基于协同优化算法的流速仪检定系统设计

提出了一种小型轻便的流速仪检定系统的设计方案,并运用改进的多学科协同优化方法求解各学科设计变量的最优解。首先介绍了算法思想及改进措施,并根据系统设计要求建立了各学科的设计变量、目标函数和约束条件；其次,运用遗传算法求解各学科设计变量的最优解,并根据优化结果完善了系统的设计方案,同时运用计算机仿真等方法验证了优化结果的可行性。结果表明,优化后的检定系统满足流体力学效应、匀速运动时间、系统重量等设计要求,同时证明了协同优化算法解决多学科设计优化问题的有效性。     

Exploiting Bayesian networks for fault isolation: A diagnostic case study of diesel fuel injection system

Fault isolation is known to be a challenging problem in machinery troubleshooting. It is not only because the isolation of multiple faults contains considerable number of uncertainties due to the strong correlation and coupling between different faults, but often massive prior knowledge is needed as well. This paper presents a Bayesian network-based approach for fault isolation in the presence of the uncertainties. Various faults and symptoms are parameterized using state variables, or the so-called nodes in Bayesian networks (BNs). Probabilistically causality between a fault and a symptom and its quantization are described respectively by a directed edge and conditional probability. To reduce the qualitative and quantitative knowledge needed, particular considerations are given to the simplification of Bayesian networks structures and conditional probability expressions using rough sets and noisy-OR/MAX model, respectively. By adopting the simplified approach, symptoms under multiple-fault are decoupled into the ones under every single fault, while the quantity of the conditional probabilities is simplified into the linear form of the faults quantity. Prior knowledge needed in Bayesian network-based diagnostic model is reduced significantly, which decreases the complexity in establishing and applying this diagnosis model. The computational efficiency is improved accordingly in the simplified BN model, after eliminating the redundant symptoms. The fault isolation methodology is illustrated through an example of diesel engine fuel injection system to verify the developed model.     

OPM3要素对项目组合管理能力影响的SD建模与仿真

根据组织项目管理成熟度模型（OPM3），确定影响项目组合管理能力的OPM3要素，分析OPM3要素与项目组合管理能力的因果关系，构建系统动力学模型，仿真模拟OPM3要素对项目组合管理能力的影响。仿真结果表明：OPM3要素与项目组合管理能力正相关；OPM3要素对项目组合管理能力的影响在短期内并不显著；在OPM3要素中，对项目组合管理能力影响较为显著的是战略执行与规划、组织领导能力和信息分析。     

Adaptive neural network command filtered backstepping control of pure‐feedback systems in presence of full state constraints

An adaptive neural network (NN) command filtered backstepping control is proposed for the pure‐feedback system subjected to time‐varying output/stated constraints. By introducing a one‐to‐one nonlinear mapping, the obstacle caused by full stated constraints is conquered. The adaptive control law is constructed by command filtered backstepping technology and radial basis function NNs, where only one learning parameter needs to be updated online. The stability analysis via nonlinear small‐gain theorem shows that all the signals in closed‐loop system are semiglobal uniformly ultimately bounded. The simulation examples demonstrate the effectiveness of the proposed control scheme.     

Motion control of underactuated linkage robot based on gymnastic skill

In this paper, a reproduction of a swing‐up and a giant swing motion of underactuated robots based on technique of the horizontal bar gymnast is discussed with focusing on an equivalent center of mass (ECM) of underactuated robots and the gymnast. At first, the behaviors of the ECM of the gymnast (ECMG) are analyzed by using a motion capturing technique and an efficient motion of the ECMG for the swing‐up and for the giant swing motion are identified from analysis results, respectively. Next, a partial linearization method, which can realize that the ECM of the Acrobot (ECMA) replicates this efficient motion, is designed and reproduces the underactuated robots the swing‐up and giant swing motion like the gymnast. Finally, an effectiveness of the proposed controller is shown by numerical simulations.     

