Abstract: in orderto improve the falure diagnosis eficiency and accuracy of the cuting unit in the roadheader:the paper provided the falure dlagnosis method ofthe cutting unt in the roatheader based on the BP neural network of the mui sensor information and the falure diagnosis was conduced on the cutng unit of the EB.160 nmode roadheader.The method combined with the acaptive leamning rate method and the aditional momentum method was applied to soive the slow convarcence rate of the previous algorithm and the local mininmum problem existed in the BP neural network.The muti sensors were appied ocollect the state sgrals of the cuting .nit in the roacheader.Vith the data analysis conducted on the status signal ofthe cuting unti n the roadheade,muiti roups of the feauwre vectors werecalected an te feature database of the cutting unit in the roadheader was established.The BP neural network was applied to the training of the sample data.The case analysisresut.showed that the method could effectivlly monitor and diagnose the heath status of the cutting unit in the roadheader and the diagnosis precision an accuracy were hgh.