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| 1 | Leakage Prediction Method for Contacting Mechanical Seals with Parallel Faces显示文摘Since the beginning of the 20th century, many researches on the sealing characteristic of mechanical seals were carried out broadly and in depth by various methods and some leakage models were built. But due to the lack of the way to characterize the main factors of influence on the leakage, most of the early researches were based on the assumptions that the seal faces topography and the frictional conditions were invariant. In the early built models, the effect of the surface topography change of the seal face on the leakage rate was neglected. Based on the fractal theory, the contact of end faces of the rotary and stationary rings was simplified to be the contact of a rough surface and an ideal rigid smooth surface, and the contact interface’s cavity size-distribution function as well as the fractal characteristic of the cavity profile curve was discussed. By analyzing the influence of abrasion on the seal face topography and the leakage channel, the time-correlation leakage prediction model of mechanical seals based on the fractal theory was established and the method for predicting the leakage rate of mechanical seals with parallel plane was proposed. The values of the leakage rate predicted theoretically are similar to the measured values of the leakage rate in the model test and in situ test. The experimental results indicate that the leakage rate of mechanical seals is a transient value. The surface topography of the end faces of the seal rings and its change during the frictional wear of mechanical seals can be accurately characterized by the fractal parameters. Under the work conditions of changeless frictional mechanism, the fractal parameters measured or calculated based on the accelerated testing equation can be used to predict the leakage rate of mechanical seal in service. The proposed research provides the basis for determining the leakage state and predicting working life of mechanical seal. | SUN Jianjun WEI Long FENG Xiu GU Boqin | 2010 | Chinese Journal of Mechanical Engineering2010，23，1： | 16 |
| 2 | Towards an effective personalized information filter for P2P based focused Web crawling 显示文摘 | Fu Xianghua Feng Boqin | 2006 | Journal of Computer Science2006，2，1： | 1 |
| 3 | Conflicts for multi-resource knowledge fusion显示文摘 | Lu Huimin Feng Boqin | 2009 | Information Technology Journal2009，8，8： | 1 |
| 4 | Distributed knowledge inte- gration based on intelligent topic map 显示文摘 | Huimin Lu and Boqin Feng | 2010 | Information Technology Journal2010，，1： | 1 |
| 5 | Mining Representative Subset Based on Fuzzy Clustering显示文摘Two new concepts-fuzzy mutuality and average fuzzy entropy are presented. Then based on these concepts,a new algo-rithm-RSMA(representative subset mining algorithm) is pro-posed,which can abstract representative subset from massive data. To accelerate the speed of producing representative subset,an improved algorithm-ARSMA(accelerated representative subset mining algorithm) is advanced,which adopt combining putting forward with backward strategies. In this way,the performance of the algorithm is improved. Finally we make experiments on real datasets and evaluate the representative subset. The experiment shows that ARSMA algorithm is more excellent than RandomPick algorithm either on effectiveness or efficiency. | ZHOU Hongfang FENG Boqin LU Lintao | 2007 | Wuhan University Journal of Natural Sciences2007，12，5： | 1 |
| 6 | Classification Rule Mining with an Improved Ant Colony Algorithm显示文摘 | Ziqiang Wang Boqin Feng | 2004 | Lecture Notes in Computer Science2004，1，3339： | 1 |
| 7 | Incremental clustering algorithm via crossentropy显示文摘A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on (fuzzy) crossentropy(CE). This algorithm is divided into two parts: initial clustering process and incremental clustering process. The former calculates fuzzy crossentropy or crossentropy of one point relative to others and a hierachical method based on crossentropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the crossentropy measure. Experimental comparisons show the proposed method has lower time complexity than common methods in the largescale data situations or dynamic work environments. | Guan Tao Xu Jiucheng Feng Boqin | 2005 | Journal of Systems Engineering and Electronics2005，16，4： | 0 |
| 8 | Text clustering based on fusion of ant colony and genetic algorithms显示文摘Focusing on the problem that the ant colony algorithm gets into stagnation easily and cannot fully search in solution space,a text clustering approach based on the fusion of the ant colony and genetic algorithms is proposed.The four parameters that influence the performance of the ant colony algorithm are encoded as chromosomes,thereby the fitness function,selection,crossover and mutation operator are designed to find the combination of optimal parameters through a number of iteration,and then it is applied to text clustering.The simulation results show that compared with the classical k-means clustering and the basic ant colony clustering algorithm,the proposed algorithm has better performance and the value of F-Measure is enhanced by 5.69%,48.60%and 69.60%,respectively,in 3 test datasets.Therefore,it is more suitable for processing a larger dataset. | Yun ZHANG Boqin FENG Shouqiang MA Lianmeng LIU | 2009 | Frontiers of Electrical and Electronic Engineering in China2009，4，1： | 0 |
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