NDLI: Working points on-line intelligent optimization strategy for dredging slurry pipeline transportation

Content Provider	IEEE Xplore Digital Library
Author	Zhiyue Bi Qingfeng Wang Jianzhong Tang
Copyright Year	2008
Description	Author affiliation: State Key Lab. of Fluid Power Transm. & Control, Zhejiang Univ., Hangzhou (Zhiyue Bi; Qingfeng Wang; Jianzhong Tang)
Abstract	Based on the analysis of the structure and boundary conditions of a dredge slurry pipeline transport system, a novel working points on-line intelligent optimization strategy was introduced, which uses the pipeline systempsilas specific energy consumption as its optimization goal. It can solve not only the problem of high energy consumption and low efficiency of the optimization methods which use output maximum as their goals, but also the problem that offline static optimization methods canpsilat be applied to the slurry pipeline transport systempsilas working points on-line continuous optimization. Based on the real time process data analysis, this method uses the intelligent technology, such as fuzzy decision and data fusion, to optimize the operating pointspsila parameters. This method doesnpsilat rely on the precise description of the characteristics of slurry pipeline transport system and it can be easily applied to the dredging operation, during which the soil and systempsilas characteristics vary from time to time. Field experiments were carried out to verify the novel optimization strategy. Experiment results show that this method can not only improve the dredging output, but also minimize the fluctuation of slurry concentration and velocity, thus the slurry pipeline transport systempsilas specific energy consumption is lower and its efficiency is higher.
Starting Page	9089
Ending Page	9094
File Size	311579
Page Count	6
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4594366
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Niobium Pipelines Slurries Optimization Energy consumption Optimization methods Artificial intelligence specific energy consumption dredging slurry pipeline transport fuzzy decision data fusion
Content Type	Text
Resource Type	Article

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