风电叶片部件疲劳试验机跟随控制策略研究

针对风电叶片部件疲劳试验过程中实际载荷与期望载荷跟随效果差的问题,提出一种超前自校正与改进线性自抗扰(LADRC)相结合的同步控制策略。该方法通过对实际载荷进行自校正补偿与系统误差以及外部扰动一起输入到改进线性自抗扰控制器,从而实现加载力和频率的有效控制。对疲劳试验机油电液伺服系统控制算法进行仿真分析,并通过搭建现场试验平台对同步控制策略进行有效性验证。仿真及试验结果表明：在较大载荷疲劳试验过程中,该控制策略显著提升系统的快速响应性和抗干扰能力,载荷误差控制在1%以内,相对于传统ADRC控制算法同步误差减小了56.14%,有效实现了风电叶片部件疲劳试验载荷的精确控制。     

改进的注意机制在滚动轴承故障诊断中的应用

针对滚动轴承振动信号易受到非平稳噪声的影响,提出一种改进注意力机制的多尺度内核网络(IA-MKNet),以从含噪振动信号中提取更敏感的特性信号。首先提出一种改进的多尺度卷积注意力机制(IAM),自适应提取有意义的故障特征并自动抑制噪声;然后针对振动信号固有的多时间特征,设计基于IAM的自适应多尺度核残差块来捕获振动信号的多时间尺度故障特征;最后提出一种基于自适应集成学习器的组合策略,通过融合多个IA-MKNets的输出来增加特征的多样性,从而进一步提高诊断的准确性和稳定性。实验结果表明：该方法提高了噪声环境下滚动轴承的故障诊断精度,性能优于其他5种基准方法。     

基于视觉的机械臂轨迹优化方法研究

针对应用视觉系统进行工件抓取时,工件相互遮挡导致识别工件不准确且抓取效率较低的问题,提出基于视觉的机械臂轨迹优化方法。由相机采集工件图像信息,通过标定机械臂坐标系、工件坐标系及相机坐标系,建立“手眼”坐标关系,基于点云数据对工件识别与定位;提出改进遗传-鲸鱼混合轨迹规划算法,以控制工件抓取过程。对机械臂的3个重要关节进行了运动仿真与实验测试。仿真结果显示：改进的遗传-鲸鱼混合算法收敛速度更快,搜索能力更强,优化后的抓取时间比基本遗传算法优化的抓取时间减少了2.3 s。实验结果表明：基于点云识别的机械臂抓取成功率达到93.75%,极大提高了抓取效率,验证了算法的有效性。     

基于改进粒子群算法的线缆路径规划方法研究

针对复杂机电产品布线路径规划过程中存在的效率较低、可应用性差等问题,提出一种改进粒子群算法,使用栅格法对布线空间进行划分,对障碍物建模并进行方向包围盒处理。为了避免算法在迭代过程中陷入局部最优,引入非线性逐渐递减的惯性权重与异步变化的学习因子,并且将贴壁约束加入到路径规划的过程中,保证线缆在敷设时路径的合理性。最后在仿真试验中,与标准粒子群算法进行对比,验证了改进后算法的合理性与可行性。     

Optimization of a plate-fin heat exchanger design through an improved multi-objective teaching-learning based optimization (MO-ITLBO) algorithm

Teaching-learning-based optimization (TLBO) is a recently developed heuristic algorithm based on the natural phenomenon of teaching-learning process. In the present work, multi-objective improved teaching-learning-based optimization (MO-ITLBO) algorithm is introduced and applied for the multi-objective optimization of plate-fin heat exchangers. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions maintained in an external archive. Minimizing total annual cost and the total weight of heat exchanger as well as minimization of total pressure drop and maximization of heat exchanger effectiveness for specific heat duty requirement are considered as objective functions. Two application examples are presented to demonstrate the effectiveness and accuracy of the proposed algorithm.     

