非线性油膜力作用下转子弯扭耦合振动特性研究

建立了非线性油膜力作用下转子-轴承系统弯扭耦合振动的数学模型.采用Rugge-Kutta数值积分方法计算模拟了转子升速过程中弯曲振动和扭转振动的不平衡响应,得到了转子弯曲振动的三维谱图和分岔图.分析发现,转子的弯曲振动会发生倍周期和概周期等复杂的非线性动力学行为.通过与不考虑弯扭耦合作用的系统特性进行比较,指出在转子弯曲振动临界转速附近,弯扭耦合作用对转子弯曲振动特性影响最大.数值分析揭示了扭转振动随转速升高,振幅基本保持不变,频率减小,有助于更深入地认识转子-轴承系统的弯扭耦合振动特性.     

大学英语教学中创新能力的培养

首先明确了创新的定义并在此基础上探索了大学英语教学上的弊端。其次联系“创新”这一概念,就如何在大学英语教学中培养学生的创新能力进行了阐述。最后,就应该如何在大学英语课堂上激发学生的创新能力提出了具有实际意义的建议。     

软土地区水平定向钻施工对周围环境的影响

通过水平定向钻在市政工程中的广泛应用,水平定向钻施工越来越显示出它的优势,其施工对周围环境的影响需要评估。为此,对水平定向钻小直径管道施工过程引起的力学效应进行了讨论,重点探讨了拉力、扭矩和泥浆的影响,同时通过分析沉降位移监测值,就具体施工过程所带来的影响进行了讨论,得出了有益的结论。     

Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride (cBN) superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness, such as titanium alloys and superalloys. However, grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance, the chip storage capability of the working layers and the stability and controllability of the dressing process. Therefore, in this work, novel metallic cBN superabrasive wheels with aggregated cBN (AcBN) grains and open pore structures were fabricated to improve machining efficiency and surface quality. Prior to the grinding trials, the air-borne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials. Subsequently, the comparative experiments were performed and then the variations in grinding force and force ratio, grinding temperature, tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti–6Al–4V alloys. In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes, the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60# and the abrasive blasting distance and time of 60 mm and 15 s, respectively. The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN (McBN) grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains. The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.     

增强神经网络辨识模型泛化能力的研究

神经网络(Artificial Neural Network,ANN)辨识模型的泛化能力是其最主要的性能之一,增强ANN模型的泛化能力也是近年来国内外有关专家学者研究的重点问题。大量研究表明,ANN模型泛化能力的改善与很多因素相关联,其中恰当的性能指标函数设计是一个重要影响因素。文中在分析常见的基于均方误差最小原则的性能指标函数基础上,通过加入ANN辨识模型权值间的延迟信息,进而获得一种改进型性能指标函数。通过仿真,验证了所设计的改进型性能指标函数对增强ANN辨识模型的泛化能力是有效的。