摘要
Disc-cutters play a crucial role in the penetration process during construction using a tunnel boring machine(TBM).Their wear status has a significant impact on working efficiency and costs that accounts for a large part of the budget.Discovering the wear pattern and characteristics of disc-cutters could provide a valuable guide for field maintenance and cutter replacement work.It also provides insight into the wear mechanism of cutters at different positions for optimizing the disc-cutter arrangement design.In this study,the cutter wears data of 34 disc-cutters over 643 days in the Chaoer River to Xiliao River water diversion tunnel was collected.The dataset contains 21862 manual readings measured from 1079 disc-cutters replaced in this project.The raw data from the hard copy version was transformed into a digital twin database by eliminating abnormal data,filling in empty values,and performing linear interpolations.It has been found that the cutters can pass statistical testing for an exponential probability distribution function with respect to the wear rate(w).The regression ratios of R2are essentially greater than 0.8.These findings would help estimate the future service life of a currently working cutter,which means significant savings for the costly disccutters.The application of exponential distribution has the advantage of only one shape parameter,λ,whose reciprocal represents both the statistical mean and standard deviation of the wear rates.It is simple and practically amenable.A preliminary study was carried out to simulate the wear process between two neighboring cutters for drafting a replacement plan for disc-cutters by the Monte Carlo method.The prediction results agreed reasonably well with the measured information.
基金
supported by the National Natural Science Foundation of China (Grant Nos.41831281,42220104007 and 52079150)
the Basic Research Project of the China Institute of Water Resources and Hydropower Research (Grant No.GE0145B022021)
the Core Research Project of Power Construction Corporation of China (Grant No.DJ-HXGG-2021-01)。