Abstract: The surface potential signals induced by the deformation and failure of coal and rock contain key information on damage evolution. It has been widely studied in the field of coal and rock dynamic disaster monitoring. However, most of these studies focus on the fluctuation features of potential time series signals in a single time dimension. There is a lack of in-depth research on the nonlinear and multiscale feature changes of the time series signals. To solve this problem, a monitoring system for the potential of coal and rock failure is built, and the potential time series signals of raw coal and gabbro samples are synchronously tested. Through the multiscale multifractal analysis (MMA) method, the nonlinear features of potential signals at multiple scales are studied in depth. The singularity index, singularity dimension, local Hurst index and other parameters of the potential time series signals are obtained. The Hurst surface is quantified by the L2 norm. The experimental results show that the overall potential signals of raw coal and gabbro show multiscale multifractal features, and the potential multifractal maps before and after crack initiation show some differences. Compared with gabbro, the positive and negative trends of the singularity index difference Δα of the potential signals of the coal samples at different positions in the pre-loading and post-loading phases show different features. It indicates a stronger non-linear evolution of the coal samples. The L2 norm of the local Hurst index at multiple scales better reflects the long-range correlation between different channel potential signals of the sample. It can quantify the nonlinear evolution features of the sample time series signals, thereby achieving the prediction of coal rock instability and failure.