红南油田喀拉扎组储层测井评价

红南油田于20世纪80年代投入勘探开发，并且在白垩系和中体罗统均取得了工业油流，而红南喀拉扎组油藏在2004年7月才被发现，这充分说明它是一个典型的隐蔽性油气藏，具有较高的研究价值。通过对其储层四性关系、油藏特征等方面深入研究，从隐蔽的储集空间和流体性质两方面，剖析了隐蔽性油气藏的成因，在此基础上，建立了一套针对性较强的细岩性低阻低丰度油气层识别方法，可以作为隐蔽型油气藏勘探开发的配套技术。     

曲流河沉积亚相的地震识别方法

本文提出利用三维地震资料相干数据分析研究曲流河沉积相的方法，其优点是在地质分析的基础上，对沉积体系有较为明显的识别特征，且在钻井较少的地区尤为实用。该方法在济阳拗陷东北部上第三系应用中取得了较为明显的效果。     

精准识别 Gpuinfo让假卡无所遁形

Gpuinfo是一款名不见经传的显卡信息监控软件,因为现在我们已经习惯于使用GPU-Z了。不过,最新版的Gpuinfo Beta6却给用户带来了不小的惊喜,那就是它能够绝对准确地识别出打磨显卡。难道这个市场上还     

矢功率谱与RBF网络结合在旋转机械故障诊断中的应用

与传统功率谱相比,矢功率谱融合了多通道的能量信息,反映的信息更全面.径向基函数网络具有良好的推广能力和分类能力.基于此,本文结合矢功率谱和径向基函数网络,提出了一种新的故障识别方法,该方法以矢功率谱为特征向量,径向基函数网络为分类器.并以转子裂纹、转子不对中、油膜涡动为例进行实验研究,实验结果表明,该方法是有效的.     

海底管道干式高压焊接跟踪轨迹的识别

干式高压TIG焊接法是海底输油(气)破损管道修复所用的重要的、焊接质量较高的连接方法,而自动化焊接又是解决潜水员焊接效率低下的有效途径,焊缝跟踪技术则是保证焊接过程正常进行和焊缝质量的关键技术.设计了能克服环境压力影响的CCD图像摄取装置,研究了一套焊缝跟踪路径识别算法.运用直方图均衡化方法强化坡口与非坡口的差别,增加焊缝图像的理解性.提出了以图像灰度最低值拟合成的曲线将整个图像分为两个部分的图像分解法,提高了图像识别目标的焊缝坡口部分所占的比重,有利于二值化阈值的选取.采用基于数学形态学的二值图像边界识别方法分离出焊缝边界,用Hough变换法确定坡口边线位置,最后用图像分解逆过程经合并后识别出坡口所在的位置.所提出的方法组合后抗干扰能力强,计算速度快,为进一步实现自动化焊接奠定了基础.     

Adaptive Face Recognition via Structed Representation

In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspaee approach to classify the test sample. In order to adapt all the eases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low ~ample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.     

Similarity identification method on formational interfaces and application in general granite

An instrumented drilling system can be applied for the acquisition of drilling process parameters.The system can provide continuous and huge data for geotechnical engineering.However, due to the complexity of ground strata, the variation in the drilling parameters with stratigraphical characteristics is great and the correlation between likely comparable parameters is not high, which limits the use of conventional correlation approaches in this field.How to use the data for engineering and how to get a reasonable interpretation for the relationships among the drilling parameters, as well as between a drilling parameter and formational character-istics, become a technical choke point for the development and application of the instrumented drilling system.Based on similarity criteria, the extraction of sample data and characteristics, the pretreatment of data and feature matching algorithms have been ana-lyzed and an approach of slope coefficient searching identification has been established.A case study was carried out for the similar-ity between the rotational speed of the drill bit, flushing pressure, and effective thrust force graphics in general weathered granite.The result shows that the similarity coefficients between the rotational speed of the drill bit, flushing pressure, and effective thrust force are 0.72 and 0.83, respectively.Although there are differences between the distances of the graphics, the curves of both rota- tional speed and flushing pressure agree with the effective thrust curve in shape, which provides a possible method for the identifica- tion of various formations by use of the similarity between feature drilling parameters.     

A recognition method of vibration parameter image based on improved immune negative selection algorithm for rotating machinery

To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery using the negative selection mechanism of biology immune system. This method uses techniques of biology clone and learning mechanism to improve the negative selection algorithm to generate detectors possessing different monitoring radius, covers the abnormality space effectively, and avoids such problems as the low efficiency of generating detectors, etc. The result of an example applying the presented monitoring method shows that this method can solve the difficulty of obtaining fault samples preferably and extract the turbine state character effectively, it also can detect abnormality by causing various fault of the turbine and obtain the degree of abnormality accurately. The exact monitoring precision of abnormality indicates that this method is feasible and has better on-line quality, accuracy and robustness.     

3D Object Recognition Based on Linear Lie Algebra Model

A surface model called the fibre bundle model and a 3D object model based on linear Lie algebra model are proposed.Then an algorithm of 3D object recognition using the linear Lie algebra models is presented.It is a convenient recognition method for the objects which are symmetric about some axis.By using the presented algorithm,the representation matrices of the fibre or the base curve from only finite points of the linear Lie algebra model can be obtained.At last some recognition results of practicalities are given.