本文選題：耙吸挖泥船 + 密度預(yù)測　； 參考：《江蘇科技大學(xué)》2017年碩士論文

【摘要】：隨著經(jīng)濟的不斷發(fā)展,近年來,我國耙吸挖泥船的建造和疏浚技術(shù)已經(jīng)取得了較大的進步,國內(nèi)的耙吸挖泥船正朝著自動化的方向發(fā)展。隨著國內(nèi)港口疏浚工程量的日益增加,耙吸挖泥船疏浚作業(yè)的高效化越來越受到疏浚行業(yè)的關(guān)注。然而,國內(nèi)有關(guān)研究提高疏浚作業(yè)效率的成果尚少。因此,如何根據(jù)現(xiàn)場施工條件來提高耙吸挖泥船疏浚效率已成為國內(nèi)疏浚行業(yè)的重點研究方向,本文通過研究耙吸挖泥船疏浚作業(yè)過程,對施工控制參數(shù)進行優(yōu)化。本文在中交疏浚技術(shù)裝備國家工程研究中心基金項目的支持下,對如何提高疏浚效率進行了研究。文中采用遺傳神經(jīng)網(wǎng)絡(luò)的方法對耙頭密度進行了預(yù)測,使用多種群遺傳算法對疏浚土質(zhì)參數(shù)進行了估算并對施工參數(shù)進行優(yōu)化,開發(fā)了耙吸挖泥船疏浚界面,為施工人員提供了疏浚數(shù)據(jù)和施工控制參數(shù)的參考。本文主要研究如下:首先,本文對耙吸挖泥船耙頭疏浚機理進行了分析研究,根據(jù)流量、航速、波浪補償器壓力等參數(shù)使用遺傳神經(jīng)網(wǎng)絡(luò)對吸入密度進行預(yù)測。通過從廈門港獲得的實測數(shù)據(jù)對預(yù)測密度進行仿真驗證,仿真結(jié)果表明:該方法具有很高的預(yù)測準確性,可以為施工人員提供吸入密度參考,以便船員調(diào)整施工參數(shù),避免因吸入密度過大使得泥泵發(fā)生氣蝕而損壞。其次,本文對耙吸挖泥船疏浚過程中泥艙沉積模型進行了分析研究,使用多種群遺傳算法對裝艙質(zhì)量進行擬合,從而給出當前疏浚工況的土壤參數(shù),然后,根據(jù)土質(zhì)參數(shù)判斷土質(zhì)類型。仿真結(jié)果表明:該方法能夠準確地擬合裝艙質(zhì)量,可為施工人員提供疏浚土質(zhì)類型的參考。最后,本文結(jié)合耙頭模型和泥艙沉積模型使用多種群遺傳算法給出優(yōu)化的航速、流量,提高了疏浚效率。最終,開發(fā)了耙吸挖泥船疏浚界面,該界面實現(xiàn)了當前疏浚產(chǎn)量和優(yōu)化產(chǎn)量的對比。此外,該界面給出了最佳疏浚周期的控制參數(shù),可為施工人員提供參考。
[Abstract]:With the development of economy, in recent years, the construction of suction dredger and dredging technology have made great progress in our country, and the domestic suction dredger is developing towards the direction of automation. With the increasing amount of dredging engineering in domestic ports, the high efficiency of dredging operation of rake suction dredger has been paid more and more attention by dredging industry. However, there are few achievements in improving the efficiency of dredging operation in China. Therefore, how to improve dredging efficiency of suction dredger according to site construction conditions has become the key research direction of domestic dredging industry. In this paper, the construction control parameters are optimized by studying the dredging process of suction dredger. This paper studies how to improve the dredging efficiency with the support of the National Research Center for dredging Technology and equipment. In this paper, the method of genetic neural network is used to predict the density of the rake head, the parameters of dredged soil are estimated and the construction parameters are optimized by using the multi-population genetic algorithm, and the dredging interface of the rake suction dredger is developed. The reference of dredging data and construction control parameters is provided for the construction personnel. The main contents of this paper are as follows: firstly, the dredging mechanism of suction dredger head is analyzed and studied in this paper. The suction density is predicted by genetic neural network according to the parameters of flow, speed and pressure of wave compensator. The simulation results show that the proposed method has a high prediction accuracy and can provide a reference for the construction personnel to adjust the construction parameters by using the measured data obtained from Xiamen Port, and the simulation results show that the proposed method can provide a reference for the construction personnel to adjust the construction parameters. Avoid cavitation damage due to excessive suction density. Secondly, the sediment model of mud tank in dredging process of rake suction dredger is analyzed and studied, and the loading quality is fitted by multi-population genetic algorithm, and then the soil parameters of current dredging condition are given, and then, The soil type is judged according to the soil quality parameters. The simulation results show that the method can accurately fit the loading quality and provide reference for the dredged soil type. Finally, combined with the rake head model and the mud tank sediment model, the optimal speed and flow rate of the dredging are obtained by using multi-population genetic algorithm, and the dredging efficiency is improved. Finally, the dredging interface of the rake suction dredger is developed, which realizes the comparison between the current dredging yield and the optimized output. In addition, the control parameters of the optimal dredging period are given at the interface, which can be used as a reference for the constructors.
【學(xué)位授予單位】：江蘇科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U674.31;TP18

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