Design of Quadrature Lock-in Amplifier Based on LMS Time Delay Adaptive

• Published in: 2021 IEEE 15th International Conference on Electronic Measurement & Instruments (ICEMI) pp. 100 - 104
• Main Authors: Wang, Li, Wei, Zhikun, Xie, Hua, Qiu, Gen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 29.10.2021
• Subjects: Adaptation models; Delay effects; DQLIA; Estimation; Fluctuations; LMS adaptive time delay estimation; Magnetic sensors; Noise reduction; SNR; Time-frequency analysis
• DOI: 10.1109/ICEMI52946.2021.9679631

When the traditional Digital Quadrature Lock-in Amplifier(DQLIA) is used to detect the current signal of the Giant Magneto-Impedance (GMI) magnetic sensor online, the original current signal is mixed with strong noise after passing through the GMI magnetic sensor, resulting in large fluctuations in the output result and low accuracy. In order to reduce noise interference and improve the detection accuracy of GMI magnetic signals, this paper proposes a current signal noise reduction method combining Least Mean Square(LMS) adaptive time delay estimation and DQLIA. LMS adaptive time delay estimation is added to DQLIA, using the noise reduction characteristics of LMS adaptive time delay estimation, makes the noise superimposed on the frequency-locked signal further reduced. Improve the detection accuracy of the GMI current signal and reduce the output fluctuation rate. Through MATLAB/Simulink simulation, the results show that under the condition of input signal-to-noise ratio(SNR) of −7.01dB, the output volatility of the improved method proposed in this paper is reduced by 15.6% compared with the traditional method. Therefore, simulations and experiments have verified the rationality and effectiveness of the proposed method.