KEYWORDS: Field programmable gate arrays, Computer programming, Signal processing, Data conversion, Optical filters, Filtering (signal processing), Digital signal processing, Interfaces, Diffraction gratings, Logic
Compared with the four-phase optical structure, the grating encoder based on two-phase optical structure reduces the number of optical devices used in the system and makes the system more compact. Due to the high requirements for realtime and parallel processing of algorithm solution, the powerful parallel computing ability of Field Programmable Gate Array (FPGA) and customized hardware acceleration algorithm are needed to improve the real-time performance. In the previous research, the displacement signal generated by the grating encoder can be input into the FPGA through analog to digital converter (ADC) sampling, and then complete self-designed filter filtering, phase correction and displacement solution. In this paper, further, the ADC sampling rate adjustable interface is added to the FPGA, the global signal and the dc offset remove algorithm is added, and the displacement solution results in the form of fixed-point number are output to the host computer through the MicroBlaze (MB) soft core. MB core can realize process control and interface conversion on FPGA, and use a small amount of logic resources to replace the functions of MCU and DSP of traditional embedded measurement system, so as to further improve the integration of the instrument. A series of experiments are carried out on the two-phase FPGA platform. ADC sampling rate is 200ksps, 8-Channel synchronous parallel sampling, FPGA system clock frequency is 200MHz. The linear displacement table is set to drive the measurement grating at different displacement speeds, and the total stroke is set to 10mm. The FPGA real-time displacement solution platform is tested. The experimental results show that FPGA obtains accurate displacement solution results under different speed tests. In the test of 2 mm/s, the maximum cumulative displacement measurement error is 5um, which shows the real-time performance and accurate displacement solution performance of FPGA platform.
The signal processing of the grating encoder has a great impact on its accuracy and resolution. We proposed a new type of signal processing method for a grating encoder using a two-phase differential algorithm based on the two-phase physical structure. The interference signal could be divided into two phases with 90 degrees phase delay, capable of effectively reducing the number of optical devices and the space occupied by the reading head. Owing to the rapid elimination of the DC component in the measurement signal, the measurement displacement was solved swiftly by the two-phase signal using the algorithm. In the experiment, a 660 nm laser and a 1 µm-period grating were used, and the scale grating was actuated at a speed of 1 µm/s by a linear stage. With a sampling rate of 20 kHz, the system resolution of the grating encoder was enabled to reach 50 pm. Simultaneously, there was a measurement error of ±1 µm at a stroke of 4 mm, and the error within a single cycle was 2 nm. Compared with the four-phase algorithm, our proposed two-phase differential algorithm exhibits a compact physical structure and fast solution without reducing the accuracy and resolution, which will be of great significance to the real-time measurement and miniaturization of grating encoders.
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.
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