Research on coal-rock recognition based on sound signal analysis

摘要：

　　The recognition of the cutting state of shearer is the key technology to realize variable speed cutting and mining automation.It is of great significance for improving shearer reliability,ensuring personal safety and improving coal quality.This paper proposed a coal-rock recognition method based on sound signal analysis.The original sound signal produced during the cutting process of shearer is decomposed by variational mode decomposition(VMD),and the obtained IMFs can construct a signal matrix.The signal matrix is processed by singular value decomposition(SVD),and a series of singular values can be obtained and defined as the signal features.Finally,the coal-rock recognition is realized by extreme learning machine(ELM)based on the extracted signal features.The experiment results show that the overall recognition accuracy is 91.7%under the actual cutting condition,which verifies the effectiveness of the proposed method in coal-rock recognition,and lays a theoretical foundation for the automation and intellectualization of shearer mining.

作者: Xihui Chen Zenan Yang Gang Cheng

作者单位: College of Mechanical and Electrical Engineering,Hohai University,Changzhou,213022,China;School of M College of Mechanical and Electrical Engineering,Hohai University,Changzhou,213022,China School of Mechatronic Engineering,China University of Mining and Technology,Xuzhou,221116,China

会议类型: 国际会议

会议名称: 2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)(2018第二届电子信息技术与计算机工程国际会议)(EITCE2018)

会议地点: 上海

会议语种:英文

页码: 1-5

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）