摘要
针对煤矿机械关键零部件超声检测时受到煤矿现场非线性、非平稳噪声干扰的问题,研究了超声信号的自适应去噪方法,将超声信号分解成独立的IMF分量,并得到各IMF分量的频谱,选择与探头中心频率相近的各IMF进行重构,提高了信噪比。
In the ultrasonic nondestructive test of coal machinery, the ultrasonic signal is disturbed by electronic noise, structure noise and other nonlinear and non-stationary noise. A new noise filtering method based on empirical mode decomposition （EMD） is proposed. The original signal is decomposed into many intrinsic mode function components（IMFs）, and frequency spectrum of each IMF component is plotted. IMFs which frequency are close to the probe center frequency are choosed to reconstruct adaptivity. Experimental results show that this method can greatly improves the signal-to-noise ratio.
出处
《煤炭技术》
CAS
北大核心
2016年第9期269-270,共2页
Coal Technology
基金
国家自然科学基金项目(51074121)
中国博士后科学基金项目(2015M572653XB)
陕西省教育厅专项科学研究计划项目(15JK1455)
长安大学高速公路施工机械陕西省重点实验室开放基金项目(310825161124)
西安科技大学博士启动金项目(2014QDJ003)和培育基金项目(201332)
关键词
煤矿机械
经验模式分解
超声检测
频谱
coal mine machinery
empirical mode decomposition
ultrasonic testing
frequency spectrum
