基于煤矸信号特征的自动化放煤技术研究

Research on Automatic Caving Technology Based on Gangue Signal Characteristics

为了有效判别煤矸信号特征的差异,利用小波变换法中Haar小波系、VisuShrink法对煤矸下落过程中振动信号和声音信号进行了重构,根据重构后的特征信号,重新定义了煤炭和矸石在下落过程中信号特征,并在现场中得到了成功应用,为精确自动化放煤技术提供了重要的基础。

In order to effectively distinguish the differences in the characteristics of coal gangue signals,the author uses the Haar wavelet series and VisuShrink method in wavelet transform to reconstruct the vibration and sound signals during the coal gangue falling process and redefines the signal characteristics of coal and gangue during the falling process based on the reconstructed feature signals,which is successfully applied in the field and provides an important foundation for precise automatic caving technology.