肉桂特色资源加工利用产业发展现状

肉桂是我国特色经济林树种，我国肉桂种植面积和年产量均居世界首位。我国肉桂主要分布在两广地区，其中广西为14.9万hm²，广东为8.9万hm²，两地面积占全国肉桂分布总面积的95%以上。肉桂既是著名的香料又是传统的名贵中药，具有极高的经济价值，发展肉桂产业对于促进农民增收、维护健康中国有着重要的意义。本研究综述了肉桂资源量、分布情况及主要利用部位，介绍肉桂主要产品（如桂皮，桂枝，肉桂粉及肉桂油）及加工技术现状、产品质量控制及其分析检测方法，分析了产业未来的发展趋势，并提出了产业发展的对策和措施：加强肉桂标准化示范基地建设，提高优质资源供给能力；提高肉桂加工利用技术水平，延长产业链；培育肉桂龙头企业，提高产品市场竞争力。为我国肉桂特色资源加工利用产业的可持续发展提供一定的思路。     

基于深度网络迁移学习的致痫区脑电识别* .txt

摘要：致痫区脑电识别能够为癫痫外科手术提供重要的参考价值。提出了一种基于深度网络迁移学习的致痫区脑电识别算法。首先利用连续小波变换（CWT）对脑电信号进行时频分析，获得脑电信号时频图；然后迁移学习AlexNet网络模型，调整网络结构使之适应于致痫区脑电识别，将模型第7层全连接层输出作为脑电信号时频图的特征表示，最后利用支持向量机（SVM）、BP神经网络、长短期记忆网络（LSTM）、基于稀疏表达分类算法（SRC）、线性判别分析（LDA）等分类算法进行特征分类。基于开源脑电数据集采用十折交叉验证的方法对算法进行了验证,比较6种分类器的效果，得到SVM算法的平均特异性为8881%，灵敏度为8807%，准确率为8844%，证明了该方法识别致痫区脑电信号的有效性。 .txt     

基于人工神经网络的柴油机失火故障诊断

车载诊断系统在诊断失火故障时,采用基于曲轴段角加速度和阈值规则相结合的方法,该方法在内燃机高速轻载运行时诊断单缸完全失火工况存在一定的局限性。通过对比分析失火和正常工况下曲轴瞬时转速的幅频和相频特征,提取不同谐次的幅值和相位信息,结合人工神经网络作为故障模式识别工具,得到了一种改善方法。通过台架实验,对此改善方法进行了单缸完全失火、两缸完全失火和单缸一定程度失火的故障诊断测试。结果表明,在实验条件下该方法可以有效识别不同的失火模式,并可在单缸失火模式下实现失火程度判别。同时,该方法通过少量工况数据训练神经网络,即可实现一定转速范围内的失火诊断,可行性强,可用于发动机失火故障在线诊断。     

波浪荷载作用下海上新型潜式浮式风力机运动特性研究

以适用于中等水深(50~200 m)的新型潜式浮式风力机为研究对象,该风力机基础综合Spar式、半潜式及张力腿(TLP)3类浮式风力机基础的优点,运行时基础主体淹没在水下,具有较小的水线面(如同Spar平台),受波浪影响较小;平台通过张紧式系泊线与海床相连(如同TLP平台),具有良好的垂荡和摇摆运动特性;拖航状态下,浮式平台处于半潜状态,水线面面积大(如同半潜式平台),具有良好的浮稳性。通过分析不同波况下的潜式浮式风力机耦合动力响应得到潜式浮式基础的横荡、纵荡、垂荡及纵摇运动响应,以及发电功率、叶片根部弯矩、塔筒顶部和底部弯矩、锚链张力时程曲线。研究结果表明:波浪对于结构的纵摇运动的影响最为明显,对发电功率、叶片根部弯矩和塔筒顶部弯矩影响较小,对塔筒底部弯矩和系泊线张力影响较大。     

