基于特征迁移的面铣刀磨损监测方法

实时监测刀具磨损状态对保证工件加工质量和确定合理换刀时间至关重要.数据驱动的多源信号融合预测是解决刀具磨损预测难题的可行方案.本文中通过时域和频域分析提取了多维信号特征,并结合机器视觉方法处理刀具磨损图像获得的磨损特征,针对涂层面铣刀建立了随机森林磨损预测模型.对于同类型的刀具和工件材料,使用特征迁移方法解决多工况场景下新刀样本不足问题.试验结果表明,基于迁移特征建立的磨损预测模型对目标刀具的磨损量预测效果较迁移前显著提升,准确性评价指标R²决定系数从0.37提升到0.96.基于特征迁移的磨损预测模型为数据驱动模型在刀具磨损预测和实时监测领域的应用提供参考依据.     

基于克里格重构的区域地磁变化场短时预测模型

区域地磁变化场建模与预测是地磁辅助导航、空间环境监测与预报等领域的重要研究课题。结合时域上的单台站地磁变化场预测,以及空间域上的区域地磁变化场重构,提出了一种基于克里格重构的区域地磁变化场短时预测模型。以区域范围(101°E¹11°E,30°N111°E,30°N⁴0°N)的地磁测站2009年的数据为实例,结果表明:1)基于克里格方法重构的区域地磁变化场Z分量,准确合理的反映了其时空变化特性;2)在短时预测中,区域模型能紧跟地磁变化场的变化趋势,说明其能很好地描述变化磁场的时空演化特性,且位于区域边缘的台站预测误差稍大。当预测期为1 h、6 h、12 h、24 h时,区域地磁变化场预测模型的平均绝对误差分别为1.67 nT、2.19 nT、2.72 nT、3.14 nT。     

Smart computing approach for design and scale-up of conical spouted beds with open-sided draft tubes

Open-sided draft tubes provide an optimal gas distribution through a cross flow pattern between the spout and the annulus in conical spouted beds.The design,optimization,control,and scale-up of the spouted beds require precise information on operating and peak pressure drops.In this study,a multi-layer perceptron(MLP)neural network was employed for accurate prediction of these hydrodynamic characteristics.A relatively huge number of experiments were accomplished and the most influential dimensionless groups were extracted using the Buckingham-pi theorem.Then,the dimensionless groups were used for developing the MLP model for simultaneous estimation of operating and peak pressure drops.The iterative constructive technique confirmed that 4-14-2 is the best structure for the MLP model in terms of absolute average relative deviation(AARD%),mean square error(MSE),and regression coefficient(R²).The developed MLP approach has an excellent capacity to predict the transformed operating(MSE=0.00039,AARD%=1.30,and R²=0.76099)and peak(MSE=0.22933,AARD%=11.88,and R2=0.89867)pressure drops.     

乐山泥岩的水土曲线和崩解特征试验研究

红层软岩的崩解性引发显著的软岩风化破裂现象，经常导致坡体不稳定、岩石崩落等不良地质现象。为深入理解泥岩的水土特征曲线(soil and water characteristic curve,SWCC)和浸水崩解特征，以乐山红层泥岩为例，采用滤纸法、浸水法等试验方法系统研究了泥岩的SWCC以及其在水中崩解的特征，构建了适合于该地区的SWCC模型，并讨论了浸水时间对泥岩崩解质量、颗粒级配的影响。结果表明：(1)泥岩的SWCC呈单峰曲线，随着含水率的减少，基质吸力增大。(2)通过与4种典型率定曲线的拟合比较，基质吸力拟合结果表现出良好的相关性(R²≥92%)，其中Fredlund&Xing模型能够更准确地反映该地区泥岩的SWCC(R²=96%)。(3)浸水试验表明，0～6 h为快速崩解期，6～12 h为慢速崩解期，12 h后为长期崩解期。干湿交替浸水可以加速泥岩在亲水初期的崩解速率，但在最终崩解量方面与持续浸水基本一致。(4)浸水崩解后，颗粒粒径变化主要集中在2～20 mm范围内，级配曲线D₆₀,D₃₀     

Chemical characteristics of PM2.5 during dust storms and air pollution events in Chengdu,China

