Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

考虑流固耦合的管道机器人冲击环焊缝过程动力学建模与分析

以管道机器人（Pipeline inspection gauge，PIG）为载体的内检测技术是保障油气管道安全运输的重要手段。针对管内高压流体作用下，管道机器人在冲击管内环焊缝过程中产生的动力学行为突变问题。建立了管道周向受限空间中基于Kelvin弹簧阻尼的管道机器人密封盘等效动力学模型，结合管道机器人本体建立了多体系管道机器人动力学模型；详细推导了管道机器人轴向振动微分方程，以及管内流体的流动方程；并使用Matlab/Simulink与Adams进行流固耦合仿真，作为重要的工艺参数之一，研究了管道机器人速度改变时，其在冲击环焊缝过程中的动力学响应情况。结果表明：所建立的密封盘及管道机器人动力学模型能够很好地表征密封盘在管道轴向、径向以及周向的力学特性；运行速度越快，管道机器人通过环焊缝引起的轴向振动越剧烈，冲击振动越明显；而垂向和俯仰振动现象随运动速度增大而显著减弱。     

郭庄煤业选煤厂振动筛筛选形式的优化研究

针对郭庄煤业选煤厂振动筛振动筛分方式可靠性差、筛分效率低下、物料筛分率低的难题,本文提出了三种新的振动筛分方案,对不同筛分方案的实际应用效果进行了分析。结果表明三移动一摆动的振动筛分方式对物料的综合分散度最高,稳定性好,该筛分方案已在郭庄煤业选煤厂煤炭筛分过程中得到了全面的应用。     

不同润湿表面液体沸腾的分子动力学模拟

采用分子动力学方法研究纳米尺度下液氩在过热基板上的沸腾过程。通过调节固液间相互作用的方式改变壁面润湿性，模拟并分析了壁面润湿性对沸腾过程中能量传递和液体运动情况的影响。结果表明：不同润湿性表面均会发生固液分离的现象，但是固体表面附近吸附的氩原子数密度随润湿性增强而增大；润湿性较强时，液体的能量上升快，热通量高，液体内部温度梯度大，发生固液分离时间早，系统中氩的温度和能量低，上升过程中液氩密度、厚度变化小；润湿性较弱时，液体的能量上升慢，热通量小，液体内部温度梯度小，发生固液分离时间延后，系统中氩的温度、能量更高，上升过程中液氩密度、厚度变化较大。下部气体压力整体上大于上部气体压力，发生固液分离时润湿性越强的表面上液体上下压差越大，首次上升过程能达到的高度越高，所需时间越短。     

A simple model for deep dynamic stall conditions

The present study is focused on modeling of dynamic stall behavior of a pitching airfoil. The deep stall regime is in particular considered. A model is proposed, which has a low implementation and computational complexity but yet is able to deal with different types of dynamic stall conditions, including those characterized by multiple vortex shedding at the airfoil leading edge. The proposed model is appraised against an extensive data set of experimental (α,C_L) curves for NACA0012. The results of an existing widely used model, having comparable complexity, are also shown for comparison. The proposed model is able to well reproduce not only the classic curves of deep dynamic stall but also the curves characterized by lift oscillations at high angles of attack due to the shedding of multiple vortices. Furthermore, the model appears to be robust to variations of its parameters from the optimal values and of the airfoil geometry. Finally, the model is successfully implemented in a commercial CFD software and applied to the simulation of a vertical axis wind turbine within the actuator cylinder approach. The accuracy of the prediction of the turbine power coefficient in the whole rotation cycle is very good for the optimal working condition of the turbine, for which the model parameters were calibrated. Fairly good accuracy is also obtained in significantly different working conditions without any further calibration.     

Kernel-based fourth-order diffusion for image noise removal

The fourth-order partial differential equations have good performance on noise smoothing and edge preservation without creating blocky effects on smooth regions. However, for low signal-to-noise ratio images, the discrimination between edges and noise is a challenging problem. A novel kernel-based fourth-order diffusion is proposed in this paper. It introduces a kernelized gradient operator in the fourth-order diffusion process, which leads to more effective noise removal capability. Experiment results show that this method outperforms several previous anisotropic diffusion methods for noise removal and edge preservation.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

铸态Ti-20Zr-20Al钛合金动态压缩力学性能与断裂机制研究

采用X射线衍射仪、金相显微镜、分离式霍普金森杆和扫描电镜等手段研究了Ti-20Zr-20Al钛合金在动态压缩条件下的微观结构、力学性能和断裂机制。结果表明,Ti-20Zr-20Al铸态合金由Zr基体相和TiAl/Ti₃Al针状相组成; 随着应变率增加,合金的抗压强度增加,失效应变显著增加; Ti-20Zr-20Al合金的断裂机制为解理断裂; 随着应变率增加,试验压缩断裂后碎片总数增大,平均粒径减小。采用DID模型模拟的材料碎片尺度与实验结果比较吻合,Grady模型与实验结果的偏差较大。     

饱和尾粉砂动孔隙水压力发展特性试验研究

采用动三轴仪对内蒙古某尾矿库尾粉砂进行了动强度试验,研究了围压、相对密实度及固结比对动荷载作用下尾粉砂中孔隙水压力发展特性的影响。研究结果表明,随着固结比、相对密实度、围压的增大,动荷载作用下饱和尾粉砂孔压增长曲线形状由陡峭转变为平缓。随着围压及固结比增大,试样动力破坏形式从以孔压值为主要表征指标的液化破坏,转化为以动剪应变为主要破坏形式的软化破坏。动荷载作用下发生液化破坏的饱和尾粉砂孔压增长过程分可为初始增长阶段、稳定增长阶段和快速增长至破坏阶段,孔压增长曲线表现为明显的反S型,本文采用双对数函数对该试验孔压增长曲线进行拟合,结果表明该模型可以较好地模拟尾粉砂在动荷载作用下的孔压发展规律。     

基于TRIZ理论滤咀排列鼓工装夹具优化设计

针对滤咀排列鼓工装夹具所存在的制造难度大,精度难于保证,效率低的问题。利用TRIZ理论进行分析,根据技术矛盾解决方法并结合问题的实际情况,获得了具体可行的解决方案。经过实践证明,此设计方案是可行的、可靠的,大大缩短了夹具的加工周期,提高了生产效率,节约了成本。