稳定性和动态性能得到明显改善。仿真与实验结果表明,基于残差生成器的电流补偿能有效平抑外界扰动引起的母线电压波动,负低-高通校正环节在改善系统性能的同时又进一步抑制电感电流噪声,进而平滑母线电压曲线。最终,证明提出的改进策略可显著提升直流微网的动态响应性能。

基于CEEMD的露天深孔爆破振动信号降噪光滑模型

由于爆破区域地形地质条件的复杂、监测仪器的误差、振动传播介质的反射以及磁场的干扰等原因,采集的原始爆破振动信号常常会掺杂大量的噪声,针对此问题提出了基于互补集合经验模态分解(CEEMD)的信号降噪光滑模型。此模型将爆破振动信号进行CEEMD,基于分解所得到的IMF分量建立低通滤波算法。根据滤波算法的相似度与光滑度,构造目标函数并计算最优解,其对应的滤波算法模型即为爆破振动信号的最优降噪光滑模型。通过构造仿真信号验证了降噪光滑模型算法的可行性,并将模型应用了实际露天深孔爆破振动信号的研究。采用信噪比和均方根误差两种指标对比经验模态分解(EMD)方法、小波阈值法、CEEMD-小波阈值法与滤波算法模型BP3的降噪效果,验证了降噪光滑模型在对露天矿山爆破振动信号降噪方面的有效性,并通过频谱分析进一步验证了降噪光滑模型较CEEMD-小波阈值法的优越性。结果表明:基于CEEMD的露天深孔爆破振动信号降噪光滑模型具有良好的降噪能力,能够在保留原始爆破振动信号真实特征信息的前提下对信号进行降噪,且降噪效果优于EMD方法、小波阈值法和CEEMD-小波阈值法。

基于低通滤波器的柔性关节空间机器人时延估计跟踪控制

为解决位姿不受控情况下柔性关节空间机器人系统预抓取阶段的关节跟踪控制和振动问题,采用拉格朗日方程并结合动量守恒原理进而建立漂浮基三杆柔性关节空间机器人系统动力学方程。为提高柔性关节的等效刚度,引入关节柔性补偿的方法;即根据奇异摄动理论,将柔性关节空间机器人系统分解为慢变系统和快变系统。在此基础上,针对慢变系统设计以时延估计为主框架的滑模控制方法,同时与低通滤波器相结合消除滑模控制带来的系统抖振问题;针对快变系统设计线性速度差值反馈控制系统,抑制柔性关节给系统带来的柔性振动问题。通过仿真验证空间机械臂能够在有限时间内快速、稳定地跟踪上期望轨迹,证实该控制方案具有较好的鲁棒性和可靠性。

基于末端触觉传感器的智能机器人压力补偿

末端触觉是智能机器人实现对外部环境做出直接反应的必需媒介。触觉传感器的弹性层易导致表面接触压力测量结果出现偏差,降低机械手的抓取力度的合理性。提出智能机器人末端触觉传感器压力误差补偿方法。建立触觉传感器三维力学模型,分析表面接触应力与弹性层之间的关系,得到传感器压力特征;计算弹性层的低通效应值,通过传感器测量值推理得到表面压力值,利用线性迭代反卷积算法对压力误差补偿。实验结果表明,研究方法应用下,压力误差补偿的均方误差接近于10-3,精度与理想效果更接近,上述方法获取的传感器对不同大小作用力的电学响应结果与实际数据具有较高一致性。

基于DGS的切比雪夫低通滤波器设计

为了抑制微波传输系统中的高次谐波以及杂散信号,采用DGS(缺陷地结构)来设计低通滤波器。通过在经典的五阶切比雪夫低通滤波器的接地面上蚀刻多个哑铃型DGS结构,获得了较好的通带和阻带性能。仿真及测试结果显示,采用DGS结构设计的低通滤波器,其通带截止频率为1.4 GHz,0~1.4 GHz通带内回波损耗值优于-20 dB且插入损耗值小于0.5 dB,阻带范围为2~10 GHz。经实物加工测试分析表明,实测结果与仿真结果吻合较好。设计的DGS结构低通滤波器在无线通信系统中具有一定的应用前景。