The identification of the milling tools wear state (MTWS) exerts a significant influence on mill-ing workpiece quality. Through the demodulation to the milling force signal by Hilbert Transform,the MT-WS-related signal is obtained in order to monitor the MTWS more effectively, rapidly and accurately. The energy of the frequency band is extracted through the wavelet packet decomposition by db4 wavelet function. By analyzing the energy with the tool wear curve, the frequency band representing the MTWS is then ob-tained and the Zoom-FFT method is used on whole frequency band refinement. Through experiment, the amplitude change rule on zero frequency of the refined frequency band and the spectrum movement rule on whole frequency are testified. The MTWS can be identified rapidly and accurately by relating the two rules.

螺旋升降柱及其构成的升降平台结构简单紧凑、易于控制,目前广泛用于舞台及各种工作平台的顶升.针对这种螺旋升降柱,介绍了其两种结构及工作原理.为进一步分析研究其静力特性,通过Solidworks对其"I-Lock"结构某型号建立模型,导入有限元分析软件ANSYS Workbench,建立了适当简化的两种高度的螺旋升降柱有限元模型并分别分析最大静载工况下的静力特性,研究了载荷对不同高度螺旋升降柱应力、位移大小与分布的影响.结果一方面证明了结构符合设计要求,另一方面也为结构的进一步设计优化提供了参考.

目前使用的内燃双头轨枕螺栓扳手(简称内燃螺栓扳手)不能实时显示拧紧扭矩,难以满足对轨枕螺栓紧固作业精度和效率的要求.对现有的内燃螺栓扳手进行数字化改进,增加扭矩测量及显示功能.在添加的扭矩测量装置中,使用电阻应变式压力传感器测量压缩弹簧的压力;对安全离合器模型进行简化并分析,确定了弹簧压力与拧紧扭矩之间的线性关系;用改进后的设备分组进行实验,使用SPSS软件进行数据分析,建立起弹簧压力与拧紧扭矩之间的线性回归方程;将理论分析和实验分析得到的结果进行对比,验证了理论分析结果的正确性,也验证了该方案的可行性.对现有内燃螺栓扳手进行数字化改进成本较低,改进后的设备大大提高了路务工人的作业效率和精度.

It is a new paradigm to apply data mining technologies to analyze the crime groups and terrorist social networks,there is little work being done on analyzing the communication behavior of criminal and terrorist groups.This paper designed a simulation email system based on personality trait dimensions,called MEP,to model the email users' traffic behavior,proposed a new approach of computing the weight of each dimension in a personality trait vector by using personality trait judge matrix,and simulated the real-world email communication behavior based on normal distribution model satisfying users' personality trait.This paper proposed a social network analysis based algorithm called CNKM(Crime Network Key Member mining) to mine key members of a crime group,and employed time-series analysis techniques to discover the email sending and receiving rules in order to detect the abnormal communication cases.The experimental results show the efficiency and usability of the simulation email analysis system,the average simulation error is less than 10%,and demonstrate that CNKM is efficient.

An algorithm to accurately identify the VGA mode is designed in this paper,which is based on the horizontal synchronous signal and the vertical synchronous signal,and can be applied to FPGA in order to complete the scheme of the VGA video collection card through the frequency counting theory.The algorithm is implemented in Verilog HDL,and is accomplished by Quartus II of the Altera company.

A scheme to identify the VGA modes and the frequency of pixels is designed in this paper,which is based on FPGA.The design is based on the idea of frequency counting and it is verified by hardware circuit.By using Verilog HDL and applying FPGA to the design of embedded video collection chip,the design can speed up data processing and save hardware resource.

It is hot topic to apply data mining techniques to anti-criminal and anti-terrorism research in many law enforcement agencies.The main contributions of this paper include:(1)designed a conceptual e-mail system(CEM)based on personality trait dimensions and intelligence attribute of e-mail users in order to model the e-mail traffic behavior of criminal and terrorist organizations;(2)used normal distribution controlled by the personality trait dimension and intelligence attribute to generate e-mail data;(3)used social network analysis and time-series visualization to search for interesting e-mail behavioral patterns and abnormal communications;(4)demonstrated that CEM has good robust and scalability,exactly simulate the behavior in e-mail's,and solve the problem of lacking simulation model of the e-mail system.