Abrasive waterjet micro-machining of channels in metals: Comparison between machining in air and submerged in water

Abrasive water jet technology can be used for micro-milling using recently developed miniaturized nozzles. Abrasive water jet (AWJ) machining is often used with both the nozzle tip and workpiece submerged in water to reduce noise and contain debris. This paper compares the performance of submerged and unsubmerged abrasive water jet micro-milling of channels in 316L stainless steel and 6061-T6 aluminum at various nozzle angles and standoff distances. The effect of submergence on the diameter and effective footprint of AWJ erosion footprints was measured and compared. It was found that the centerline erosion rate decreased with channel depth due to the spreading of the jet as the effective standoff distance increased, and because of the growing effect of stagnation as the channel became deeper. The erosive jet spread over a larger effective footprint in air than in water, since particles on the jet periphery were slowed much more quickly in water due to increased drag. As a result, the width of a channel machined in air was wider than that in water. Moreover, it was observed that the instantaneous erosion rate decreased with channel depth, and that this decrease was a function only of the channel cross-sectional geometry, being independent of the type of metal, the jet angle, the standoff distance, and regardless of whether the jet was submerged or in air, in either the forward or backward directions. It is shown that submerged AWJM results in narrower features than those produced while machining in air, without a decrease in centerline etch rate.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

面向草莓抓取的气动四叶片软体抓手研制

农林业中果蔬的自动化采摘需求日趋强烈,末端抓手是实现无损采摘的关键。传统的末端抓手以刚性结构居多,现有的各种柔性抓手也存在抓取力不足、包覆性不佳等缺点。本文以草莓的无损采摘为研究对象,提出将草莓外部轮廓曲线作为设计曲线,设计了一种新型气动四叶片软体抓手。首先,对软体抓手的结构做仿真优化,提出一种安全地附着在目标物表面的设想。然后,在进行草莓表面的最小破坏应力试验的基础上,测试了软体抓手的末端力,验证了其实现无损抓取的可行性。再次,利用动态捕捉技术,研究了软体抓手叶面的弯曲变形规律。最后,选择使用弧线型气体通道的软体抓手进行了草莓抓取测试,结果证明了气动四叶片软体抓手可以实现草莓的无损抓取,抓取成功率达90%,破损率为2%,表明所研制的四叶片软体抓手用于草莓抓取时具有良好的稳定性和实用性,可用于草莓采摘的末端执行器。本研究也可为其他易损果蔬的采摘技术提供理论基础和技术支撑。     

不同粒径改性粉煤灰对磷酸根吸附性能的影响

废水排放过量的磷导致水体污染日益严重，将粉煤灰通过化学改性制备成了水化硅酸钙吸附剂，研究了改性吸附剂对磷酸根的吸附效果。利用XRD, SEM及BET比表面积等手段对粒度分级前后的吸附剂进行表征，研究不同粒级吸附剂对磷酸根的吸附性能，并考察其吸附机理。结果表明，不同粒级的吸附剂其化学成分出现了明显的偏析现象，孔隙结构也差异显著。相比其他粒径下的吸附剂颗粒，颗粒粒径在50?75 μm时，吸附剂中钙和硅含量较多，铝、铁和镁含量较低，水化硅酸钙组分含量最高，且伴有含铝的托贝莫来石晶体出现，钙离子的增加使其可以与更多的磷酸根结合形成沉淀。同时此粒径下具有较高的比表面积及孔隙度，疏松多孔的结构为钙离子提供更多活性位点。当使用粒径在50?75 μm的吸附剂吸附磷酸根时，磷的饱和吸附量可达到17.1 mg/g，比未分级的吸附剂高19.58%。     

