To explore the development mechanism of cracks in the process of rock failure, triaxial compression tests with simultaneous acoustic emission monitoring were performed on granite specimens using the MTS rock mechanics test system. The frequency-domain information of the acoustic emission signal was obtained by the fast Fourier transform. The Gutenberg–Richter law was used to calculate the acoustic emission signals and obtain the b-value dynamic curve in the loading process. Combined with the stiffness curve of granite specimens and acoustic emission signal in the time domain and frequency domain, the crack development characteristics in different stages were analyzed. The results showed that the acoustic emission signals of granite samples under triaxial compression can be divided into four stages: quiet period 1, active stage 1, quiet period 2, and active stage 2. b-value attained its maximum value in the active phase 2 when it is close to the sample loss, and then drops rapidly, which means the propagation of cracks and the formation of large cracks. The acoustic emission signal’s dominant frequency was not more than 500 kHz, mostly concentrated in the medium-frequency band (100–200 kHz), which accounted for more than 80%. The proportion of signals in each frequency band can reflect the distribution of the three kinds of cracks, while the change in low-frequency signals can reflect the breakthrough of microcracks and the formation time of macrocracks in granite samples. By fully analyzing the characteristics of acoustic emission signals in the time domain and frequency domain, the time and conditions of producing large cracks can be determined accurately and efficiently.

为了探索岩石破裂过程中裂纹的发展机理，使用MTS岩石力学测试系统对花岗岩标本进行了同时声发射监测的三轴压缩测试。通过快速傅立叶变换获得声发射信号的频域信息。古登堡一里克特法被用于计算声发射信号，将获得的b值动态曲线在加载过程中。结合花岗岩试样的刚度曲线和时域和频域的声发射信号，分析了不同阶段的裂纹扩展特征。结果表明，花岗岩样品在三轴压缩下的声发射信号可分为四个阶段：静止期1，活动期1，静止期2和活动期2。b当活性值接近样品损失时，它在活性相2中达到最大值，然后迅速下降，这意味着裂纹的传播和大裂纹的形成。声发射信号的主要频率不超过500 kHz，主要集中在中频带（100–200 kHz）中，占80％以上。每个频带中信号的比例可以反映三种裂缝的分布，而低频信号的变化可以反映花岗岩样品中微裂纹的突破和宏观裂纹的形成时间。通过在时域和频域中充分分析声发射信号的特性，可以准确，有效地确定产生大裂纹的时间和条件。