CAJ | 학술논문

从传感器中采集到的信号即使经过了模拟滤波，但是其通过数据采集系统后仍然会含有随机噪声。然而，这些随机噪声会限制传感器的分辨率和影响系统的动态范围。针对这一问题，利用HHT算法的经验模态分解对从基于压电陶瓷驱动的微纳米传感器中采集到的数字信号进行数字滤波，进而对采集到的微弱信号进行进一步处理，以提高微纳米传感器在稳态输出时信号的信噪比从而提高传感器的性能。主要采用两种方法：一种方法是滤掉经过模态分解后信号中的最高频噪声，另一种方法是滤掉经过模态分解后信号中的前两阶噪声。最后对比实验结果证实了此算法的有效性，其能够有效的改善传感器的线性度。
종전감기중채집도적신호즉사경과료모의려파，단시기통과수거채집계통후잉연회함유수궤조성。연이，저사수궤조성회한제전감기적분변솔화영향계통적동태범위。침대저일문제，이용HHT산법적경험모태분해대종기우압전도자구동적미납미전감기중채집도적수자신호진행수자려파，진이대채집도적미약신호진행진일보처리，이제고미납미전감기재은태수출시신호적신조비종이제고전감기적성능。주요채용량충방법：일충방법시려도경과모태분해후신호중적최고빈조성，령일충방법시려도경과모태분해후신호중적전량계조성。최후대비실험결과증실료차산법적유효성，기능구유효적개선전감기적선성도。
A relatively new algorithm called Hilbert-Huang transform( HHT) is proposed. It utilizes empirical mode decomposition(EMD)to filter noise in a nanoscale displacement sensor,which is actuated by PZT. However,even after the pre-filtering,the random noise still cannot be fully eliminated. The noise limits the resolution of the sensor and affects the dynamic range of the whole system. So the signal need to be further processed to increase the Signal to Noise Ratio( SNR) and then improve the performance of the sensor. Two kinds of methods are attempted. One is filtering the highest frequency noise of intrinsic mode functions( IMFs) after EMD. And the other one is to just filter the first and second IMFs. Finally,experiments are conducted to verify the effectiveness of the HHT algorithm and the improvement of sensor's linearity.