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目的解决780 MPa级别超强度钢板冷冲压生产汽车前纵梁时发生的冲压开裂问题。方法通过网格应变分析技术和仿真分析,研究该零件冲压开裂的原因,分析引起开裂的因素,基于CAE模型系统,研究压边力、模具间隙、坯料尺寸、材料性能对开裂的影响规律。结果降低压边力和增加模具间隙均能减轻开裂,但是无法消除冲压开裂;坯料尺寸缩小可以消除冲压开裂,但是优化坯料尺寸需要改变模具上的坯料定位器,同时增大起皱风险;通过提升材料性能可以消除开裂。结论考虑最终各方案成本,选择性能优异的材料进行生产,将冲压开裂率降低至0.6%,满足了冲压要求。 相似文献
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以提取得到的被动声呐目标功率谱特征为基础,采用二进制粒子群(Binary Particle Swarm Optimization, BPSO)优化算法和k最近邻(k-Nearest Neighbor, KNN)分类算法相结合的BPSO-KNN算法进行特征选择和参数优化,分别用KNN分类算法和BPSO-KNN分类算法对实际得到的四类海上被动声呐目标进行分类识别。结果表明,BPSO-KNN算法可对提取的功率谱特征进行特征优化选择,并对KNN分类器进行参数优化,提高了对四类目标的分类精度。该算法在被动声呐目标分类识别方面有参考价值。 相似文献
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利用样本向量的空间位置关系,对目标识别方法进行研究。根据样本向量最小夹角给出了可分类识别率的定义,且应用样本向量间的夹角对样本向量进行筛选,获得了更有利于分类的样本。在此基础上提出了样本向量最小夹角识别算法,以及对样本向量最小夹角和最短距离进行综合的目标识别算法。为了进一步提高识别效果,将特征线之间的最小夹角引入到识别算法当中。所研究的目标识别算法应用到飞机目标识别,若采用奇异值特征作为样本可以得到90.0%以上的识别率,而采用颜色特征作为样本则可以得到92.5%以上的识别率。 相似文献
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采用化学成分分析、力学性能测试和宏、微观检验等方法对斯太尔曲轴断裂原因进行了分析.结果表明,坯料加热过程存在局部过热现象,加上受校直产生的应力作用,最后造成加工后的曲轴发生断裂.除控制坯料的加热温度和时间外,同时改进了工艺流程,解决了斯太尔曲轴质量问题. 相似文献
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基于支持向量机改进算法的船舶类型识别研究 总被引:3,自引:0,他引:3
利用船舶目标辐射噪声DEMON谱特征,采用改进的支持向量机算法,实现了对船舶目标的分类识别研究。针对支持向量机算法对噪声比较敏感和最优分类面求解时约束较多不利于支持向量机最优分类面寻优的问题,在保持支持向量稀疏性和应用径向基核函数的条件下,对支持向量机算法在松弛变量和决策函数两方面进行了改进,提出了基于径向基核函数的齐次决策二阶损失函数支持向量机改进算法,并应用于利用船舶目标辐射噪声DEMON谱进行船舶目标类型分类识别实验。理论分析、数据仿真与实验结果表明,该改进算法实现了在二次规划中的较少约束条件下最优分类面求解,具有模型参数寻优空间广阔、总体分类性能优的特点,其分类性能优于原支持向量机算法,是一种适合于船舶辐射噪声DENOM分类识别的有效的支持向量机改进算法。 相似文献
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采用基于奇异值分解和人工神经网络的多传感器数据融合方法对喷水推进泵的空化状态进行了分类识别研究。首先利用基于奇异值分解的权值估计算法分别对水声信号和振动信号在时间上进行数据级融合,提取出各自的特征,然后将所有特征组合起来作为神经网络的输入,利用BP网络和RBF网络进行特征级融合和分类识别。分析结果表明:基于多传感器数据融合的分类识别结果优于单传感器分类识别结果;采用基于奇异值分解的数据融合方法后,分类识别率显著提高,对空化初生微弱特征的识别效果尤佳。 相似文献
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基于WO_3薄膜的双声路声表面波型SO_2气体传感器 总被引:1,自引:1,他引:0
以金属钨粉,H2O2,CH3OH和PVP(聚乙烯吡咯烷酮)为原料,利用热喷射方法在双声路声表面波器件的测量声路上制作了细微多网孔状WO3薄膜,提出并实现了一种在常温下可以实现对二氧化硫(SO2)气体进行物理吸附和解吸附的基于WO3薄膜的双声路声表面波型SO2气体传感器.声表面波器件的双声路结构消除了由于外界测量条件改变引起的测量误差,也进一步提高了传感器的可靠性和准确性.实验结果表明,该传感器具有好的重复性,在测量范围内对各种浓度的SO2气体具有好的响应特性;传感器在0.5ppm到20ppm浓度范围内的线性灵敏度大约为6.8KHz/ppm. 相似文献
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以淀粉和乙烯醋酸乙烯酯(EVA)为原料制备淀粉/EVA生物质发泡材料,研究了螺杆转速、模头温度和含水率对挤出发泡的影响,并应用人工神经网络技术建立双层BP网络模型,将其正交实验结果作为样本进行训练,对生物质发泡材料的膨胀率进行预测。结果表明,该BP神经网络模型能准确地预测出淀粉/EVA发泡材料的膨胀率,样品的膨胀率随着螺杆转速的增加而逐渐增大,在螺杆转速为320 r/min时达到最大值;样品的膨胀率亦随着模头温度的升高而逐渐增大,在140℃时达到最大值;含水量对淀粉/EVA发泡材料的膨胀率影响显著。 相似文献
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Yu Wang Xuewei Fu Min Zheng Wei‐Hong Zhong Guozhong Cao 《Advanced materials (Deerfield Beach, Fla.)》2019,31(6)
The charge transport system in an energy storage device (ESD) fundamentally controls the electrochemical performance and device safety. As the skeleton of the charge transport system, the “traffic” networks connecting the active materials are primary structural factors controlling the transport of ions/electrons. However, with the development of ESDs, it becomes very critical but challenging to build traffic networks with rational structures and mechanical robustness, which can support high energy density, fast charging and discharging capability, cycle stability, safety, and even device flexibility. This is especially true for ESDs with high‐capacity active materials (e.g., sulfur and silicon), which show notable volume change during cycling. Therefore, there is an urgent need for cost‐effective strategies to realize robust transport networks, and an in‐depth understanding