【作者】 上官子昌；

【导师】 栾茂田； 李守巨；

【作者基本信息】 大连理工大学 ， 岩土工程， 2011， 博士

【摘要】 盾构机在掘进过程中,由刀盘切割破碎的渣土从刀盘开口进入刀盘后面与隔板之间的密封压力舱,然后经改性后由螺旋输送机排出密封舱内的改性渣土。螺旋输送机的转速和排土率由盾构机操作工或者计算机软件控制,以使得螺旋输送机排出的土体与从刀盘进入的土体相平衡,其目的是控制掘进工作面的土压力,进而有效控制盾构机掘进过程中的地表变形。在盾构机掘进过程中,掘进工作面的稳定性是通过密封舱的支护压力得以实现的,掘进工作面支护压力过大会造成地表隆起,而压力过小,容易导致地表沉陷甚至坍塌。目前,盾构机密封舱压力控制参考值大多凭经验人为设定,控制方法大多由操作者手工实时调整螺旋输送机转速控制密封舱压力,盾构机隧道掘进过程中普遍遇到的关键问题包括：1)密封舱压力优化设置问题：2)盾构机合理推力优化问题；3)盾构机密封舱压力分布数值模拟问题；4)盾构机密封舱压力控制机理模型问题；5)控制机理模型参数实时辨识问题；6)优化控制策略和自动控制问题。针对这些亟待解决的问题,论文开展了以下几个方面的研究工作：1)基于土力学的主动土压力和被动土压力理论,分析了掘进工作面稳定性机理,采用解析方法研究了盾构机与土体之间的相互作用,确定了合理的掘进工作面压力范围,提出了优化盾构机推力的方法。经过与现场的观测数据相对比,验证了所提出的优化盾构机推力方法的有效性。研究了刀盘开口率变化对密封舱压力传递系数的影响,建立了压力传递系数与刀盘开口率之间的映射关系。密封舱可观测压力与掘进工作面土压力之间关系的确定为优化设置密封舱压力提供了理论依据。根据优化确定的掘进工作面土压力以及渣土的Duncan-Chang非线性本构模型和反演的模型参数,数值模拟了盾构机密封舱土压力分布特性,数值模拟结果与现场观测的密封舱隔板压力分布进行对比,数值模拟值与观测值基本一致。2)为了模拟盾构机密封舱内的压力分布特性,需要反演确定改性后渣土的力学模型和模型参数。参数识别反问题通过对定义的目标函数进行极小化求解。参数反演的目标函数定义为观测的应变矢量与模型计算的应变矢量残差平方和,而模型计算的应变矢量是被估计参数的函数。常规的基于梯度搜索的优化方法包括单纯性法、阻尼最小二乘法和高斯一牛顿法等,但遗憾的是,基于梯度搜索的优化方法存在的固有缺陷在于容易陷入局部极小值；而研究表明,由于观测误差和模型误差的存在,参数识别反问题存在多个极小值。为了解决这个问题,建立了基于浮点编码遗传算法的参数反演方法,该方法将简单遗传算法与梯度搜索优化算法相结合,用以提高反演精度和速度。将从沈阳某地铁隧道施工现场采集土样加工成三轴压缩试验试件,实验得到不同维压条件下的应力一应变曲线,为本构模型参数反演提供实验数据。根据参数反演得到的渣土本构模型参数,预测三轴压缩试验变形曲线。研究结果表明,预测值与观测值吻合较好,所提出的参数反演方法的有效性和精度得到了验证。3)以密封舱渣土的Duncan-Chang非线性弹性本构模型为基础,建立了盾构机密封舱土压力与盾构机推进速度和螺旋输送机转数的映射关系,提出了单独调整螺旋输送机转速的盾构机密封舱土压力优化控制模型。将密封舱隔板压力的变化分解为两部分,即密封舱渣土质量改变和掘进工作面土压力改变引起的密封舱隔板压力变化。建立了密封舱渣土质量改变与盾构机的推进速度和螺旋输送机转速之间的关系、以及掘进工作面土压力改变与盾构机推力之间的关系。考虑到盾构机与土体之间的耦合作用,建立了新的密封舱压力控制机理模型,该模型可以通过同时控制螺旋输送机转速、盾构机推进速度和推力,快速实现密封舱压力平衡和自动控制。4)基于系统辨识原理,建立了密封舱压力控制模型参数在线辨识方法。这些需要辨识的参数很难在实验室或者通过其他方法在现场直接确定,参数包括改性后渣土的变形模量、螺旋输送机的排土效率和土体的松散系数等。根据盾构机掘进过程中的观测信息,基于观测到动力系统的输入(螺旋输送机转速)和输出(密封舱观测点压力),采用优化方法识别出动力系统中模型的参数。考虑到观测噪音的存在,随机模拟了带有观测噪音的系统参数辨识问题。提出了基于BP神经网络的盾构机密封舱压力非线性和时变系统的辨识模型和方法,该方法能够实时对盾构机密封舱压力系统进行在线辨识,具有较高的辨识精度。数值模拟结果表明,即使存在随机观测噪音,辨识方法仍然能够比较准确辨识出控制模型的参数。5)将非线性动力系统模型参数辨识与优化控制集合为一体,建立了基于神经网络的盾构机密封舱压力控制策略和方法。建立基于实时观测信息的密封舱压力控制模型中参数辨识方法,解决盾构机密封舱压力控制的非线性、随机性、时滞性和时变性等问题,提高了控制系统的精确性、抗干扰性和鲁棒性。数值仿真结果表明,该方法对于盾构机密封舱压力时变性和非线性系统控制,具有良好的稳定性和控制效率,所提出新控制模型的有效性和精确性通过数值仿真进行了验证。6)盾构机实验平台验证了盾构机密封舱压力控制模型、控制模型参数在线辨识方法和密封舱压力自动控制策略的有效性。实验平台可以观测的数据包括,盾构机密封舱压力、螺旋输送机的转速和盾构机的推力等。根据实验台观测的盾构机密封舱压力和螺旋输送机转速,首先辨识出控制机理模型参数。然后,根据辨识出的模型参数和预先设定的密封舱压力,实现了密封舱压力自动和实时控制。更多还原

【Abstract】 Earth pressure balance (EPB) shield tunnelling has successfully been adopted for urban tunnelling in recent years in very different ground conditions and at present it can be considered the most commonly used mechanized tunnelling technology, even challenging the role of the Slurry Shield both as far as machine size and the geomechanical fields of applicability are concerned. The screw conveyor’s speed and discharge rate is controlled by the operator or computer software and is used to control the pressure at the working face and match the muck discharge rate to the advance rate of the EPBM, and effectively control ground deformation induced from shield tunneling. The control of face support is a major issue in EPB shield tunneling. Continuous support of the tunneling face must be provided by the excavated soil itself, which should completely fill the working chamber. The required support pressure at the tunneling face will be achieved through shoving the shield forward and regulation of the screw conveyor’s rotation rate. The support pressure has to balance the earth pressure and