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The research on high speed underwater target recognition based on fuzzy logic inference

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Journal of Marine Science and Application 2006年第2期5卷 19-23页

作者： JIANG Xiang-Dong YANG De-Sen SHI Sheng-guo LI Si-Chun College of Underwater Acoustics Engineering Harbin Engineering University Harbin 150001 China

The underwater target recognition is a key technology in acoustic confrontation and underwater defence. In this article, a recognition system based on fuzzy logic inference (FLI) is set up. This system is mainly composed of three parts: the fuzzy input module, the fuzzy logic inference module with a set of inference rules and the de-fuzzy output module. The inference result shows the recognition system is effective in most conditions.

关键词： features extraction target recognition fuzzy logic inference

GRADE-LIFE PROGNOSTIC MODEL OF AIRCRAFT ENGINE BEARING

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Transactions of Nanjing University of Aeronautics and Astronautics 2012年第2期29卷 171-178页

作者：苗学问牛枞杨云韩磊洪杰空军装备研究院北京理工大学信息与电子学院北京航空航天大学能源与动力工程学院

Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduced to de- scribe the service life of bearings. A GL prognostic model for aircraft engine bearings is proposed based on sup- port vector machine （SVM） and fuzzy logic inference. Firstly, the mathematical model is discussed to predict the physics-based GL （PGL）. Then, the diagnostic estimation model based on SVM is presented in detail to predict the empirical GL （EPL）. Thirdly, a fuzzy logic inference is adopted to fuse two GL predicted results. Finally, the GL prognostic model is verified by the run-to-failure data acquired from an accelerated life test of an aircraft bearing. The results show that the model provides a more practical and reliable prediction for the service life of bearings.

关键词： aircraft engine bearing grade-life fuzzy logic inference SVM

Method for Underwater Target Tracking Based on an Interacting Multiple Model

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Geo-Spatial Information Science 2008年第3期11卷 186-190页

作者： XU Weiming LIU Yanchun YIN Xiaodong Department of Electronic Engineering Tsinghua University Qinghuayuan Beijing 10084 China Department of Hydrography ＆ Cartography Engineering Dalian Naval Academy 667 Jiefang Road Dalian 116018 China.

According to the requirements of real-time performance and reliability in underwater maneuvering target tracking as well as clarifying motion features of the underwater target, an interacting multiple model algorithm based on fuzzy logic inference （FIMM） is proposed. Maneuvering patterns of the target are represented by model sets, including the constant velocity model （CA）, the Singer mode~, and the nearly constant speed horizontal-turn model （HT） in FIMM technology. The simulation results show that compared to conventional IMM, the reliability and real-time performance of underwater target tracking can be improved by FIMM algorithm.

关键词： underwater target tracking interacting multiple model fuzzy logic inference

fuzzy Based Auto-coagulation Control Through Photometric Dispersion Analyzer

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Journal of Harbin Institute of Technology(New Series) 2004年第2期11卷 164-167页

作者：白桦李圭白 School of Environmental Engineering Tongji UniversityShanghai 200092 China School of Mechatronics Engineering Harbin Institute of Technology Harbin 150006 China 3. School of Municipal and Environmental Engineering Harbin Institute of Technology Harbin 150090 Chinahe main role of water treatment plants is to supply high-quality safe drinking water. Coagulation is one of the most important stages of surface water treatment. The photometric dispersion analyzer(PDA) is a new optical method for flocculation monitoring and is feasible to realize coagulation feedback control. The on line modification of the coagulation control system's set point(or optimum dosing coagulant) has influenced the application of this technology in water treatment plant for a long time. A fuzzy control system incorporating the photometric dispersion analyzer was utilized in this coagulation control system. Proposed is a fuzzy logic inference control system by using Takagi and Sugeno's fuzzy if-then rule for the self-correction of set point on line. Programmed is the dosing rate fuzzy control system in SIEMENS small-scale programmable logic controller. A 400 L/min middle-scale water treatment plant was utilized to simulate the reaction. With the changes of raw water qualitythe set point was modified correctly in time as well as coagulant dosing rate and residual turbility before filtration was eligible and stable. Results show that this fuzzy inference and control system performs well on the coagulation control system through PDA.

The main role of water treatment plants is to supply high-quality safe drinking water. Coagulation is one of the most important stages of surface water treatment. The photometric dispersion analyzer(PDA) is a new optical method for flocculation monitoring, and is feasible to realize coagulation feedback control. The on line modification of the coagulation control system' s set point( or optimum dosing coagulant) has influenced the application of this technology in water treatment plant for a long time. A fuzzy control system incorporating the photometric dispersion analyzer was utilized in this coagulation control system. Proposed is a fuzzy logic inference control system by using Takagi and Sugeno' s fuzzy if-then rule for the self-correction of set point on line. Programmed is the dosing rate fuzzy control system in SIEMENS small-scale programmable logic controller. A 400 L/min middle-scale water treatment plant was utilized to simulate the reaction. With the changes of raw water quality, the set point was modified correctly in time, as well as coagulant dosing rate, and residual turbility before filtration was eligible and stable. Results show that this fuzzy inference and control system performs well on the coagulation control system through PDA.

关键词： coagulation dosing rate control photometric dispersion analyzer fuzzy control fuzzy logic inference optimum water treatment