Game of two cars: Case of variable speed

A stochastic version of Isaacs's (Ref. 1) game of two cars is dealt with here. In this version, the pursuer, owing to thrust and drag forces, has a variable speed, whereas the evader's speed is constant. Also, the pursuer can maneuver as long as his speed is bounded by some lower and upper limits. The probability of interception, corresponding to optimal (saddle-point) feedback strategies, is computed and serves as a reference for evaluating the performance of four different versions of the proportional navigation pursuit law as well as two other strategies.     

STUDY ON THE DUCTILE DEFORMATION DOMAIN OF THE SIMPLE SHEAR IN ROCKS——TAKING BRITTLE FAULTS OF THE COVERING STRATA IN THE SOUTHERN JIANGSU AREA AS AN EXAMPLE

A study on the ductile deformation domain of the brittle fault in the shallow level ofthe crust is a new probe field for the modern structural geology. Taking the southern Jiang-su Province area as an example the orientation measurement of quartz crystals, the com-positional texture observation of three pressure sensitive minerals and the rheological param-eter determination of dislocation densities, etc. have been demonstrated and analysed basedon typical samples in the present paper. In addition, their generation mechanisms arealso discussed from the cataclastic rheology, the dynamic differentiation and the simpleshearing, specially, from the Ode strength theory. Finally, a generative relationship betweenthe ductile deformation domain of the brittle fault system, in the regional layer--slip andthe formation of the stratabound ore deposit is shown as well.     

Magnetism and structural chemistry of the n=2 Ruddlesden-Popper phase La3LiMnO7

Polycrystalline samples of the n=2 Ruddlesden-Popper phase La₃LiMnO₇ have been prepared and characterized. X-ray and neutron diffraction suggest that the structure is tetragonal with a disordered distribution of Li and Mn cations over the octahedral sites, but ⁶Li MAS NMR shows that the Li and Mn are 1:1 ordered locally. Electron microscopy shows that the stacking of the cation-ordered, perovskite-like bilayers along the crystallographic z-axis is disordered on the distance scale sampled by X-ray and neutron diffraction. Magnetometry data and neutron diffraction data collected at 2 K together suggest that the Mn cations within each structural domain order antiferromagnetically at 14 K, but that the disorder along z prevents the establishment of long-range magnetic order.     

Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph

An effective fault diagnosis method of bearing is the key to predictive maintenance of modern industrial equipment. With the single use of equipment failure mechanism or operation of data, it is hard to resolve multiple complex variable working conditions, multiple types of fault and equipment malfunctions and failures related to knowledge and data. In order to solve these problems, a fault diagnosis method based on the fusion of deep learning with a knowledge graph is proposed in this paper. Firstly, the knowledge rules of bearing data is used for entity extraction. Next, the multiscale optimized convolutional neural network (MOCNN) proposed in this paper is used for fault classification to achieve relationship extraction. Finally, the fault diagnosis graph of the bearing is constructed for fault-assisted decision-making as well as the detailed display of fault information. According to experiment analysis, the fault diagnosis model based on MOCNN proposed in this paper, which integrates the end-to-end convolutional neural network and the attention mechanism, still achieves an accuracy of 97.86% under the data set of 160 types of faults. Compared with the deep learning models such as Resnet and Inception in the noise environment of multiple working conditions and variable working conditions, the model proposed in this paper not only shows a faster convergence speed and stable performance, but also a higher accuracy in evaluation indicators, which is beneficial to practical use.     

Intelligent Fault Diagnosis of Industrial Robot Based on Multiclass Mahalanobis-Taguchi System for Imbalanced Data

One of the biggest challenges for the fault diagnosis research of industrial robots is that the normal data is far more than the fault data; that is, the data is imbalanced. The traditional diagnosis approaches of industrial robots are more biased toward the majority categories, which makes the diagnosis accuracy of the minority categories decrease. To solve the imbalanced problem, the traditional algorithm is improved by using cost-sensitive learning, single-class learning and other approaches. However, these algorithms also have a series of problems. For instance, it is difficult to estimate the true misclassification cost, overfitting, and long computation time. Therefore, a fault diagnosis approach for industrial robots, based on the Multiclass Mahalanobis-Taguchi system (MMTS), is proposed in this article. It can be classified the categories by measuring the deviation degree from the sample to the reference space, which is more suitable for classifying imbalanced data. The accuracy, G-mean and F-measure are used to verify the effectiveness of the proposed approach on an industrial robot platform. The experimental results show that the proposed approach’s accuracy, F-measure and G-mean improves by an average of 20.74%, 12.85% and 21.68%, compared with the other five traditional approaches when the imbalance ratio is 9. With the increase in the imbalance ratio, the proposed approach has better stability than the traditional algorithms.     

