DOI: 10.57760/sciencedb.cssj.00012
title: Coal mine rock burst acoustic emission (AE) signal dataset
title: 煤矿冲击地压声发射信号（AE）数据集

description: Coal is the main energy source and an important industrial raw material in China. However, as the depth of mining increases, the in-situ stress grows, and the risk of underground coal and rock dynamic disasters becomes greater and greater, seriously affecting the safe and efficient mining of coal mines. Among various deep coal and rock dynamic disaster accidents, rock burst has become one of the most significant disasters threatening the safety of coal mine production in China. Rock burst accidents can cause severe casualties and property losses. In recent years, researchers have conducted extensive and in-depth studies and adopted many prevention and control measures, leading to a continuous and steady improvement in the safety situation of Chinese coal mines. Nevertheless, rock burst accidents still occur from time to time, and the safety situation in coal mines remains severe. The monitoring and early warning of rock burst and its effective prevention and control remain urgent scientific and technological issues in coal mine safety production. During the deep coal mine mining process, acoustic emission (AE) signals can be monitored. The AE sensor collects one data every 30 seconds, and the current risk of rock burst in the working face or roadway can be determined by analyzing the trend of these data. The dataset consists of two sub-datasets, as shown in Figure 1: Dataset 1 covers partial AE signal data from January 9, 2019 to September 8, 2020, with each sample labeled as either normal operation data or interference signal data. Dataset 2 is composed of three non-consecutive time periods (November 1, 2021 to January 15, 2022, April 1, 2022 to May 30, 2022, and October 10, 2022 to November 10, 2022), and contains a total of 168,558 AE signal samples without labeled data types.
description: Coal is the main energy source and an important industrial raw material in China. However, as the depth of mining increases, the in-situ stress grows, and the risk of underground coal and rock dynamic disasters becomes greater and greater, seriously affecting the safe and efficient mining of coal mines. Among various deep coal and rock dynamic disaster accidents, rock burst has become one of the most significant disasters threatening the safety of coal mine production in China. Rock burst accidents can cause severe casualties and property losses. In recent years, researchers have conducted extensive and in-depth studies and adopted many prevention and control measures, leading to a continuous and steady improvement in the safety situation of Chinese coal mines. Nevertheless, rock burst accidents still occur from time to time, and the safety situation in coal mines remains severe. The monitoring and early warning of rock burst and its effective prevention and control remain urgent scientific and technological issues in coal mine safety production. During the deep coal mine mining process, acoustic emission (AE) signals can be monitored. The AE sensor collects one data every 30 seconds, and the current risk of rock burst in the working face or roadway can be determined by analyzing the trend of these data. The dataset consists of two sub-datasets, as shown in Figure 1: Dataset 1 covers partial AE signal data from January 9, 2019 to September 8, 2020, with each sample labeled as either normal operation data or interference signal data. Dataset 2 is composed of three non-consecutive time periods (November 1, 2021 to January 15, 2022, April 1, 2022 to May 30, 2022, and October 10, 2022 to November 10, 2022), and contains a total of 168,558 AE signal samples without labeled data types.