An improved signal filtering strategy based on EMD algorithm for ultrahigh precision grating encoder

Abstract

The signal filtering of the grating encoder is of great significance to the measurement accuracy, aiming at eliminating the background noise potentially from the temperature changes, airflow fluctuations, and mechanical vibrations. Compared with the traditional time-frequency analysis methods, including wavelet transform, fast Fourier transform (FFT), and time Fourier transforms (TFT), the empirical mode decomposition (EMD) algorithm owing to no basis functions and high adaptability, is widely applied for signal decomposition. Here, we extended the EMD algorithm for the background-noise-based signal filtering in a grating encoder, with the experimental parameters of 5 μm/s moving speed and ∼19 mm stroke. Simultaneously, a laser interferometer, as a reference, was additionally assembled to calibrate the measurement results of the grating encoder. The measurement signal was collected by NI acquisition card with a 1000 Hz sample rate and processed by EMD algorithm. Here, EMD decomposed the signal into multiple intrinsic mode functions (IMFs), which were reconstructed by removing the noise and DC components according to the correlation coefficients. Compared with the measurement results of the laser interferometer, the measurement displacement with a 6.2 μm error was solved by the phase correction and arctangent calculation from the reconstructed signals. Finally, our proposed signal-filtering approach based on the EMD algorithm exhibits a stable, accurate, and real-time calculation performance applicable for the grating encoder with ultra-high precision positioning.