无人机入水发射流场仿真及冲击特性分析

跨介质航行是近年来无人机应用领域的重要研究内容。本文通过数值模拟方法,对某型号飞翼式无人机在不同工况下发射入水过程流场演变及运动姿态进行对比分析,同时对其入水冲击响应进行了数值仿真研究,得到不同发射工况下无人机的入水冲击载荷响应情况。结果表明：该型号无人机入水过程的姿态变化同时受水面条件及发射工况影响,静水工况下以25°入水角、4 m/s的条件发射无人机入水时,可实现最优的姿态恢复时间及入水冲击载荷响应值。

     

A Fault Detection Method for Electrohydraulic Switch Machine Based on Oil-Pressure-Signal-Sectionalized Feature Extraction

A turnout switch machine is key equipment in a railway, and its fault condition has an enormous impact on the safety of train operation. Electrohydraulic switch machines are increasingly used in high-speed railways, and how to extract effective fault features from their working condition monitoring signal is a difficult problem. This paper focuses on the sectionalized feature extraction method of the oil pressure signal of the electrohydraulic switch machine and realizes the fault detection of the switch machine based on this method. First, the oil pressure signal is divided into three stages according to the working principle and action process of the switch machine, and multiple features of each stage are extracted. Then the max-relevance and min-redundancy (mRMR) algorithm is applied to select the effective features. Finally, the mini batch k-means method is used to achieve unsupervised fault diagnosis. Through experimental verification, this method can not only derive the best sectionalization mode and feature types of the oil pressure signal, but also achieve the fault diagnosis and the prediction of the status of the electrohydraulic switch machine.     

载体振动对差动激光多普勒测速仪的影响

为了减小载体振动对传统差动激光多普勒测速仪(LDV)测速精度的影响,提出了Janus配置的差动LDV,并对其速度测量的相对误差进行了理论分析与数值仿真。结果表明：Janus配置技术可以近似反演出载体上下振动时的俯仰角,并对速度进行补偿;载体上下振动对传统差动LDV的测量精度有较大影响,而对Janus配置的差动LDV的影响较小;在Janus配置的差动LDV中,当存在俯仰角且大小一定时,随着载体上下起伏速度与运行速度比值增大,速度测量的相对误差增大;当载体上下起伏速度与运行速度的比值为0.01,俯仰角小于10时,Janus配置的差动LDV的速度测量的相对误差小于0.2%。     

郯庐断裂带鲁皖段新生代玄武岩形成机制的稀土判别

根据郯庐断裂带鲁皖段早第三纪、中新世以及更新世玄武岩的稀土元素特征的研究，应用稀土判据探讨了区内玄武岩的形成机制。稀土元素和常量元素的相关关系显示，郯庐断裂带新生代3个阶段玄武岩成岩过程中分离结晶作用不明显，其形成机制应该为上地幔部分熔融作用。通过多种稀土元素联合协变关系也同样反映了这些玄武岩的形成机制为上地幔部分熔融作用，同时也显示区内新生代玄武岩的稀土元素特征继承了其源区物质的稀土元素特征。这一结论与区内Sr，Nd同位素研究的结果相吻合。     

地球静止轨道远程交会过程导航性能评估

远程交会是静止轨道共位卫星自主定点置入的关键途径。针对远程交会过程中大距离跨度下相对运动模型的误差信号特性,理论推导了误差的传递机理,给出了相对导航EKF算法期望及噪声特性的定量分析模型。研究表明,确定距离区间存在最优过程噪声量级及其对应的最优滤波性能,且滤波误差与交会距离正相关,可作为全局最优滤波器的定量设计依据,解决了静止轨道远程交会过程EKF导航算法性能的量化评估问题。仿真表明,分析结论正确,相对速度滤波误差全程优于0.005 m/s(1σ),满足交会任务需求。