Genetic algorithm to simultaneously optimise stope sequencing and equipment dispatching in underground short-term mine planning under time uncertainty

ABSTRACT

The main issue in short-term planning optimisation for underground mining is organising the mining process with limited resources in the form of equipment and materials to satisfy production targets and stable feed grade requirements. In this paper, an integrated optimisation model is proposed based on an individual generation algorithm and an improved Genetic Algorithm to simultaneously optimise stope extraction sequencing and timing, extracted ore grade and equipment dispatching. The model objectives are to shorten the time gap between the stope mining processes and the overall working time. When the uncertainty of equipment working time is taken into account in a short-term scheduling model, the Monte Carlo simulation is applied to evaluate the risk of not meeting the production target. A modification strategy is defined to evaluate equipment failure. Consequently, any available equipment is automatically reassigned to the mining site to replace the broken-down equipment. A case study is used to validate the model in the Sanshandao gold mine of China to formulate an optimal monthly schedule. Compared with the conventional approach, the new model could reduce the variance of ore tonnage and feed grade and improve the equipment allocation efficiency. Discussions are presented to address the uncertainty.     

Feature extraction of AC square wave SAW arc characteristics using improved Hilbert–Huang transformation and energy entropy

In order to extract the arc feature information related to welding quality in alternating current square wave submerged arc welding (AC Square Wave SAW), an improved Hilbert–Huang transform (HHT) is put forward to investigate the time–frequency distribution of arc current, and the energy entropy is employed to quantitatively judge the arc characteristics. The empirical mode decomposition (EMD) is used to decompose the collected current signal into a number of Intrinsic Mode Functions (IMFs). The method for removing the high frequency and undesirable low-frequency IMFs is proposed by using the correlation coefficient of the IMF and the original signal as criterion, and the valid IMFs are selected for the Hilbert transform and energy entropy calculation. The improved HHT combining with energy entropy can quantitatively describe the time–frequency energy distribution characteristics of the arc current signal at different duty cycle, frequency and welding speed. Experimental results are provided to confirm the effectiveness of this approach to extract the arc physical information related to welding quality.     

地下突水隐患识别与风险预测的改进D-S算法

针对地下矿突水因素的不确定性与时空的随机性,主要应用改进D-S算法开展地下矿突水隐患识别与风险预测,以期为地下矿突水隐患识别和水灾预测与防治等提供有效的理论依据。在考虑地质突水因素的同时,更加注重在生产管理中的人为因素。通过采用专家打分法获取各突水因素的基本概率赋值(BPA),基于改进D-S算法,构建识别框架Ω={突水、临界、不突水、不确定},建立以富水性系数、隔水层系数、水压系数、构造系数、矿压系数、勘探系数、开采系数、预防管理系数为证据体的突水融合决策模型。最后,通过国内某典型矿山进行实际应用,结果与实际情况基本一致,说明所建立的预测模型是可行的。     

Experimental study of improved two step synthesis for DME production

Dimethyl ether (DME) has received growing attention due to its potential use as a multi-purpose fuel. A new technical route of improved two step synthesis is proposed for DME production, which is composed of methanol synthesis and methanol dehydration in a fixed-bed reactor. The influences of the operating conditions including reaction pressure, temperature, H₂/CO mole ratio in the syngas and space velocity on CO conversion, selectivity and yield of DME are investigated. CO conversion and DME yield both increase monotonically with the pressure increase. The optimal reaction temperatures for the synthesis and dehydration of methanol are different. CO conversion increases at first and keeps constant when the H₂/CO mole ratio is above 2. DME yield increases obviously and then decreases gradually with the space velocity increase. The optimal conditions are obtained to maximize the CO conversion and DME selectivity. The reaction temperatures of the top and bottom stage are in the range of 270-280 °C and 235-245 °C, respectively. The optimal ratio of H₂/CO is above 2, and the space velocity is in the range of 1000-1300 h^− 1.     

基于改进模糊自适应补偿的柔性关节机器人PD控制

针对柔性关节机器人具有不确定性、轨迹跟踪精度低和抖动的问题,提出一种改进模糊自适应补偿的PD控制方法。该方法在原有模糊自适应控制和PD控制的基础上进行改进,采用改进模糊自适应控制对PD控制进行补偿,以提高存在不确定性条件下的关节轨迹跟踪精度并抑制抖动。通过Lyapunov理论证明了系统的稳定性。仿真结果表明：新型控制器具有良好的自适应能力,与传统PD控制和模糊自适应控制相比,新型控制策略显著提高了关节的轨迹跟踪精度并在一定程度上抑制了关节抖动。