摘要
为了解决钻头在钻进过程中由于采集到的信息存在信噪比低和钻头与钻柱振动信号互相混叠而难以对钻头故障振动状态进行有效识别的问题。提出一种基于MIMU的FastICA算法来对钻头与钻柱振动数据进行处理分析,从而放大了钻头振动信号特征(正常、松动),提高了钻头振动信号的识别度。首先对经MIMU采集而来的原始数据进行误差分析和预处理,接着使用FastICA算法进行仿真实验,最后采用预处理后的松动状态下钻头与钻柱的振动信号进行实例实验验证。经验证,此方法有效放大了钻头的振动信号特征,有一定的实际意义。
In order to solve the problem that the drill bit has low signal-to-noise ratio and the vibration signal of the drill bit and the drill string overlap during the drilling process,it is difficult to effectively identify the fault vibration state of the drill bit.A FastMU algorithm based on MIMU is proposed to process and analyze the vibration data of the drill bit and the drill string,thereby amplifying the vibration signal characteristics of the drill bit (normal and loose) and improving the recognition degree of the vibration signal of the drill bit.Firstly,the error analysis and preprocessing of the original data collected by MIMU are carried out,and then the simulation experiment is carried out by using FastICA algorithm.Finally,the experimental results of the drill bit and the drill string vibration signal under different conditions (normal and loose) are preliminarily verified.It is verified that this algorithm effectively amplifies the vibration signal characteristics of the drill bit and improves the recognition degree of the drill fault vibration signal.
作者
杨金显
范耀辉
YANG Jin-xian;FAN Yao-hui(School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo,Henan 454003,China)
出处
《软件》
2019年第5期147-153,共7页
Software
基金
国家自然科学基金项目(U1404510,41672363,61440007)
河南省科技攻关项目(172102210289)
河南省创新型科技人才队伍建设工程(CXTD2016054)
河南省高校基本科研业务费专项资金(NSFRF1619)
河南理工大学杰出青年基金(J2017-5)
