Low Input and High Output Impedances Current-Mode First-Order Allpass Filter Employing Grounded Passive Components

A current-mode low input and high output impedances first-order allpass filter using two multiple output second-generation current conveyors (MOCCIIs), one grounded capacitor and one grounded resistor is presented. The suggested filter uses a canonical number of passive components without requiring any component matching condition. The frequency responses simulation results of the proposed filter confirm the theoretical analysis.

Image Inpainting Detection Based on High-Pass Filter Attention Network

Image inpainting based on deep learning has been greatly improved.The original purpose of image inpainting was to repair some broken photos, suchas inpainting artifacts. However, it may also be used for malicious operations,such as destroying evidence. Therefore, detection and localization of imageinpainting operations are essential. Recent research shows that high-pass filteringfull convolutional network (HPFCN) is applied to image inpainting detection andachieves good results. However, those methods did not consider the spatial location and channel information of the feature map. To solve these shortcomings, weintroduce the squeezed excitation blocks (SE) and propose a high-pass filter attention full convolutional network (HPACN). In feature extraction, we apply concurrent spatial and channel attention (scSE) to enhance feature extraction and obtainmore information. Channel attention (cSE) is introduced in upsampling toenhance detection and localization. The experimental results show that the proposed method can achieve improvement on ImageNet.

基于数字控制延时的LCL型并网逆变器强鲁棒性加权平均电流控制策略

加权平均电流(WAC)控制因其对LCL型并网逆变器固有的降阶特性而备受关注,通过对逆变器控制系统的环路增益进行零极点对消,达到将三阶系统降为一阶系统的目的。但是,传统WAC控制未充分考虑数字控制延时对系统造成的影响,数字控制延时的存在导致系统无法进行理想降阶,并网逆变器对弱电网的鲁棒性较差。鉴于此,提出了一种基于数字控制延时的LCL型并网逆变器强鲁棒性WAC控制策略,在耦合点电压前馈通道引入一阶高通滤波器,进而对系统反向谐振峰进行完全补偿,以提高并网逆变器对弱电网的适应性。最后,通过仿真分析验证了所提控制策略的有效性。

采用参数辨识及新型主动阻尼控制的LCL滤波脉宽调制整流器

采用LCL滤波器的脉宽调制整流器一般需要检测电网电压、电流及直流母线电压,为抑制谐振还需检测交流滤波电容支路电压或电流。过多的传感器增加了整流器成本,且检测所得电网电压实际易受电网内感抗干扰,影响整流器稳定运行。首先提出一种基于电网参数辨识的虚拟磁链定向控制方法。在整流器启动之前,采用遗传算法辨识电网感抗、频率、幅值和初始相位角等参数,以获得虚拟磁链及其初值的精确观测。为抑制LCL滤波器谐振,提出一种通过一阶高通滤波器回馈整流器侧电流高频分量的新型有源阻尼控制方法,建立频域模型,分析高通滤波器参数对谐振抑制效果的影响。所提控制策略只需检测直流母线电压及整流器侧两相电流,省去了电网电压传感器及交流滤波电容支路电压或电流传感器。仿真和实验分析证实了该控制策略有效性。

一阶高通滤波在发电机低频时转子位置检测角中的应用

本文将一阶高通滤波和基于磁链函数的无位置传感器控制技术相结合,利用一阶高通滤波器的数学算法同步修正转子位置角和磁势幅值,能实现在低频情况下准确测量转子位置。设计一阶高通滤波观测器,抑制实际测量采样中存在直流偏移和随机分量的干扰,提高转子位置角的测量精度。即使在发电机静止情况下,也可以实现发电机任意转子位置角的实际值与通过控制系统测量得到的转子位置角相一致,并通过了仿真试验验证,验证了该方法的有效性。

Adaptive Noise Cancellation Method Used for Wheel Speed Signal of Integrate ABS/ASR System

A novel adaptive noise cancellation method for wheel speed signal of the anti-lock braking system/ anti-slip regulation（ABS/ASR） control system is proposed. Based on the spectrum distribution of vehicle＇s wheel speed signal got from fast Fourier transform under various conditions, the high-pass filter is used to deal with original wheel speed signals sampled to get reference noise signal and the original wheel speed signals are used as adaptive filter＇s desired outputs. The difference between original signals and reference noise signals is used as the error signal for the adaptive FIR filter and also used as the whole adaptive noise cancellation system＇s final output. This method can obtain the noise signal on-line and is easy to use for. real control system, which is useful to improve the performance of integrate system ABS/ASR.

Novel approach to GPS/SINS integration for IMU alignment

Strapdown inertial navigation system（SINS） requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit（IMU） motion is available based on the measurement obtained from global position system（GPS）.But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.

STRASS Dehazing:Spatio-Temporal Retinex-Inspired Dehazing by an Averaging of Stochastic Samples

In this paper,we propose a neoteric and high-efficiency single image dehazing algorithm via contrast enhancement which is called STRASS(Spatio-Temporal Retinex-Inspired by an Averaging of Stochastic Samples)dehazing,it is realized by constructing an efficient high-pass filter to process haze images and taking the influence of human vision system into account in image dehazing principles.The novel high-pass filter works by getting each pixel using RSR and computes the average of the samples.Then the low-pass filter resulting from the minimum envelope in STRESS framework has been replaced by the average of the samples.The final dehazed image is yielded after iterations of the high-pass filter.STRASS can be run directly without any machine learning.Extensive experimental results on datasets prove that STRASS surpass the state-of-the-arts.Image dehazing can be applied in the field of printing and packaging,our method is of great significance for image pre-processing before printing.

Finite-difference time-domain studies of low-frequency stop band in superconductor-dielectric superlattice

The transmission coefficients of electromagnetic （EM） waves due to a superconductor-dielectric superlattice are numerically calculated. Shift operator finite difference time domain （SO-FDTD） method is used in the analysis. By using the SO-FDTD method, the transmission spectrum is obtained and its characteristics are investigated for different thicknesses of superconductor layers and dielectric layers, from which a stop band starting from zero frequency can be apparently observed. The relation between this low-frequency stop band and relative temperature, and also the London penetration depth at a superconductor temperature of zero degree are discussed, separately. The low-frequency stop band properties of superconductor-dielectric superlattice thus are well disclosed.

A thermally crosslinked ion-gel gated artificial synapse

We demonstrate a synaptic transistor that uses a thermally crosslinked three-dimensional network to accommodate ionic liquid to form an ion gel layer. The synaptic transistor successfully emulated important synaptic plasticity, such as paired-pulse facilitation, spike-number dependent plasticity, spike-voltage dependent plasticity, and spike-rate dependent plasticity;these responses imply successful use of the ion gel. Moreover, the device realized “OR” and “AND” logic operations, and high-pass filtering behavior. Energy consumption of the device can be reduced to sub-femtojoule level, which is below that of biological synapses. Compared with traditional physical cross-linking using block copolymers, this method provides a facile strategy to prepare ion gels with tunable properties by altering the polymers and crosslinkers,and to enormously reduce the price by replacing expensive block copolymers or eliminating additional synthesis processes. This report provides a versatile strategy for design of synaptic transistors and their applications in neuromorphic electronics.

A cost driven predictive maintenance policy for structural airframe maintenance

Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） method.By using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.