悬浮于润滑油中的颗粒运动分析及其对油膜压力的影响

对含有固体颗粒的局部润滑流域建立格子Boltzmann(LBM)离散模型,分析固体颗粒在润滑油中的动力学特性;考虑颗粒形状的影响,推导计入单个固体颗粒运动的润滑方程,并分析得到油膜压力;将油膜流动特性与颗粒动力学计算相结合,分析不同形状的颗粒运动对于油膜压力的影响。分析发现,当颗粒进入润滑油后,经过很短的瞬时颗粒就会达到一个瞬态稳定的状态,无论颗粒在油膜厚度方向的初始位置位于两壁面之间的中线上侧还是下侧,颗粒都会向中线位置移动;当颗粒速度为0时对于油膜压力的影响较大,随着颗粒速度逐渐增大,颗粒对于油膜压力的影响逐渐减小;当颗粒的宽度在油膜厚度方向相同时,长宽比越大的颗粒对于油膜压力的影响也越大;当颗粒长轴相等时,颗粒在油膜厚度方向的宽度越大,则其对于油膜压力的影响也越大,即颗粒形状对于油膜流动的阻碍能力越强,则其对于油膜压力的影响越大。     

Study on the relationship between the particle size distribution and the effectiveness of the K‐powder fire extinguishing agent

The relationship between the particle size distribution and the extinguishing effectiveness of the new K‐powder fire extinguishing agent has been studied experimentally, to explore the reason of the great extinguishing efficiency exhibited by the new K‐powder fire extinguishing agent on Class B fire (liquid fuel fire). The results of the experiment showed that the extinguishing effectiveness increased along with the decrease of the particle size distribution. In addition, a sharp discontinuity appeared around the limiting size, about 40 μm. The powder with the particle size below 40 μm exhibited highly effective extinguishing with the minimum effective extinguishing concentration C_xr = 23 g·m^?3, while the powder with the particle size above 40 μm exhibited little fire extinguishing efficiency. Compared with other fire extinguishing agents produced by different substances, the new K‐powder fire extinguishing has the bigger limiting size. That means, in the same particle size distribution, the new K‐powder fire extinguishing agent contains more highly effective powder than others contain, and is more effective.     

MG410采煤机滚筒辅助叶片板的增设与应用

针对MG170/410-WD滚筒式采煤机在大倾角、仰角、“三软”煤层使用中遗漏在机道中的浮煤多、装煤效率低等问题,通过添加螺旋板数量对采煤机滚筒进行改造。改造后,在滚筒转速不变的情况下,提高抛煤效率,缩短了工作面割煤和工作面空顶时间,提高了装煤效率,从源头上降低了顶板管理的安全风险。     

基于SVM的煤与瓦斯突出预测模型及应用

为有效预测矿井内煤与瓦斯突出的危险程度,对其影响因素做了分析与探讨,分别构建了基于粒子群优化算法以及遗传算法支持向量机的煤与瓦斯突出预测模型,并且通过实例对两种模型预测的准确性进行了验证。分别利用单项以及综合指标、BP神经网络以及PSO-SVM模型、GA-SVM模型,对寺河煤矿二号井的突出区域进行预测比较。结果表明,PSO-SVM的预测模型不仅可以在小样本数据中预测出煤与瓦斯突出程度的大小,而且综合预测结果更加精确,其在解决矿井内煤与瓦斯突出的小样本数据中显示出更加强大、通用的性能。     

高落差粉尘扩散规律和分布特征

高溜井放矿过程中会形成强大的冲击气流引起粉尘扩散，造成严重的井下环境污染，对其进行有效治理一直是井下通风除尘的工作重心，本工作利用相似实验和数值模拟相结合的方式探究溜井放矿过程中粉尘的扩散规律和分布特征。通过改变放矿质量、矿石粒径、溜井密闭程度、含水率等因素测试不同条件下气流大小和粉尘浓度分布，并利用CFD-DPM耦合方法模拟卸矿过程中的气?固两相流，研究气流和粉尘浓度时空分布特征。结果表明，最大粉尘浓度和风速随放矿质量增加而上升，随颗粒粒径和溜井密闭程度增大而降低，且含水率越大，粉尘浓度越小，风速无明显变化，在放矿过程中矿石颗粒之间碰撞占主导作用，颗粒流呈横向分布。