Sun Zhihong, Wu Yuanke, Xiao Hao, Hu Panpan, Weng Zhenyong, Xu Shunhai, Sun Wei
School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China.
China Railway Engineering Equipment Group Co., Ltd., Zhengzhou 450016, China.
Sensors (Basel). 2025 Jul 31;25(15):4715. doi: 10.3390/s25154715.
The main bearing of a tunnel boring machine (TBM) is a critical component of the main driving system that enables continuous excavation, and its performance is crucial for ensuring the safe operation of the TBM. Currently, there are few testing technologies for TBM main bearings, and a comprehensive testing and evaluation system has yet to be established. This study presents an experimental investigation using a self-developed, full-scale TBM main bearing test bench. Based on a representative load spectrum, both operational condition tests and life cycle tests are conducted alternately, during which the signals of the main bearing are collected. The observed vibration signals are weak, with significant vibration attenuation occurring in the large structural components. Compared with the test bearing, which reaches a vibration amplitude of 10 g in scale tests, the difference is several orders of magnitude smaller. To effectively utilize the selected evaluation indicators, the entropy weight method is employed to assign weights to the indicators, and a comprehensive analysis is conducted using grey relational analysis. This strategy results in the development of a comprehensive evaluation method based on entropy weighting and grey relational analysis. The main bearing performance is evaluated under various working conditions and the same working conditions in different time periods. The results show that the greater the bearing load, the lower the comprehensive evaluation coefficient of bearing performance. A multistage evaluation method is adopted to evaluate the performance and condition of the main bearing across multiple working scenarios. With the increase of the test duration, the bearing performance exhibits gradual degradation, aligning with the expected outcomes. The findings demonstrate that the proposed performance evaluation method can effectively and accurately evaluate the performance of TBM main bearings, providing theoretical and technical support for the safe operation of TBMs.
隧道掘进机（TBM）的主轴承是主驱动系统的关键部件，它能实现连续挖掘，其性能对于确保TBM的安全运行至关重要。目前，针对TBM主轴承的测试技术较少，尚未建立全面的测试与评估体系。本研究采用自行研制的全尺寸TBM主轴承试验台进行了实验研究。基于代表性载荷谱，交替进行工况试验和寿命周期试验，在此期间采集主轴承的信号。观察到的振动信号很微弱，在大型结构部件中存在明显的振动衰减。与在规模试验中振动幅值达到10g的试验轴承相比，差异小几个数量级。为有效利用选定的评估指标，采用熵权法为指标赋权，并运用灰色关联分析进行综合分析。该策略形成了一种基于熵权和灰色关联分析的综合评估方法。在不同工况以及同一工况的不同时间段对主轴承性能进行评估。结果表明，轴承载荷越大，轴承性能综合评估系数越低。采用多级评估方法对主轴承在多种工作场景下的性能和状态进行评估。随着试验持续时间的增加，轴承性能呈现逐渐退化的趋势，与预期结果相符。研究结果表明，所提出的性能评估方法能够有效、准确地评估TBM主轴承的性能，为TBM的安全运行提供理论和技术支持。