Daily fine particulate(PM_2.5) samples were collected in Chengdu from April 2009 to February 2010 to investigate their chemical profiles during dust storms（DSs） and several types of pollution events, including haze（HDs）,biomass burning（BBs）,and fireworks displays（FDs）.The highest PM_2.5 mass concentrations were found during DSs（283.3μg/m³）,followed by FDs（212.7μg/m³）,HDs（187.3μg/m³）,and BBs（130.1μg/m³）.The concentrations of most elements were elevated during DSs and pollution events, except for BBs.Secondary inorganic ions(NO₃^-,SO₄^2-,and NH₄⁺) were enriched during HDs,while PM_2.5 from BBs showed high K⁺ but low SO₄^2-.FDs caused increases in K⁺ and enrichment in SO₄^2-.Ca²⁺ was abundant in DS samples.Ion-balance calculations indicated that PM_2.5 from HDs and FDs was more acidic than on normal days,but DS and BB particles were alkaline.The highest organic carbon（OC） concentration was 26.1μg/m³ during FDs,followed by BBs（23.6μg/m³）,HDs（19.6μg/m³）,and DSs（18.8μg/m³）. In contrast,elemental carbon（EC） concentration was more abundant during HDs（10.6μg/m³） and FDs （9.5μg/m³） than during BBs（6.2μg/m³） and DSs（6.0μg/m³）.The highest OC/EC ratios were obtained during BBs,with the lowest during HDs.SO₄^2-/K⁺ and TCA/SO₄^2- ratios proved to be effective indicators for differentiating pollution events.Mass balance showed that organic matter,SO₄^2-,and NO₃^- were the dominant chemical components during pollution events,while soil dust was dominant during DSs.     

位错载氢运动对材料氢脆行为的影响

位错载氢运动会导致金属结构材料中氢原子的再分布和氢损伤的加剧,但目前仍缺乏相关实验数据支撑。本文首先对比了高锰钢预充氢后在四种应变速率(1×10^–3 s^–1,1×10^–4 s^–1,1×10^–5 s^–1和1×10^–6 s^–1)下的断口特征,随后结合理论计算探究了不同应变速率下位错载氢对金属材料氢脆行为的影响。结果表明较慢应变速率(1×10^–5 s^–1 and 1×10^–6 s^–1)下拉伸的试样具有比较快应变速率(1×10^–3 s^–1和1×10^–4 s^–1)拉伸时更高的氢脆敏感性和更大的断口脆性区面积。这是因为较慢应变速率下拉伸时,氢可以随位错运动,导致在塑性变形过程中形成更大的氢原子扩散距离和脆性区深度。此外,在更慢的应变速率(1×10     

热处理NiAl-Bi2O3涂层的宽温域循环摩擦学行为及高低温润滑相再生机制

采用UMT-3高温摩擦试验机评价了氩气气氛800℃热处理等离子喷涂NiAl-Bi₂O₃涂层在室温至800℃的摩擦磨损性能.通过分析热处理前后涂层及其摩擦表/界面的组成和微结构演变,首次研究了热处理NiAl-Bi₂O₃涂层的高低温润滑相(NiBi、Bi₂O₃和NiO)自适应再生机制及宽温域循环摩擦学行为.结果表明：热处理能使涂层中产生弥散增强的Al₂O₃和具有中低温润滑性的金属间化合物NiBi,提高了涂层室温至800℃的减摩抗磨性能,尤其使涂层在400℃的摩擦系数和磨损率分别从0.39和35.56×10^-5 mm³/(N·m)降至0.28和8.53×10^-5 mm³/(N·m);在800℃时,接触表面通过摩擦氧化再次产生润滑相(Bi₂O₃、NiO),并与增强相Al₂     

融合相似性原理的涡轮叶型流场预测方法研究

计算流体力学(CFD)方法是涡轮叶片等设计阶段性能评估的重要手段.然而,基于CFD的数值仿真方法通常比较耗时,难以满足涡轮叶型设计阶段快速迭代的需求.为实现快速性能评估并克服纯数据驱动预测模型泛化能力不足的问题,受到物理增强的机器学习思路的启发,将相似性原理与深度学习模型相结合,提出了一种泛化能力强的涡轮叶型流场预测新方法.以涡轮叶片表面等熵马赫数分布预测为例,提出采用相似性原理对叶型几何变量和气动参数进行归一化,进而在归一化参数空间构建训练样本集与深度学习预测模型,由此建立统一的流场预测模型,对几何尺寸、边界条件差异较大的叶型气动性能进行评估.在完成模型训练后,对归一化条件下不同工况/不同形状叶型的流场、真实环境下不同工况/不同尺寸叶型的流场以及GE-E³低压涡轮不同截面叶型的流场进行预测,结果表明预测结果的分布曲线与CFD评估结果吻合良好,平均相对误差在1.0%左右,由此验证了所提出的融合相似性原理的流场预测模型的精度与泛化能力.     

