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基于LS-SVM的盾构密封舱土压建模仿真研究

Modeling and Simulation of Shield Sealed Cable’s Earth Pressure Based on LS-SVM

【作者】 刘任喜

【导师】 邵诚;

【作者基本信息】 大连理工大学 , 控制理论与控制工程, 2009, 硕士

【摘要】 密封舱土压是盾构掘进过程中一个非常重要的控制参数,压力失衡将导致地表坍塌等严重的工程事故。但现在的施工多是人工控制操作,控制精度较低。因此,实现盾构掘进过程的自动控制是当前自动化领域研究的热点问题。目前对土压平衡盾构系统的研究多集中在诸如推进系统、排渣系统等一些相对独立的领域里,这些研究都没有考虑其整体特性,且都未考虑刀盘转速的影响,无法反映盾构掘进过程中盾机的整体性能。而在研究方法上多采用神经网络、模糊算法等,并未得出具体的模型形式。再加上盾构施工现场情况复杂,影响土压的因素较多,而且实验研究需要较大的投资,所以,目前大部分土压平衡盾构系统的分析与设计都是依赖工程实践经验。基于此,本文提出一种建立盾构土压模型的方法,结合现场施工数据,对土压平衡盾构施工过程中的特性进行研究,为实际盾构施工工程提供指导与参考。由于建立土压平衡盾构系统的机理模型比较困难。因此,本文在广泛研究国内外盾构理论的基础上,基于盾构掘进过程的机理分析,初步确定土压值与刀盘转速、总推力、螺旋输送机转速及推进速度有关。进一步,利用主元分析方法来估计土压值与这些因素的相关性强弱,得出结论:推进速度、螺旋输送机转速、刀盘转速及总推力为土压值的主元。基于此,首先对现场采集数据进行数据预处理;其次,利用最小二乘支持向量机(LS-SVM)方法,结合现场施工数据,选用六种核函数来对土压进行建模分析,并引入均方根误差(RMSE)和绝对平均值百分误差(MAPE)来评价该模型的预测精度,进而确定采用二次多项式核函数建立的土压模型其估计能力较好;最后,通过仿真试验验证了该模型的有效性。并结合MAPE评价标准,比较LS-SVM模型与BP神经网络模型的估计能力,试验表明LS-SVM模型有较好的估计能力和推广能力。

【Abstract】 The earth pressure of the sealed cabin is a very important controlling parameter and is intimately related to the stability of excavated surface and deformation of ground. However, at present, most constructions are manual operations and controls, which lead to low control accuracy. Thus, the realization of automatic control during the excavation of Shield is a hot topic in the present automation research.At present, most of the researches are focus on some relatively independent areas, such as Propulsion System or Casting System. While research on the whole characteristic of EPB shield system is relatively less and exclude the consideration of affect of the speed of cutter head. The result is that it can’t reflect the overall performance during the excavation of shield. In the other side, the research methods, such as Artificial Neural Networks or Fuzzy Algorithm, which can’t get a specific form of the model. In addition, the situation of the construction of shield is complex and there are many factors that could affect the earth pressure. Moreover, it generally requires lots of investment in equipments to perform on site test or experiments of physical model which set back the process of research. Therefore, most of the analysis and designs of Earth Pressure Balance Shield System are based on engineering experience. For these reasons, this paper raise a method of establishing the earth pressure model of EPB shield, and do a research of the character of the construction process of EPB shield combined with construction-site data, which could provide some instructions and references for the construction of shield.It is difficult to establish the mechanism model of shield EPB system directly. Therefore, the thesis identify the earth pressure value may be relative with cutter head speed, main thrust, screw conveyor speed and advancing speed based on the mechanism during the excavation of shield and the study on shield theory at home and abroad. Furthermore, the use of principal component analysis to estimate the value of earth pressure and the strength of the correlation of these factors lead to a conclusion that the earth pressure has four principal elements as follows: advancing speed, cutter head speed, screw conveyor speed and main thrust. For these reasons, first, preprocess the construction-site data. Secondly, obtaining the specific model of earth pressure by using Least Squares Support Vector Machine (LS-SVM) method combined with the construction-site data, and using six kinds of kernel function to construct the earth pressure model. With the introduction of RMSE(Root Mean Square Error) and MAPE(Mean Absolute Percent Error), then estimating the precision of prediction of the constructed model, and get the conclusion that the constructed model with a quadratic polynomial kernel function has the optimal precision of prediction. At last, verifying the validity of the mathematical model by simulation experiments, and comparing the estimates capacity of LS-SVM model and BP Neural Network model with MAPE as an estimated standard. The simulation represents that the LS-SVM model gets an excellent predictive ability and generalization ability.

【关键词】 土压平衡盾构LS-SVMBP土压模型
【Key words】 EPBShieldLS-SVMBPEarth pressure model
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