研究了苹果酸作为浸出剂和还原剂,H2O2作为辅助还原剂,还原浸出废旧锂电池中的Ni、Co、Mn等有价金属,并探讨了不同反应条件对有价金属浸出效率的影响.同时,采用溶胶-凝胶法,以浸出液为原料,原位合成了LiNi1/3 Co1/3 Mn1/3O2三元正极材料.通过X射线衍射(XRD)、扫描电镜(SEM)和电化学测试对再合成三元正极材料进行结构和电化学性能的表征.结果表明,在苹果酸浓度为2.5 mol/L、固液比120 g/L、浸出时间80 min、浸出温度90℃、H2O2用量10％(体积分数)的浸出条件下,有价金属的复合浸出率达到97.5％.同时,再合成材料具有良好的结晶性能,且再合成材料在1C充放电100次后比容量为103.4 mAh/g,容量保持率85.5％,经倍率充放电后,容量恢复率为92.32％.

采用溶胶-凝胶法制备出不同Fe掺杂量的LaCo1-xFexO3,并将其作为锌-空气电池的空气电极活性材料.分别通过XRD、SEM以及电化学测试研究了其形貌结构和电催化性能.结果表明,当Fe取代量超过50％时,LaCo1-x Fex O3的晶体结构由菱面体开始转变为立方体.其中,LaCo0.5 Fe0.5 O3颗粒均匀,晶粒尺寸达到纳米级别,在-0.7 V电位下,表现出了最大的极化电流密度4.92 mA·cm-2.将LaCo0.5 Fe0.5 O3应用于锌-空气电池空气电极中,在1mA恒定电流下,放电电压稳定在1.2V.在80个循环后,充放电压差为0.85V,往返效率保持在57.2％,优于L aC o O 3的0.95 V和52.0％.

采用光学显微镜、扫描电镜、电子万能试验机、数显显微硬度计,研究了一步法淬火配分(Q&P)工艺和热轧一步法淬火配分(HR-Q&P)工艺在不同配分温度下处理后Q235钢的组织和力学性能.结果表明:HR-Q&P工艺使试验钢晶粒明显细化,显微组织由马氏体、铁素体和贝氏体组成,在350℃配分下,屈服强度和抗拉强度都达到最大值,分别为449 MPa和560 MPa,伸长率与原样相比下降了8％,但仍然超过30％;硬相的马氏体和贝氏体的同时出现,导致断口出现二次裂纹;一步法Q&P工艺下,与未处理试验钢相比,抗拉强度提高约32％,屈服强度提高近1倍,伸长率保持在26％以上.

针对锥形缸体轴向柱塞泵工作时,柱塞腔内油液体积急剧变化,腔内产生的压力脉动和压力冲击会造成柱塞泵振动以及噪声的问题,采用了AMESim建立锥形缸体柱塞泵模型的方法,研究了斜盘倾斜角度和油液的可压缩性及粘性对柱塞腔内压力的影响特性.首先,分析了A4VSO锥形缸体柱塞泵的工作原理和运动学关系,以及柱塞腔内压力的理论分析;其次,通过AMESim的二次开发对原有的柱形缸体模块进行了改进,在考虑泄漏的影响下,建立了锥形缸体轴向柱塞泵的仿真模型;最后,使用实验数据验证了仿真模型的可靠性.研究结果表明:随着斜盘倾角、油液体积弹性模量和动力粘度的增大,柱塞腔内压力增大,且油液体积弹性模量的脉动率由最初0.6％的涨幅降为0.34％.

The traditional linear methods for rolling bearing fault diagnosis under non-stationary and nonlinear running status are not effective.In order to monitor the rolling bearing status accurately and timely,a new diagnosis method was put forward by applying the algorithm of Laplacian eigenmap (LE)to the fault diagnosis of rolling bearings. With the method,the advantage of LE algorithm was fully utilized for extracting nonlinear features and reducing dimensions of characteristic space matrix constructed with vibration signals in time domain and frequency domain,the features of running status were extracted and the clustering results were visualized.Two parameters (between-class scatter and within-distance in pattern recognition)were used in experiments as the measurable indicators to identify four different faults of bearings and four different levels of ball damages in bearings.Compared with PCA &KPCA,it was shown that the LE algorithm can more clearly identify the four different faults and the different levels of ball damages,and its recognition efficiency rises greatly.The effectiveness of LE was verified with test samples.