The paper gathered deep layers well logging materiak record well materiak core and cutting material of 27 wells in the daqing district , recognized the different type of igneous rock according to their log response feature , and made a large number of cross plot , then carefully chose several of them which works better igneous rock lithology recognition . made pattern recognition procedure using computer to recognize lithology , synthetical many logging parameter to identify igneous rock lithology . and then on the basis of recognizing lithology , the paper analyzed the lithofacies recognition law in this district 文中采集了大庆地区27口井的深层测井资料、录井资料、岩心和岩屑资料，根据火成岩的测井响应特征识别不同类型的火成岩，并做了大量交会图，精选了几种识别火成岩岩性效果较好的交汇图版，编制计算机识别岩性的模式识别程序，综合多个测井参数识别火成岩岩性，并在识别岩性的基础上，进一步分析本地区岩相的识别规律，最后结合试油资料，分析本地区火成岩储集空间的特点及油气与火成岩岩性和岩相的关系。
The continuous signal is transformed to the discrete signal which it could be recognized the computer through input signal circuit and aid transformation circuit . the discrete control signal which it is output by the computer is transformed to the continuous control signal through output signal circuit and d / a transformation 将检测到的连续角信号经输入信号电路和a d电路转换为飞控计算机识别的离散信号；将飞控计算机输出的离散控制信号经输出信号电路和d a电路转换为滑翔弹的连续控制信号。
Feature extracting method for text information is one of the emphasis of this thesis . the problem of identifying text from different format of title block is solved by using template and feature identifying technologies . so the text information in cad files can be recognized and shared with different cad systems 论文采用特征识别方法和模板技术解决了由于标题栏格式不同给文字信息提取带来的困难，实现了图纸文字信息的计算机识别，满足了异构cad系统之间零件信息的数据共享。
And that system has a great help especially for the safeguard and solving cases . aimed at advancing the speed of extracting the key characters , improving the veracity , cutting down the cost of time and space , this task put forward a new template thinning algorithms after analyzing the principle , disadvantages and advantages of many thinning methods including condition thinning , template thinning and thinning in morphology maths . this algorithm with good collection has less thin - hair , and avoid excessive erosion 为了使计算机识别时能很快的提取关键特征，提高准确度，减少时空耗费，本课题在分析了多种传统的条件细化、模板细化、形态数学上的细化等多种细化方法的原理和优缺点后，提出了一种新的模板细化算法，该算法毛刺较少，避免了过度的腐蚀，同时具有良好的连通性。
