Abstract:  To address the challenge of accurately perceiving surrounding rock parameters at the tunnel face bored by a tunnel boring machine(TBM), a case study is conducted on a water supply project in Northwest China, and a TBM mainframe vibration monitoring system is established to analyze the mainframe vibration signals under various rock conditions. The impact of TBM selfvibration is mitigated through the smooth processing of spectral curves using the SavitzkyGolay algorithm. The distribution patterns of vibration peak, extreme mean value, average amplitude, and root mean square value across different rock conditions are statistically analyzed. Additionally, mapping relations among vibration characteristic parameters, uniaxial compressive strength of rock mass, and rock integrity coefficients are established using eight mathematical models. Key findings include (1) the selfvibration frequency of the TBM mainframe is approximately 40 Hz; (2) the mean values of vibration peak, extreme mean value, average amplitude, and root mean square value diminish as the quality of surrounding rock deteriorates, but increase linearly with the uniaxial compressive strength and integrity coefficient of the rock mass; (3) These relationships offer valuable insights for developing rock sensing technologies based on mainframe vibration characteristics.

Key words: open tunnel boring machine, mainframe vibration, monitoring system, rock strength, rock mass integrity coefficient, tunnel, surrounding rock parameters