基于FEM和RSM的深穴圆柱滚子优化设计

为消除圆柱滚子端部的应力集中现象,提高滚动轴承的疲劳寿命,对圆柱滚子内修形-深穴结构的形状控制参数(深穴开口度k、深穴长度l、深穴锥角α)进行了分析,建立了滚子接触有限元(FEM)模型。基于响应曲面法(RSM),建立了以滚子端部与中间接触应力差最小为优化目标,以k,l和α为设计变量的优化数学模型,并对响应面模型进行了求解,得到一组最优解,通过对比分析表明深穴滚子可以有效地降低滚子端部的应力集中现象,优化后深穴滚子应力分布更为均匀,避免了因局部应力过大而过早发生疲劳失效;采用FEM与RSM相结合的优化方法操作简单、效率高,可将其应用于其他机械零部件的优化设计。     

Characterization of summer PM2.5 aerosols from four forest areas in Sichuan,SW China

Aerosol samples were collected over 24 and 12 h to represent day/night aerosol characteristics in forest areas at Ya’an Baima Spring Scenic Area（BM）,Panzhihua Cycas National Nature Reserve（PZ）,Gongga Mountain National Nature Reserve（GG）,and Wolong National Nature Reserve（WL）,during the summers of 2010-2012.Mass and chemical component concentrations,including organic carbon,elemental carbon,and inorganic ions(F^-,Cl^-,NO₂^-,NO₃^-,SO₄^2-,C₂O₄^2-,PO₄^3-,K⁺,Na⁺,Ca²⁺,Mg²⁺,and NH₄⁺),of PM_2.5 aerosols were measured.The average PM2.5 concentrations for 24 h were 72.42,104.89,20.55,and29.19 μg/m³ at BM,PZ,GG,and WL,respectively.Organic matter accounted for 38.0-49.3%,while elemental carbon accounted for 2.0-5.7%of PM2.5 mass.The sum concentrations of SO₄^2-,NH₄⁺,and NO₃^-accounted for 23.0%,17.4%,22.1%,and 30.5%of PM2.5 mass at BM,PZ,GG,and WL,respectively.Soil dust was also an important source of PM2.5,accounting for 6.3%,17.0%,10.4%,and 19.1%of PM2.5 mass at BM,PZ,GG,and WL,respectively.These reconstructed masses accounted for 75.9-102.0%of PM2.5 mass from the four forest areas of SW China.     

A note of hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

The paper attempts at reviewing a previous research entitled “Hybrid GR-SVM for prediction of surface roughness in abrasive water jet (AWJ) machining” and some problems were found in its reducing parameters process and prediction model. The authors presented a hybrid of grey relation analysis (GRA) and support vector machine (SVM) to estimate the roughness surface in a certain dataset of AWJ machining. Their proposed method may not work in real case of AWJ machining as it is claimed. This paper gives a counter model in order to illustrate these remarks.     

磨合表面形貌特征参数的提取及分析

在销-盘式摩擦磨损试验机上对船用柴油机活塞环-缸套材摩擦副进行磨合磨损试验,采用光学显微镜对不同磨损阶段的磨损表面形貌进行观察分析,应用小波分析和奇异值分解提取磨损表面统计特征的低频特征参数和高频特征参数.结果表明:低频特征参数和高频特征参数刻画了磨合表面的形貌特征,可以作为磨合表面的特征参数;低频特征参数反映了磨合表面的接触面积,其值愈大,接触面积愈大;高频特征参数反映了磨合表面的粗糙度,其值愈大,粗糙度愈小.     

Hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

This paper presents a hybridization model of support vector machine (SVM) and grey relational analysis (GRA) in predicting surface roughness value of abrasive water jet (AWJ) machining process. The influential factors of five process parameters in AWJ, namely traverse speed, water jet pressure, standoff distance, abrasive grit size and abrasive flow rate, need to be analyzed using GRA approach. Then, the irrelevance factors of process parameters are eliminated. There is a need of determining the influential factors of process parameters to the surface roughness as to develop a robust prediction model. GRA acts as feature selection method in preprocessing process of hybrid grey relational-support vector machine (GR-SVM) prediction model. Efficiency of the proposed model is demonstrated. GR-SVM presents more accurate result than conventional SVM as it removes the redundant features and irrelevant element from the experimental datasets.     

粗糙表面的摩擦触觉感知研究

本文中研究了手指触摸粗糙表面的摩擦振动特性、脑电生理反应和主观评价,为产品触感舒适性和抓握可靠性设计以及产品触感量化表征提供理论依据.研究结果显示：随着表面轮廓算术平均偏差和轮廓单元平均宽度的降低,摩擦系数和功率谱重心逐渐增大,垂直偏差逐渐降低;垂直偏差、功率谱重心和摩擦系数特征参数能够反应粗糙表面的形貌特征变化,并且与人的主观感知评价一致,可以用来定量表征人对材料表面粗糙度、细致度和黏着度的感知. ERP曲线的P200成分峰值与接触表面的粗糙特征相关,粗糙度大的表面诱发的P200峰值高;P300成分与人的主观认知判断有关,粗糙感强、细致感差及黏着感低的表面诱发的P300峰值高且潜伏期短.研究表明,材料表面的粗糙特性通过影响皮肤的接触摩擦行为,进而影响人脑的触觉感知和主观评价.表面摩擦振动特性、人脑电生理反应和触感主观评价具有相关性,三者结合是系统研究粗糙表面摩擦触觉感知的有效手段.     