of the roles of their structures and properties in device performance. To address this urgent need, the primary strategies reported recently are summarized here into three categories according to their controllability over ion‐transport networks, electron‐transport networks, or both of them. More specifically, the significant studies on active materials, binders, electrode designs based on various templates, pore additives, etc., are introduced accordingly. Finally, significant challenges and opportunities for building robust charge transport system in next‐generation energy storage devices are discussed. 相似文献
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BP神经网络在复合材料研究中的应用 总被引:1,自引:0,他引:1
人工神经网络因能处理复杂的非线性问题而成为材料科学研究的一种重要方法.在介绍BP神经网络的基础上,综述了其在复合材料设计、工艺优化、性能预测、损伤检测及预测等方面的应用情况,分析了应用中存在的问题,展望了其发展趋势. 相似文献
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Kiyoung Yi K. K. Choi Nam H. Kim Mark E. Botkin 《International journal for numerical methods in engineering》2007,71(12):1483-1511
The springback is a manufacturing defect in the stamping process and causes difficulty in product assembly. An impediment to the use of lighter‐weight, higher‐strength materials in manufacturing is relative lack of understanding about how these materials respond to complex forming processes. The springback can be reduced by using an optimized combination of die, punch, and blank holder shapes together with friction and blank‐holding force. An optimized process can be determined using a gradient‐based optimization to minimize the springback. For an effective optimization of the stamping process, development of an efficient design sensitivity analysis (DSA) for the springback with respect to these process parameters is crucial. A continuum‐based shape and configuration DSA method for the stamping process has been developed using a non‐linear shell model. The material derivative is used to develop the continuum‐based design sensitivity. The design sensitivity equation is solved without iteration at each converged load step in the finite deformation elastoplastic non‐linear analysis with frictional contact, which makes sensitivity calculation very efficient. Numerical implementation of the proposed shape and configuration DSA method is performed using the meshfree method. The accuracy and efficiency of the proposed method are illustrated by minimizing the springback in a benchmark S‐rail problem. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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In this study, the thermal-responsive polymer networks based on poly(vinyl butyral) (PVB) are prepared, and their friction properties in response to external stimuli are investigated. Under dry sliding condition, the materials show low friction (COF ~0.14) at room temperature, but show ultra-high friction (COF ~1.09) at 100 °C above the glass transition temperature of PVB. This marked variation is due to the effect of recovery stress caused by the shape memory effect of polymer networks. Additionally, the recovery stress would increase with the increase of cross-linked density and test temperature above T g, leading to a higher COF. The polymer networks also show excellent mechanical strength with tensile modulus and elongation at break over 60 MPa and 100 %, respectively. To the best of our knowledge, this is the first paradigm about tunable friction properties realized by shape memory polymer. These interesting properties would enable the polymer networks with potential application in the design of intelligent device in future. 相似文献