基于PBFT区块链技术的电网企业仓储系统

提出了一种基于实用拜占庭容错(PBFT)算法的区块链技术,首先对传统的实用拜占庭容错算法原理进行了阐述,该传统算法包含前期、需求、预准备、准备、确认、答复6个阶段,但传统算法具有实时性差、缺乏惩罚机制、带宽高的缺点。针对出现的这些问题,又对传统算法进行了改进,具体涉及记账节点、共识过程以及视图切换过程。通过测试进一步证明了该改进算法的实用性,并将该算法应用于电网企业中,构建的虚拟仓库实现了联储联备,降低了库存资金的耗费,并且提高了电网企业库存管理的效率。     

Data-driven diagnosis of the high-pressure hydrogen leakage in fuel cell vehicles based on relevance vector machine

The hydrogen pressure inside tanks and its adjacent pipes can reach up to 70 MPa in fuel cell vehicles. This is the weak links of hydrogen leakage. The diagnosis time of mainstream hydrogen leakage diagnosis method based on hydrogen concentration sensors (HCSs) is easily affected by the number and location of installed sensors. In this study, a data-driven diagnosis method is proposed for the high-pressure hydrogen leakage. Fisher discrimination analysis and linear least squares fitting are used for data preprocessing, relevance vector machine is used for pattern recognition. When the total volume of tanks is 82 L and the hydrogen leakage flow rate is larger than 2 g/s, the diagnosis accuracy of the proposed method is higher than 95% and the diagnosis time is constant. When the leakage location is far away from HCSs, the proposed method can the diagnose hydrogen leakage in a shorter time than mainstream method.     

FPGA互连测试中的反馈桥接故障覆盖问题

现场可编程门阵列(FPGA)内部资源众多,其中互连资源出现故障的概率远远高于片内其他资源,而在以往许多互连测试研究中,所生成的测试配置存在无法覆盖反馈桥接故障的难题,所以较难有测试配置实现故障列表的100%覆盖。因此通过约束桥接故障只发生在单个查找表(LUT)内的信号线上,并结合单项函数,对反馈桥接故障模型进行优化改进,从根本上解决难题；然后对优化后的反馈桥接故障设置相应的约束条件,再使用布尔可满足性理论(SAT)生成满足约束条件的测试配置。采用优化后的故障模型对ISCAS"89基准电路进行了测试配置生成实验,结果表明生成的测试向量解决了反馈桥接故障的覆盖难题,并且在实现故障列表的100%覆盖下,优化后的故障模型所需要的测试配置数最少。     

Study on the influence of segmented fuel cell by grooving method and its application in oxygen starvation diagnosis

The oxygen starvation in fuel cells is an important reason for the deterioration of durability. The segmented fuel cell is a method to study the gas distribution inside the fuel cell. In order to study the influence of the grooving method on segmented fuel cell and its application in oxygen starvation diagnosis, a five-serpentine-channel three-dimensional two-phase simulation model is established by FLUENT. Through steady-state simulation, the effect of grooving method on fuel cell performance is studied. The overall performance (polarization curve) of the fuel cell drops slightly, but the current density distribution on the anode graphite plate changes greatly due to the grooves. The “current concentration” phenomenon is proposed based on the current density distribution. Through dynamic simulation, the oxygen starvation under current load mode and voltage load mode is simulated, and the “starvation coefficient” is defined as an oxygen starvation diagnostic index. In the current load mode, the “starvation coefficient” never exceed 15%, because when the oxygen starvation is severe, the simulation cannot converge or even cannot maintain, which corresponds to the voltage reversal in reality. However, in the voltage load mode, the “starvation coefficient” can reach up to 100%. The conclusions have important guiding significance for the judgment of the internal reaction uniformity of the segmented fuel cell by grooving method and provide a theoretical basis for judging whether a fuel cell is out of oxygen by segmented fuel cell.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

新媒体环境下智慧化阅读推广研究——以重庆第二师范学院为例

开展智慧化阅读推广,紧跟时代步伐,有效提升读者多重阅读体验和满意度,增强智慧化阅读推广的价值,促进智慧化阅读推广服务的有效化、规范化、科学化、常态化、长期化发展,已成为当前阅读推广研究中一个重要的切入点。文章基于智慧化阅读研究,结合"新媒体"高新技术环境,提出智慧化阅读推广的内容分析、具体实施、环境构建、推广评估与效果、推广改进等几个方面组成的以读者为中心的核心服务体系。本文分析了智慧化阅读基本方面,以我校图书馆实际运用推广效果,智慧化阅读存在的优、劣势及相应的对策。     

液相色谱-串联质谱技术在临床检验中的应用研究进展

液相色谱-串联质谱（LC-MS/MS）技术具有高灵敏度、高特异性、高分辨率和高效率的优点。近年来随着仪器灵敏度的提高，LC-MS/MS在常规临床检验中显示出极大的潜力，并在疾病早期预防和诊断中发挥着不可替代的作用。本文对LC-MS/MS在新生儿疾病筛查、维生素D检测、内分泌激素检测、肽类和蛋白质定量分析等临床检验方面的研究进展进行综述，并讨论了未来面临的挑战。     

用于电弧检测的电力专用SoC设计

针对传统的电弧电路故障检测结果不准确的问题,设计用于电弧检测的SoC系统,并且在55nm工艺下进行流片验证。采用包含两种结构的模数转换器的片上电压源,设计了锁相环以及复位电路,精度最高可达8.67 bit。验证结果表明,本设计可提高电弧检测的准确性。     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。