影响内燃机活塞环—缸套擦伤的因素及防擦伤的摩擦学设计

阐述了内燃机活塞环－缸套擦伤的机理。分析了磨合，缸套表面形貌，活塞环外形，活塞组件的热变形与机械变形，润滑油，材料和表面覆层等因素对活塞环擦伤的影响。指出可以采用内燃机强化系数ｐｅｖｍ作为活塞环防擦伤摩擦学设计的判别特征值，从而为从设计上防止活塞环擦伤提供了思路。     

粗糙颗粒的随机离散元模拟——随机法向接触定律

真实颗粒的力学性质会受到其随机粗糙表面的影响,然而在传统离散元模拟中通常假设颗粒具有光滑表面,因此有必要在定量考虑颗粒表面粗糙度的基础上改进离散元的接触模型。本文基于经典 Greenwood-Williamson(GW)模型通过理论分析和数值模拟提出了一种可以考虑颗粒表面粗糙度的法向接触定律;开发了基于 Newton-Raphson迭代的数值计算方法,通过输入颗粒重叠量和一系列表面粗糙系数计算总接触力;讨论了改进计算方法效率和准确性的相关问题。相对于 GW模型中接触关系的复杂积分表示,拟合得到新随机接触定律的表达式具有类似 Hertz定律的简单结构,只包含一个表征颗粒表面粗糙度标准偏差的新增参数,σ,可以方便的引入当前离散元模拟程序中进行计算。     

DYNAMICAL BEHAVIORS OF DOUBLE CAVITATION BUBBLES UNDER ULTRASONIC HONING

为了探讨超声珩磨作用下磨削区的空化机理,基于速度势叠加原理,考虑超声珩磨速度和珩磨压力,建立了磨削区两空化泡的动力学模型. 数值模拟了磨削区空化泡初始半径、两空化泡间距、超声声压幅值、珩磨压力、珩磨头转速对磨削区两空化泡动力学特性的影响. 研究表明,考虑两空化泡之间的相互作用时,要想获得良好的空化效果,可将两空化泡初始半径之比控制在3 倍以内;选择较高的超声波声压幅值与较低的珩磨压力,并且使超声波声压幅值与珩磨压力和液体静压力之差介于0.66~1.89MPa 之间;增大珩磨头转速空化泡溃灭也略有加速;通过试验测量材料表面粗糙度的方法间接验证了理论分析的合理性.     

超声珩磨作用下两空化泡动力学特性

为了探讨超声珩磨作用下磨削区的空化机理,基于速度势叠加原理,考虑超声珩磨速度和珩磨压力,建立了磨削区两空化泡的动力学模型. 数值模拟了磨削区空化泡初始半径、两空化泡间距、超声声压幅值、珩磨压力、珩磨头转速对磨削区两空化泡动力学特性的影响. 研究表明,考虑两空化泡之间的相互作用时,要想获得良好的空化效果,可将两空化泡初始半径之比控制在3 倍以内;选择较高的超声波声压幅值与较低的珩磨压力,并且使超声波声压幅值与珩磨压力和液体静压力之差介于0.66~1.89MPa 之间;增大珩磨头转速空化泡溃灭也略有加速;通过试验测量材料表面粗糙度的方法间接验证了理论分析的合理性.      

Unsteady characteristics of the cavity flow around a rough circular cylinder

Effects of surface roughness on the unsteady cavitating flow around a two-dimensional circular cylinder were experimentally investigated at Reynolds numbers from 1.36 × 10⁵ to 1.78 × 10⁵. Two patterns of surface roughness were investigated, a double-cut pattern and a single-cut pattern. The cavity elongates with an increase of the surface roughness, especially in supercavitating flow. However, for some roughness parameters tested, the cavity length exhibits an extreme decrease. In a particular case of the double-cut pattern, there exists the minimum cavity behind the cylinder.     

粗糙表面接触分形模型的提出与发展

自表面接触塑性变形模型问世以来，经过近４０年的发展，已经形成以分形几何理论为基础的Ｍ－Ｂ粗糙表面接触分形模型．Ｍ－Ｂ模型以分形参数代替统计学参数表征粗糙表面，推导出了实际接触面积与载荷的关系，以及实际弹性接触面积和实际塑性接触面积的计算公式，指出了影响接触面变形性质的因素与规律．由于分形参数的尺度独立性，可望利用Ｍ－Ｂ模型对接触面积的预测不受测量仪器分辨率和取样长度等因素的影响，故其比基于统计分析的Ｇ－Ｗ接触模型更为合理．尽管如此，Ｍ－Ｂ模型还有待完善，多方面的问题尚待进行深入研究