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Safety monitoring system of dam based on bionics

机译:基于仿生学的大坝安全监控系统

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Safety monitoring of dam is an integration of information obtaining and processing pattern recognition and knowledge discovery. The information on dam safety needs to be managed, processed and analyzed in real time. Based on the thought of life sciences and systems engineering, a bionics model of dam safety monitoring was proposed. From the viewpoint of a vital and intelligent system, this paper designed a monitoring system of dam safety, which was composed of integration control, comprehensive inference engine, project database, model base, graphics base, and input/output modules. Metadata base based on OODM was used to implement the integration of homogeneous or nonhomogeneous databases storing dam safety data from different information sources. The multilevel link style was adopted to manage model base. This work used the fuzzy theory and artificial neural networks to build the inference models, which can analyze and evaluate the run characteristics of dams. In practice, the proposed system has been used to monitor dam safety successfully. The applications show that the bionics model is feasible, the system structure is reasonable, the proposed key technologies are effective. The systems can supply technical support for improving the level of dam safety management, extending normal run time of dam and voiding dam failure.
机译:大坝的安全监控是信息获取和处理模式识别以及知识发现的集成。大坝安全信息需要实时管理,处理和分析。基于生命科学与系统工程思想,提出了大坝安全监控的仿生模型。从生命力和智能系统的角度,设计了大坝安全监控系统,该系统由集成控制,综合推理引擎,项目数据库,模型库,图形库和输入/输出模块组成。基于OODM的元数据库用于实现存储来自不同信息源的大坝安全数据的同构或非同构数据库的集成。采用了多级链接样式来管理模型库。这项工作使用模糊理论和人工神经网络来建立推理模型,从而可以分析和评估大坝的运行特性。在实践中,所提出的系统已被成功地用于监测大坝的安全。应用表明,仿生学模型是可行的,系统结构合理,所提出的关键技术是有效的。该系统可以为提高大坝安全管理水平,延长大坝的正常运行时间和排空大坝故障提供技术支持。

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