普及型数控车床主轴控制的设计

对普及型数控车床的主轴变速控制和恒速切削控制进行了分析和研究，介绍利用VVVF实现的主轴变速系统在STAR—3T数控系统中的应用及新的设计，解决了经济型NC车床主轴实现无级变速问题。     

坐标测量机精度及其评定方法研究

本文分析了ISO10360－2坐标测量机性能评定标准，并对一些影响坐标测量精度的因素作了分析，给出了一些单项测试结果和两种测量机的部分测试结果。     

剑杆织机新型引纬机构的震动力完全平衡

针对一种由共轭凸轮机构、空间连杆机构和齿轮机构组合而成的新型剑杆织机引纬机构，通过有效分离，将其中的共轭凸轮作为两个盘形转子单独进行了平衡，其余构件整体上作为空间机构运用线性无关向量法一并进行了平衡，从而实现了整个机构的震动力完全平衡。     

Stability influence factors analysis and construction of a deep beam anchorage structure in roadway roof

Deep beam anchorage structures based on spatial distribution analysis of the cable prestressed field have been proposed for roadway roof support. Stability and other factors that influence deep beam structures are studied in this paper using mechanical calculations, numerical analysis and field measurements. A mechanical model of deep beam structure subjected to multiple loading is established, including analysis of roof support in the return airway of S1203 working face in the Yuwu coal mine, China. The expression of maximum shear stress in the deep beam structure is deduced according to the stress superposition criterion. It is found that the primary factors affecting deep beam structure stability are deep beam thickness, cable pre-tension and cable spacing. The variation of maximum shear stress distribution and prestressed field diffusion effects according to various factors are analyzed using Matlabòand FLAC3D~(TM) software, and practical support parameters of the S1203 return airway roof are determined.According to the observations of rock pressure, there is no evidence of roof separation, and the maximum values of roof subsidence and convergence of wall rock are 72 and 48 mm, respectively. The results show that the proposed roof support design with a deep beam structure is feasible and achieves effective control of the roadway roof.     

Reinforcement selection for deep and high-stress tunnels at preliminary design stages using ground demand and support capacity approach

Underground mining is going to be deeper gradually because near surface resources are going to be depleted. Therefore, risk of seismic events in underground mines is escalating. Additionally, existence of the large ratio of horizontal to vertical stress, could be a potential reason for high-stress condition and occurrence of dynamic activities. Depending on various parameters such as the level of induced stress, rock properties, etc., ground demand changes and it is difficult to estimate. On the other hand,under seismic condition, energy dissipation and deformation capacity of supports is the most important factors, however, rock support performance factors in dynamic conditions are still under investigation.Expanding the knowledge of reinforcement behaviour and capacity, specifically that of the rockbolt as a primary element in seismic conditions, would help to develop a suitable, safe and economic support design. This paper contains various methods to estimate ground demand including the intact rock properties approach, failure thickness and ejection velocity estimation, and rockburst damage potential method. It also covers measurement methods of rockbolts energy dissipation capacities such as drop test,blasting simulating, back calculation and momentum transfer measurement methods. A large-scale dynamic test rig is also explained. Based on the findings, a table and a graph to show the applicable range of each type of rockbolts were presented. Suitable rockbolt types for various ground energy demand and deformation capacity range were categorised in the table and the graph. The presented support selection method facilitates the selection of a suitable reinforcement system at the preliminary stages of design and guides the designer to adjust the support reinforcement system based on observed ground and support reaction.     

锻件产品开发的设计仓库和智能知识供应研究

概述了基于Web、面向锻件产品开发的设计仓库的组成，提出了设计仓库的系统构架，并指出运用KDD方法进行智能知识供应的总体思路和实施模型，是对智能设计支持方法的一种丰富。此外详细分析了用户兴趣度矩阵的组成，并对相应的挖掘算法进行了研究。     

LTE-Advanced网络Uu接口用户行为分析系统的研究与实现

大数据时代,面对海量且复杂的结构化、半结构化和非结构化数据,传统的信令监测分析系统无法快速准确地分类、处理以及存储海量数据中包含的信息.针对这些问题,提出了一种基于Hadoop系统技术平台和支持向量机(Support Vector Machine,SVM)分类算法的LTE-Advanced网络Uu接口用户行为分析系统.对用户行为分析系统的系统架构、在Hadoop平台下数据挖掘分类算法SVM的实现进行了详细阐述,并通过Uu接口进行了现网测试,测试结果表明,提出的用户行为分析系统达到了预期的效果,对用户偏好分析以及精准营销具有推广意义.     

Imbalanced SVM‐Based Anomaly Detection Algorithm for Imbalanced Training Datasets

Abnormal samples are usually difficult to obtain in production systems, resulting in imbalanced training sample sets. Namely, the number of positive samples is far less than the number of negative samples. Traditional Support Vector Machine (SVM)‐based anomaly detection algorithms perform poorly for highly imbalanced datasets: the learned classification hyperplane skews toward the positive samples, resulting in a high false‐negative rate. This article proposes a new imbalanced SVM (termed ImSVM)‐based anomaly detection algorithm, which assigns a different weight for each positive support vector in the decision function. ImSVM adjusts the learned classification hyperplane to make the decision function achieve a maximum GMean measure value on the dataset. The above problem is converted into an unconstrained optimization problem to search the optimal weight vector. Experiments are carried out on both Cloud datasets and Knowledge Discovery and Data Mining datasets to evaluate ImSVM. Highly imbalanced training sample sets are constructed. The experimental results show that ImSVM outperforms over‐sampling techniques and several existing imbalanced SVM‐based techniques.     

Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine

In the application of Wireless sensor net-works (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality es-timation mechanism is proposed, which is based on Sup-port vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive sig-nal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link qual-ity is divided into five levels according to Packet recep-tion rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial re-spectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reason-able. Compared with the recent published link quality es-timation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.     

Distributed video coding based on vector quantization: Application to capsule endoscopy

We present in this paper a new distributed video coding (DVC) architecture for wireless capsule endoscopy. It is based on the state of the art DVC systems, but without using key frames. Instead, it uses an adapted vector quantization (VQ) with a searching complexity that is shifted to the decoder. VQ allows creating a good side information (SI) by exploiting the similarities in human anatomy. Thus, SI is created from a codebook (CB) rather than by motion compensated prediction. This approach decreases largely the complexity of the encoder, which codes only Wyner-Ziv frames, and allows a progressive decoding. The encoder of the proposed DVC generates only a simple hash that is used by the decoder to select the corresponding VQ codeword. The obtained experimental results show that rate-distortion results are better than those of JPEG, and show the possibility of using scalable coding to control the used rate and energy.