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Identifying precursor information to rock failure is key to rock dynamic disaster warning. To solve the problem that a single in-situ monitoring method cannot accurately identify the precursors to rock failure, this paper combined a digital image correlation method, thermal infrared radiation and acoustic emission technology to conduct a multi-physical field joint monitoring experiment of granite under three-point bending. The information about strain, thermal infrared and acoustic emission of the rock brittle failure process could be obtained, and the variations in multi-physical field indices of the rock brittle failure process were analysed. Based on the theory of critical slowing-down, the study of the multi-physical field effects of critical slowing-down characteristics in the rock failure process, and further exploration of the precursor characteristics of the brittle failure of rock were undertaken. The results indicate that the strain, infrared, and acoustic emission parameters show sudden changes during brittle failure of granite. The lag step size has little effect on the variance of changes in multi-physical field parameters and exerts a similar influence on the changes in the autocorrelation coefficient curve. The degree of influence of the window length on the variance and autocorrelation coefficient curves of multi-physical field parameters is as follows: infrared field > strain field > acoustic emission field. Compared with the autocorrelation coefficient, the variance parameter is more universal and is better when the critical slowing-down theory is used to investigate the characteristics of multi-physical fields. The four parameters of the strain field variance, infrared field variance, the variance and autocorrelation coefficient for acoustic emission field increase sharply before fracture, representing precursor information to the brittle failure of granite. The four parameters can be used as disaster warning indicators in rock. Multi-mode joint monitoring and a comprehensive analysis of multi-physical information are beneficial to accurately determine the precursor points of rock failure disaster. [ABSTRACT FROM AUTHOR]