Precursor characteristics of rock bursts in section coal pillars based on geoacoustic monitoring

Identifying precursor characteristics information before rock bursts occur is crucial for monitoring, early warning, and prevention. Taking Panel 3-1103 in a mine of the Xinjie Mining Area as an example, cyclic loading-unloading uniaxial compression acoustic emission (AE) tests on coal samples were conducted, and geosound monitoring data before the "11.27" rock burst case were analyzed. This revealed the temporal variation patterns of energy and ring-down count (frequency) in AE signals during cyclic loading-unloading tests. These patterns were comparatively analyzed with precursor geosound characteristics of rock bursts in high-stress wide-section coal pillars. Based on this, a precursor characteristic identification model for rock bursts was constructed using the Mann-Kendall trend test method and validated through engineering applications. The research shows that:① Both AE signals from cyclic loading tests on coal samples and pre-burst geosound monitoring results exhibited a "fluctuating growth" trend, with highly similar stage activity intensities and frequencies. Within the same cyclic stage, energy and ring-down count (frequency) showed an increase-decrease pattern. Across different stages, peak values of energy and ring-down count (frequency) in later stages were higher than those in earlier stages.② Analysis of minute-level, hourly-level, and shift-level energy and deviation values before the "11.27" rock burst indicated that shift energy and deviation values exhibited distinct precursor characteristics.③ The precursor identification model for rock bursts in high-stress wide-section coal pillars, constructed via the Mann-Kendall trend test method, was applied to the "11.27" case, demonstrating its capability to detect precursor information before rock bursts.④ Validation using geosound data from the "6.10", "6.14", and "8.26" rock burst events achieved early warnings 8 h–32 h in advance. This model effectively identifies precursor characteristics of rock bursts in high-stress wide-section coal pillars, providing a reference for early warning of similar events.