the water pressure. The supporting pressure on tunneling face must be carefully determined and avoid both the collapse (active failure) and the blow-out (passive failure) of the soil mass near the tunnel face. The collapse and the blow-out are induced from smaller and bigger supporting pressure, respectively. Nowadays, the reference pressure on pressure bulkhead is commonly determined by operator experiences. The operator continually adjusts screw conveyor’s speed to control earth pressure on tunneling face. The main problems occurred in shield tunneling include:1) How to optimally choose earth pressure on chamber bulkhead; 2) How to determine shield thrust force; 3) How to simulate earth pressure distribution in shield chamber; 4) Propose mechanism model of controlling earth pressure on chamber bulkhead; 5) How to estimate model parameters of control model; and 6) Present optimization and automatic control strategy for controlling earth pressure on chamber bulkhead. In order to deal with these problems, some investigations are performed:1) Based on Duncan-Chang nonlinear elastic constitutive model, the earth pressures on head chamber of shield machine are simulated. Model parameters of conditioned soils in head chamber of shield machine are determined based on tri-axial compression tests in laboratory. The loads acting on tunneling face are estimated according to static earth pressure principle. The soil-structure interaction in shield tunneling is investigated by analytical solution. The mechanism of working face stability is analyzed and the reasonable face earth pressure for EPB shield is deduced according to the active and passive earth pressure principles. The optimal thrust fore for EPB shield is proposed in different soil parameter and shield size cases. The comparison of the practical thrust forces of EPB shields with computed ones shows that the proposed computing procedure for optimal thrust fore for EPB shield can agree well with practical engineering examples. The effectiveness of the proposed computing procedure is validated. The variation of earth pressure on different section in head chamber of shield machine is depicted. Relationship between pressure transportation factor and openings rotating cutterhead of shield machine is proposed by using aggression analysis.2) The inverse problem of parameter identification is solved by minimizing an objective function of the least-squares type that contains the difference between observed and calculated strains. The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil. The calculated strains are determined by linear approach simplification. The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm. The numerical and experimental results for conditioned soil are compared. The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones. The effectiveness and accuracy of proposed parameter estimation approach are validated.3) Based on numerical simulation using finite element method, the reference model is proposed for controlling earth pressure of head chamber. The relationship between the strain and the accumulating amount of earth is proposed based on Duncan and Chang’s model. The relationship between the increment of earth pressure and the angular velocity of screw conveyor is presented. Based on nonlinear constitutive model of soil and mass conservation