Adaptive finite‐time formation tracking control for multiple nonholonomic UAV system with uncertainties and quantized input

An adaptive finite‐time formation tracking control approach is proposed for multiple unmanned aerial vehicle (UAV) system with quantized input signals in this paper. The UAVs are described by nonholonomic kinematic model and autopilot model with uncertainties. An enhanced hysteretic quantizer is introduced to avoid chattering, and some restrictions are released by using a new quantization decomposition method. Based on backstepping technique and finite‐time Lyapunov stability theory, the adaptive finite‐time controller is designed for the trajectory tracking of the multi‐UAV formation. The nonholonomic constraints are solved by a transverse function. A transformation is introduced to the control input signals to eliminate the quantization effect. Stability analysis proves that the tracking errors can converge to a small neighborhood of the origin within finite time and all the closed‐loop signals are semiglobally finite‐time bounded. The effectiveness of the proposed control approach is validated by simulation and experiment.     

基于改进雷达图的配电系统电能质量评估方法

本文针对配电系统电能质量综合评估存在的评估指标权重分配过于主观或客观的问题,提出一种基于改进雷达图法的配电系统电能质量评估方法。该方法利用最小偏差组合权重法计算各评估指标的最优组合权重。并在传统雷达图的基础上对各指标轴间夹角值的确定和特征向量的选取两方面做了进一步的改进。首先采用扇形区域取代原始的三角形区域,并利用最小偏差组合权重法计算各指标轴间夹角值。其次选择新的特征向量构造评估函数对配电系统电能质量进行综合评估。最后通过对某钢铁厂棒材变电站10kV配电系统电能质量进行综合评估,验证了该方法的可行性和合理性。较传统雷达图而言,改进雷达图法解决了传统雷达图法中各指标间信息共用以及评估结果不唯一的问题,使评估结果更加准确合理。     

数字花卉植物的全息可视化与交互实现

花卉植物形态、结构与生长过程的数字化和可视化是现代林业科研的重要研究内 容，数字花卉植物在科普、教育、展示等方面都有着广泛的应用与需求。全息影像技术是一种 新兴的前沿技术，其原理源自佩珀尔幻象，通常用于生成立体感强的影像，实现数字幻象与真 实世界的融合，拥有良好的观赏性，用户接受度较高。将全息影像技术与数字花卉植物相关研 究进行结合，可以加强数字花卉植物的可视化效果，从而实现更好的科普、教育、展示效果。 因此在现有的研究基础之上，考虑实现数字花卉植物的全息可视化，并在可视基础上增加了用 户交互实现，设计出一套兼具展示性和交互性的流程，力求总结出一种具有完整可行性的方案， 从而对数字花卉植物的新型表现形式进行深入研究，以期对数字植物研究与应用的进一步发展 提供参考。     

Challenges and new methods for designing reliability experiments

Abstract

Engineers use reliability experiments to determine the factors that drive product reliability, build robust products, and predict reliability under use conditions. This article uses recent testing of a howitzer to illustrate the challenges in designing reliability experiments for complex, repairable systems. We review research in complex system reliability models, failure-time experiments, and experimental design principles. We highlight the need for reliability experiments that account for various intended uses and environments. We leverage lessons learned from current research and propose methods for designing an experiment for a complex, repairable system.     

Advanced Friction–Wear Behavior of Organic Brake Pads Using a Newly Developed System

The objective of this study was to investigate the influence of an advanced performance system on the tribological behavior of brake pad material using a specially designed brake pad tester system following standard SAE J-661. The tribological behavior and friction and wear characteristics of the organic brake pad samples were evaluated. During braking tests, the samples, in contact with a cast iron disk, were studied at different disc speeds, temperatures, and braking cycles under a constant pressure. In order to understand the friction and wear behavior, the unworn surfaces, worn surfaces, and wear debris were characterized by means of scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). Furthermore, the surface characteristics and differences in the wear modes of the brake pad samples were examined. Wear debris was permitted to deform the brake pad surfaces, leading to friction layers and enabling the estimation of the friction behavior of the brake pads. The results showed that the best friction–wear behavior was obtained with lower braking cycles at low speeds and temperature. Thus, the newly developed brake pad tester system proved very effective in evaluating the performance of the brake pad samples.