Robot Interaction Force Estimation Using an Adaptive Sliding Mode Observer

In constrained motion control of a robot, the interaction force is an important variable, which directly describes the state of interaction. It is required in a number of algorithms for interaction control. Desirably, the interaction force has to be measured by force sensors. However, there are inherent limitations with force sensors, such as the cost, sensing noise, limited bandwidth, and the difficulty of physical location at the required place, which is dynamic. In the present paper, the interaction force is estimated by using high order sliding mode observers. An adaptive version of a high order sliding mode observer is developed to robustly reconstruct the interaction force. Experimental results are given to show the effectiveness of the developed algorithms.     

Application of Feature Extraction through Convolution Neural Networks and SVM Classifier for Robust Grading of Apples

This paper proposes a novel grading method of apples, in an automated grading device that uses convolutional neural networks to extract the size, color, texture, and roundness of an apple. The developed machine learning method uses the ability of learning representative features by means of a convolutional neural network (CNN), to determine suitable features of apples for the grading process. This information is fed into a one-to-one classifier that uses a support vector machine (SVM), instead of the softmax output layer of the CNN. In this manner, Yantai apples with similar shapes and low discrimination are graded using four different approaches. The fusion model using both CNN and SVM classifiers is much more accurate than the simple k-nearest neighbor (KNN), SVM, and CNN model when used separately for grading, and the learning ability and the generalization ability of the model is correspondingly increased by the combined method. Grading tests are carried out using the automated grading device that is developed in the present work. It is verified that the actual effect of apple grading using the combined CNN-SVM model is fast and accurate, which greatly reduces the manpower and labor costs of manual grading, and has important commercial prospects.     

新能源分比例渗透下基于博弈的多主体效益综合评估方法

“双碳”目标下新能源大规模发展,新能源的发展给各能源主体带来了影响,如何量化评估新能源渗透给能源主体带来的影响成为研究重点。首先,基于改进的K-means算法构建基于典型场景集的新能源出力模型;然后,从源-网-荷-储出发,构建火力发电商、电网、用户、储能运营商的决策优化模型;其次,构建考虑新能源渗透的多能源主体效益评估模型;最后,进行算例分析,算例结果验证了模型的有效性。     

混合市场环境下计及电转气的园区燃气机组调峰优化模型

清洁能源消纳是当前我国电力市场改革加速推进的一项重要目标。在此背景下,文章构建了混合市场环境下计及电转气(power-to-gas,P2G)的园区燃气机组调峰优化模型。首先,设计了风光机组、燃气机组、电转气和储气罐参与的园区电力系统运行结构;其次,计及绿证交易市场和调峰辅助服务市场机制,分别构建了园区发电机组绿证交易模型和调峰补偿模型;然后,以清洁能源消纳最大化、燃气调峰意愿最大化、CO₂排放最小化和系统净收益最大化为目标,构建了清洁能源驱动下含P2G设备的园区供电系统经济调度数学模型;最后,采用混沌粒子群算法对模型求解。结果表明,此模型兼顾了P2G设备以及调峰补偿机制的园区电力系统,清洁能源消纳率提升了6.69%,CO₂排放量减少了14.66 t;燃气机组积极参与了调峰,系统净收益最高提升了18.706万元,验证了所提模型的有效性,并体现了求解算法较好的收敛效果。     

嵌入CBAM结构的改进YOLOV3超宽带雷达生命信号检测算法

为了提高超宽带雷达生命信号检测准确率,提出了一种改进型YOLOV3检测算法。考虑到超宽带雷达探测的人体呼吸信号成像后宽高相差较大,采用多尺度训练时网络对宽高的敏感程度不一样,因此在设计损失函数时,对宽高损失给予不同的权重系数。为了提高网络通道以及空间特征表达能力,使得网络能够扩大对目标特征区域的感知范围,因此将通道注意力与空间注意力结构(CBAM)嵌入到YOLOV3基础网络Darknet53的每个shortcut层,得到CBAM-YOLOV3网络结构。对比改进前后的算法。实验结果表明,改进后的算法在IoU阈值为0.5时,mAP为98.09%,提升3.90%,在阈值为0.75时,mAP为76.49%,提升16.48%。     

纤维的结构和性能（Ⅲ）

本文介绍了ＰＥＴ高速纺丝纤维的热性能，低速纺丝领域中纤维的大分子取向以及纤维结晶相和非结晶相的取向，指出：纤维的沸水收缩率在纺速为２０００－３０００ｍ／ｍｉｎ内达最大值，其后随纺速增加急剧减少；纤维结晶相取向度随纺增加而增大；非晶向取向在６００ｍ／ｍｉｎ纺速以随纺速增加而增大，６０００ｍ／ｍｉｎ纺速以上随纺增加而减少。另外指出纺丝速度在７０００ｍ／ｍｉｎ以上时，ＰＥＴ纤维横断面上存在一个内部结构分     

Electrochemical and ellipsometric study of the oxide films formed on copper in borax solution: Part I: Effect of oxygen

The formation and reduction of passive layers on copper in weakly alkaline solutions saturated with N2 and O2 were studied. Voltammetric and ellipsometric techniques were employed to examine the structural characteristics of the layers formed in the –0.32 to 0.75 V vs RHE potential region. Optical measurements at open circuit potentials (Eoc) were also made to simulate operational conditions. The passive layer consists of a duplex structure: an outer hydrated copper oxide film and an inner dehydrated film. This inner layer is composed of Cu2O with a surface excess of Cu(ii) ions. The growth rate of the oxide layers at controlled potentials is higher in O2 saturated solution. The corrosion resistance of copper depends on the presence of O2 in the electrolyte, on the stirring rate and on the Eoc value.     

END-WINDING INFLUENCE ON HOMOPOLAR EFFECTS IN ASYMMETRICAL THREE-PHASE MACHINE WINDINGS

ABSTRACT

Asymmetries in three-phase windings of rotating-field a.c, machines may cause homopolar currents in delta-connected phase windings. End-winding particulars can have an Important quantitative influence on these currents and on the connected phase current inequalities.