law, the differential equation of nonlinear discrete system is deduced by solely adjusting conveyor rotating speed. The earth pressure change in the chamber comes mainly from two parts, which conclude the change of mass quantity of conditioned soil in chamber and change of earth pressure in working face. The relationship between the change of mass quantity of conditioned soil in chamber and shield tunneling rate and conveyor rotating speed is proposed. The relationship between the change of earth pressure in chamber and shield thrust force is presented. Taking account of coupled reaction between shield machine and soils, a new control mechanism model for controlling earth pressure acting on headchamber is presented. The new control mechanism model can rapidly perform pressure balance for shield chamber and automatically control earth pressure according to preset reference pressure.4) Some parameters of control model should be determined by using system identification because these parameters can not be easily estimated in laboratory or in situ in shield tunneling. The main parameters of control model include deformation modulus of conditioned soils, conveyor discharge efficiency and loosing coefficient of soils. An estimation approach using least squares method is presented for identification of model parameters of pressure control in shield tunneling according to observed system input and output. The randomly observed noise is numerically simulated and mixed to simulated observation values of system responses. The numerical simulation shows that the state equation of pressure control system for shield tunneling is reasonable and proposed estimation approach is effectiveness even if the random observation noise exits. The identification procedure for nonlinear control system of shield machine tunneling is proposed by using neural network. Bp neural network is applied for an identifier to estimate model parameters of time varying control system. The numerical simulation shows that the identification procedure is effective for nonlinear and time varying control system in shield machine tunneling.5) By combining system identification with optimal control as an integral body, the control strategy and algorithm in shield tunneling are proposed, which are based on neural network identifier and controller. The identifier and controller can effectively perform these functions to nonlinear, random and time-varying dynamic system. The optimal procure is developed for controlling earth pressure acting on headchamber. The effectiveness and preciseness of the new model proposed are verified by numerical simulation results. The numerical simulation shows that the proposed control model is effective and stable for controlling earth pressure of shield machine by adjusting controlled variable.6) In order to validate the effectiveness of control mechanism model, parameter identification procedure and optimal control strategy, the model tests in laboratory are performed. The observed test data include earth pressure on chamber bulkhead, conveyor rotating speed, shield tunneling rate and thrust force. Based on observing data in test bed, control model parameters are first estimated. And then the earth pressure on chamber bulkhead is automatically controlled during next tunneling process based on preset reference pressure.更多还原