(1.School of Mechanics and Engineering,Liaoning Technical University,Fuxin ,China; 2.School of Physics,Liaoning University,Shenyang ,China)

In order to explore the influence of burst tendency of coal samples by charge induction method,the burst tendency,physical and mechanical characteristics and charge signal law of coal samples were studied by laboratory test.The distribution characteristics of whole process of coal samples damage and the quantitative relation between the impact tendency indexes and the charge related parameters were analyzed emphatically.The results showed that with the increase of impact tendency,the failure mode of coal samples gradually changes from fracture type to conjugated shearing type and then to single shearing type.The generation of charge signals of ruptured coal samples has good consistency with the stress mutation.The charge signals of coal samples with strong impact are mainly concentrated in the stage of enhanced damage before the stress peak,and the charge precursory information of the coal sample is unstable and the charge precursor information is obvious.The charge signals of coal samples with weak impact are mainly concentrated in the stage of enhanced damage and post peak failure.The weak impact propensity coal sample charge signal are mainly concentrated in the failure stage after the stress peak,and the charge precursory information is no longer obvious.The stronger the impact tendency of coal samples,the less accumulated charge after stress peak,but the greater the charge change rate w after stress peak.The impact energy index KE has a power increasing function relationship with the charge change rate after stress peak,and the elastic energy index WET has a linear increasing function relationship with the post-stress peak charge change rate.Therefore,the degree of impact tendency of the coal body can be preliminarily judged by the overall distribution law of the charge signal and the magnitude of the charge change rate after the stress peak.

国家重点研发计划资助项目（2017YFC0804208，2016YFC0801403-4）；国家自然科学基金资助项目（51774164）