基于磨损在线检测的全断面掘进机刀具寿命预测研究

In tunnel construction process using full face tunnel boring machine, tool cost makes a large proportion in construction costs, and the non-normal replacement of cutter also leads to the delay of construction period. So, cutter life prediction has always been one of the key and difficult techniques in tunnel construction process using tunnel boring machine. In this project，the dynamic behavior of the tunnel boring machine cutter wear is explored and analyzed, the law between cutter wear's state and many factors like operating parameters, the nature of the job object, the operating environment is studied. Using the energy spectrum based on modern signal processing method the relationship between the tunneling parameters and cutter wear is studied.The embedded system and nondestructive testing technology are used, and the online detection of cutter wear condition is realized; The cutter wear condition, including wear cumulant and wear rate, can provide technical support for the on-condition replacement of the cutter; Using orthogonal test method the various factors that affect the cutter wear is analyzed in sensitivity.Based on real-time detection of cutter wear, the prediction rule of cutter life is studied based on statistical regression analysis, the analytical method of the cutter life prediction is discussed, all these provide a theoretical basis for tunnel boring machine construction cost forecast; At same time, the experimental data is provided for cutter's life match, and the theoretical basis is provided for cutter layout design.

刀具寿命预测一直是盾构和TBM掘进过程中亟待解决的难点之一。在全断面掘进机施工过程中刀具成本占施工成本的比例较大，针对刀具的非正常更换影响施工工期和施工成本的技术难题，对刀具磨损在线检测及其寿命预测进行研究。探索并分析掘进机刀具磨损的动力学行为，研究刀具磨损状态与作业参数、作业对象的性质、作业环境等诸多因素之间的关联性与规律。利用基于现代信号处理方法的能量谱研究掘进参数信号与刀具磨损之间的关系；利用嵌入式系统和无损检测技术，实现掘进机刀具磨损的在线监测；研究刀具磨损状态（包括累积量和速率），为"视情换刀"提供技术支撑。利用正交试验法对影响刀具磨损的关键因素进行敏感度分析。基于实时检测的刀具磨损量记录，利用统计回归分析研究刀具掘进寿命的预测规律，探讨刀具寿命预测的解析方法，为掘进机施工成本预测提供理论依据；同时，为刀具的"寿命匹配"再设计提供实验数据，为刀具布局设计提供理论依据。

本项目围绕全断面掘进机的刀具磨损在线检测以及寿命预测的关键技术开展了研究，针对掘进机刀具磨损在线检测方法、掘进机刀具的磨损规律及刀具寿命预测、掘进机刀具的选型与布局优化开展了研究。. 从间接检测和直接检测两个方面研究盾构刀具的磨损。间接方法利用基于现代信号处理方法的能量谱研究掘进参数信号与刀具磨损之间的规律。直接方法用电涡流无损检测技术对盾构机滚刀磨损进行在线检测，通过对刀具磨损的实时测量及时准确掌握刀具的磨损状态为“视情换刀”提供技术支持。. 分析研究盾构刀具的磨损规律，选用正交试验的方法处理掘进数据，最终得到盾构刀具的磨损规律。利用ANSYS瞬态动力学仿真的方法分析滚刀在冲击载荷作用下的振动响应，以研究刀具磨损的机理；基于自适应神经网络模糊系统进行了刀具磨损预测，并基于现场数据回归分析进行了刀具寿命预测。. 基于PSO-BP混合智能算法(粒子群算法优化BP神经网络)建立地质条件、盾构机类型、刀盘类型以及刀具之间的关系模型，并依据搜集到的实例及盾构施工过程中的换刀记录对模型进行训练，训练好的模型可实现盾构刀具的智能推荐。针对复合型土压平衡盾构刀盘的特点，研究了切刀及滚刀的布置规律，并对滚刀和切刀进行了布置优化。在满足刀盘几何要求和力学平衡约束基础上，建立了满足多种约束条件的滚刀布置优化模型，并采用粒子群多目标优化算法对模型进行求解。从刀盘整体受力出发，并基于阿基米德螺旋线方法进行切刀布置。最后通过ANSYS Workbench有限元软件对布置结果进行仿真分析，验证了该方法布置刀具的合理性和有效性，表明优化后的方案更符合工程实际需要。