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Geomechanics and Engineering Volume 35, Number 6, December25 2023 , pages 647-663 DOI: https://doi.org/10.12989/gae.2023.35.6.647 |
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Prediction of TBM disc cutter wear based on field parameters regression analysis |
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Lei She, Yan-long Li, Chao Wang, She-rong Zhang, Sun-wen He,
Wen-jie Liu, Min Du and Shi-min Li
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| Abstract | ||
| The investigation of the disc cutter wear prediction has an important guiding role in TBM equipment selection, project planning, and cost forecasting, especially when tunneling in a long-distance rock formations with high strength and high abrasivity. In this study, a comprehensive database of disc cutter wear data, geological properties, and tunneling parameters is obtained from a 1326 m excavated metro tunnel project in leptynite in Shenzhen, China. The failure forms and wear consumption of disc cutters on site are analyzed with emphasis. The results showed that 81% of disc cutters fail due to uniform wear, and other cutters are replaced owing to abnormal wear, especially flat wear of the cutter rings. In addition, it is found that there is a reasonable direct proportional relationship between the uniform wear rate (WR) and the installation radius (R), and the coefficient depends on geological characteristics and tunneling parameters. Thus, a preliminary prediction formula of the uniform wear rate, based on the installation radius of the cutterhead, was established. The correlation between some important geological properties (KV and UCS) along with some tunneling parameters (Fn and p) and wear rate was discussed using regression analysis methods, and several prediction models for uniform wear rate were developed. Compared with a single variable, the multivariable model shows better prediction ability, and 89% of WR can be accurately estimated. The prediction model has reliability and provides a practical tool for wear prediction of disc cutter under similar hard rock projects with similar geological conditions. | ||
| Key Words | ||
| disc cutter wear; failure analysis; geological properties; prediction model; tunneling parameters | ||
| Address | ||
| Lei She and Yan-long Li: State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi'an University of Technology, No. 5 South Jinhua Road, Xi'an 710048, China Chao Wang, She-rong Zhang,Wen-jie Liu and Min Du: School of Civil Engineering, Tianjin University, No. 135 Yaguan Road, Tianjin 300072, China Sun-wen He and Shi-min Li: Power China Co., Ltd., No. 22 West Chegongzhuang Road, Beijing 100048, China | ||