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个人信息Personal Information
教授
博士生导师
硕士生导师
性别：男
毕业院校：大连理工大学
学位：博士
所在单位：水利工程系
学科：港口、海岸及近海工程
电子邮箱：sunzc@dlut.edu.cn
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基于新息理论的变点检测及其在长输管道泄漏监测中的应用
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发表时间：2022-10-10
发表刊物：自动化学报
期号：3
页面范围：462-469
ISSN号：0254-4156
摘要：The paper presents a new detection method of abrupt change based on extended sequential probability ratio test (ESPRT) innovation process. This method can convert a parameter model into a non-parameter model using innovation theory. So, the method can be widely applied to practice in combination with ESPRT. The paper uses nonlinear temporal series based on BP neural network to establish the innovation model and leakage detection model of the pipe. It is proved that the detection method can effectively online detect the leak, using the collected data in the laboratory.
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