Notch radius effect on fracture toughness of ceramics pertinent to grain size

Unlike fracture toughness, the notch fracture toughness of a ceramic is not a constant; rather, it increases with the notch-root radius ρ in a notched specimen. In this study, by analyzing the fracture measurements of eight different notched ceramics with an average grain size G of 3–40 μm, a simple model describing the relation between the notch fracture toughness and fracture toughness is proposed as a function of the relative notch-root radius ρ/G. The normal distribution is incorporated to consider the inevitable scatter in measurements where fracture mechanisms and errors are present. The results demonstrate that the model can effectively predict the quasi-brittle fracture variation trend for ceramics, including the upper and lower bounds, with 96% reliability, from a normal distribution; thus, it can address virtually all of the experimental data. We also determined that the notch fracture toughness approximates the fracture toughness if ρ ≤ G.     

Allocation and sizing of battery energy storage system for primary frequency control based on bio-inspired methods: A case study

This paper presents a new procedure for optimal allocation and optimal sizing of a battery energy storage system (BESS) for primary frequency support in an isolated power system. For the BESS allocation, a transmission bus system with larger frequency decline is recognized and the BESS sizing is performed by a constrained optimization strategy based on a new modified metaheuristic, called Developed Harris Hawks Optimization (DHHO). The simulation results of the suggested DHHO are compared with Bat Optimization Algorithm (BOA) and Genetic Algorithm (GA) from the literature to show the method efficiency. The final results showed higher precision with lower required iterations for the suggested DHHO method. Also, the proposed DHHO gives lower investment costs for BESS with lower power and energy requirement toward the other compared methods.     

Zone model predictive control for pressure management of water distribution network

In the water distribution network (WDN), although the water demand of the node is changing constantly, the water quantity and water pressure of the node need to be met at each moment. To realize energy saving and consumption reduction, it is proposed to control the nodal water head of WDN in an appropriate narrow range. The frequent large fluctuation of the water demand, which may lead the water pressure exceed the expected range, increases the difficulty of the zone control. To realize optimized WND control, a novel zone predictive control is proposed, where two switching cases are considered. The switching condition is whether there are feasible solutions to keep the pressure within the expected region over the prediction horizon. When the condition is satisfied, the controller minimizes the variation of inputs with constraints of pressure range for ensuring the tank level staying within the expected zone and obtaining optimal economic cost. When the current pressure is out of the expected region or the condition is not satisfied due to the large variation of water demand, a reference trajectory of outputs is introduced, which is combined with the inputs as an optimization variable, and the constraints of expected zone are moved from the output to the introduced reference trajectory. Through minimizing the distance between reference trajectory and output, the controller will keep the tank level from deviating too far from the expected zone and will drive the tank level rapidly into the expected zone once the tank level exceeds the expected range. An application of the proposed zone MPC to WDN in Shinan District of Shanghai is given to illustrate its effectiveness.     

基于稳定连接的配电网边缘划分方法及应用研究

随着能源互联网的建设,为了应对配电主站所面临的数据接入和计算压力,文章提出了二级配电网边缘架构,以分布式边缘智能架构缓解主站压力。主要从边缘定义、划分方法、边缘功能描述与交互描述4个方面对所提边缘架构进行介绍。提出电网稳定连接区域概念及其生成方法,并结合南京地区电网实例,说明了以电网稳定连接区域作为边缘划分的合理性。最后,对所提边缘架构在配电网中的实际应用场景进行了设计和展望。     

Power flow calculation for a distribution system with multi-port PETs: an improved AC-DC decoupling iterative method

Recently, power electronic transformers (PETs) have received widespread attention owing to their flexible networking, diverse operating modes, and abundant control objects. In this study, we established a steady-state model of PETs and applied it to the power flow calculation of AC–DC hybrid systems with PETs, considering the topology, power balance, loss, and control characteristics of multi-port PETs. To address new problems caused by the introduction of the PET port and control equations to the power flow calculation, this study proposes an iterative method of AC–DC mixed power flow decoupling based on step optimization, which can achieve AC–DC decoupling and effectively improve convergence. The results show that the proposed algorithm improves the iterative method and overcomes the overcorrection and initial value sensitivity problems of conventional iterative algorithms.