基于大数据的绞吸挖泥船参数自主寻优方案设计

Design of autonomous optimization scheme of cutter suction dredger parameters based on big data

绞吸挖泥船的施工过程非常复杂,具有较多的不确定性和随机性。针对绞吸挖泥船生产过程中疏浚产量受施工环境影响较多、稳定性不足、生产率不高的问题,以绞吸挖泥船传输管道中的泥浆为研究对象,分析挖泥施工的特性与影响因素,将疏浚工程历史大数据进行预处理,比较T-S模型和历史数据最近邻的两种不同的流量预测方案,采用偏差反馈控制器进行基于大数据的施工参数自主寻优。结果表明:由于数据进行了预处理,第2种流量预测方案准确率更高;按寻优参数进行反馈控制调节的流量比原始流量更高。

The construction process of cutter suction dredger is very complex,with more uncertainty and randomness.Regarding the problems of many impacts in dredging output,insufficient stability and low productivity,we take the slurry in the transmission pipeline of cutter suction dredger as the research object,analyze the characteristics and influencing factors of dredging construction,preprocess the historical big data of dredging engineering,compare two different flow prediction schemes of T-S model and historical data nearest neighbor,and use deviation feedback controller to independently optimize construction parameters based on big data.The results show that the accuracy of the second scheme is higher because the data are preprocessed.The flow adjusted by feedback control according to the optimization parameters is higher than the original flow.