Papers by Author: Zai Wen Liu

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Authors: Wen Li, Zai Wen Liu, Ji Ping Xu
Abstract: In order to monitor residential quarter security intelligently this paper designed a remote control system based on ZigBee wireless sensor network and Ethernet. According to monitor requirements about environment parameters and low energy consumption the system used 16 unit SPCE061A and 32 unit SPCE3200 separately as a key controller in sensor node and coordinator node. With the help of UZ2400 and Ethernet controller ENC28J60, it established a star network conforming to ZigBee standard and realized the functions of real-time acquisition collection, wireless remote transmission and communication on microcomputer. By collecting the information of temperature, water level, gas concentration and infrared warning the remote monitor center can know well the whole quarter safety conditions. It introduced the system structure and the designs of hardware and software. The experimental result shows that the system has high reliability, excellent real-time characteristic, extensibility and favorable apply foreground.
Authors: Zai Wen Liu, Xiao Yi Wang, Qiao Mei Wu
Abstract: An integrated evaluative function and prediction model and prewarning system for water bloom in lakes based on Elman neural network is proposed in this paper, in which main influence factor of outbreak of water bloom is analyzed by rough set theory. The study of the function involves some aspects: algal average activation energy of photosynthesis, integrated nutritional status index, and transparency, which are considered from the microcosmic level, the macroscopic level and the intuitionistic level respectively. The values of the function are classified properly. Combined with the basic features of outbreak of water-bloom, Elman network is studied from the angles of theory and experiment and a water-bloom prewarning system in short term based on Elman network is established. The results of simulation and application show that: Elman neural network improves the algorithm of BP neural network, it has long-term prediction period, strong generalization ability, high prediction accuracy; and needs a small amount of sample and this model provides an efficient new way for short-term water bloom prediction, And approaching ability of Elman network is more superficial than common static networks and its velocity of convergence is faster.
Authors: Wei Wei, Min Zuo, Tong Qiang Jiang, Zai Wen Liu
Abstract: Chaotic phenomena in permanent magnet synchronous motors (PMSM) can be observed when parameters in PMSM are in a certain range. In general, chaos will degrade the performance of PMSM or even collapse the system. In order to suppress the chaos in PMSM, cascade adaptive control is utilized in this paper. Faithful model of PMSM is not necessarily required by using adaptive control based on dynamic compensation mechanism. By choosing appropriate controller parameters, chaos will be eliminated and the response speed can be tunable. Numerical simulation results for nominal case and parameter perturbation case are given out to confirm the cascade adaptive control is valid in chaos control of PMSM.
Authors: Chen Chen, Xiao Yi Wang, Zai Wen Liu, Zhi Yao Zhao, Xiao Kai Wang
Abstract: According to the urgent requirement of water quality monitoring, water bloom prediction and emergency treatment decision-making, a multi-functional information system based on GIS (Geographic Information System) is designed and developed, which integrates water quality monitoring and analysis, water bloom prediction and emergency treatment decision-making. VS2010 platform and SQL Server 2005 database are used in the system, and the remote data communication is realized by GPRS. The system has functions such as lakes and reservoirs’ water quality real-time monitoring, teletransmission and location, water quality data analysis, water bloom prediction and emergency treatment decision-making. The medium-term prediction of water bloom is realized by wavelet neural network, and the optimal choice of water bloom emergency treatment decision-making projects is realized by multi-attribute decision-making theory. This design offers effective decision-making system for environmental protection departments, which also has significant meaning to the protection and renovation of water environment, and its application and promotion have considerable social and economic benefits.
Authors: Rui Ni Li, Xiao Yi Wang, Zai Wen Liu, Ji Ping Xu, Ling Bin Wang
Abstract: Various unusual conditions are likely to occur during sewage treatment process, which would lead to some consequences such as the decrease of water quality in the process of sewage treatment and the increase of disposal process, whereby causing a great influence to the practical operation efficiency of sewage treatment factories. Based on the analysis of the fault characteristics during the process of active sludge sewage treatment, a PSO clustering algorithm is presented. By putting this algorithm into the fault classification in sewage treatment, the results demonstrate that this algorithm could be an effective identification towards the unusual conditions during the sewage treatment process, which provides an efficient way for sewage treatment process fault diagnosis.
Authors: Xiao Yi Wang, Meng Liu, Zai Wen Liu, Zhen Su, Xiao Feng Lian, Xiao Dong An
Abstract: To solve the problem that outlet water index Biochemistry Oxygen Demand (BOD) of the Biological Fluidized Bed (BFB) sewage treatment process is difficult to online measure and optimization control of sewage treatment process, Water quality index neural network soft measurement method and the fuzzy control strategy was put forward in this paper. Considering the sewage treatment process exists nonlinear and time-varying characteristic, the effluent water BOD soft sensor model was established employing the process neural network. On the base of this, the optimization control was realized adopting Dissolved Oxygen (DO) for fuzzy control variable Through the soft measurement and fuzzy control model’s simulation training, Shows that the effectiveness and feasibility of these models, an effective soft measurement and optimization control way for BFB sewage treatment have been provided.
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