A 7.4 kHz, 20-bit image encoder with a CMOS linear image sensor

Mu, Yusong; Jiang, Jiaqi; Ding, Ning; Ni, Qiliang; Chang, Yuchun

doi:10.1007/s11082-019-2037-z

Cited by 17 publications

(4 citation statements)

References 17 publications

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“…In 2018, Lashmanov [15] used a camera to collect and measure the scale ruler with scale lines and achieved a resolution of 0.02μm and a measurement accuracy of 1.65μm. More recently, Mu [16] used a CMOS linear array image sensor to recognize the pseudo-random single-channel code and achieved up to 20-bit code recognition. Meanwhile, Fu [17] proposed an image grating technique that achieved ±0.3μm measurement accuracy within a 50mm range and ±0.2μm measurement accuracy within a 25 mm range.…”

Section: Introductionmentioning

confidence: 99%

Stain-Detection and Anti-Stain Algorithms Based on Dual Detector Data Interchange in Image-Type Displacement Measurement Technology

Wan

Zhao

2023

IEEE Trans. Instrum. Meas.

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Displacement measurement technology based on image recognition algorithms represents a novel high-performance technique. In such measurements, when there are stains contaminating the measuring light path, it causes recognition errors from the linear array image sensor on the grating, resulting in inaccurate measurement results. Therefore, this report proposes stain-detection and anti-stain algorithms based on image recognition. The principle of image-type displacement measurement technology is described, and the influence of stains on the displacement measurements is analyzed according to four criteria in order to judge whether there are stains present. Then, an anti-stain algorithm based on the data exchange of dual-image sensors is proposed. Finally, experimental verifications are carried out. The experimental results show that the proposed algorithm effectively identifies the errors in the displacement measurements, when the experimental device is contaminated, the developed algorithms can accurately self-correct for the stain's interference. The results presented herein provide a theoretical basis for developing highly-reliable displacement measurement devices.

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Section: Introductionmentioning

confidence: 99%

Stain-Detection and Anti-Stain Algorithms Based on Dual Detector Data Interchange in Image-Type Displacement Measurement Technology

Wan

Zhao

2023

IEEE Trans. Instrum. Meas.

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“…Presently, there are relatively few studies that have reported the integration of optoelectronic devices with signal processing circuits. With the development of integrated circuit technology, greater integration of circuits with optoelectronic devices has become the mainstream trend (Mu et al 2019). Further, the existing error compensation schemes for grating moiré fringe photoelectric signals can only be implemented under specific conditions owing to the complexity of the algorithm and low operation speed, with most methods relying on postprocessing of the encoder signals.…”

Section: Introductionmentioning

confidence: 99%

Improving the subdivision accuracy of photoelectric encoder using particle swarm optimization algorithm

Jiang

Dai

et al. 2022

Opt Quant Electron

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To improve the subdivision accuracy of a photoelectric encoder and reduce the effects of sinusoidal errors in the signals on the measurement accuracy of the system, we designed an optoelectronic chip to receive grating moiré fringe signals. An amplifier circuit with a hierarchical pipelined architecture was designed, and the photodetector array was matched with the code disk before processing the received signals. Thereafter, a quantitative analysis was performed on the sinusoidal errors in the signals. From the analysis results, a sinusoidal error compensation method based on the particle swarm optimization (PSO) algorithm was developed, and a subdivision error compensation model was established to correct the errors in the signals. Finally, a fast solution for the PSO algorithm was implemented on a field-programmable gate array, and a grating test platform was built for experimental verifications. The results showed that the peak-topeak subdivision error of the encoder's photoelectric signal decreased by approximately 60% from 2.98ʺ to 1.13ʺ. Therefore, the scheme proposed in this paper is expected to significantly improve the measurement accuracies of photoelectric encoders.

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“…Pattern recognition systems use different mathematical models and algorithms in recognizing patterns in data sets. Several researchers have developed different pattern recognition systems that have been applied in recognizing patterns in different data sets (Soliman et al 2018;Si and Yan 2015;Zhaohui and Xiaodong 2013;Hong et al 2019;Kumar 2016;Bakhtiar and Hosseinzadeh 2016;Salehi and Dehyadegari 2016;Kumar et al 2019;Farrokhi et al 2015;Kotb and Guo 2019;Morsy and Alsayyari 2019;Maity et al 2016;Metya and Janyani 2015;Jordovic-Pavlovic et al 2020;Liu et al 2016;Imtiaz et al 2020;Mu et al 2019;Bhnassy et al 2019). Motivated by the above-mentioned works, this present work has proposed a pattern recognition system.…”

Section: Introductionmentioning

confidence: 99%

3D Fringe Pattern Coding and Recognition Using Plasmonic Sensing Circuit

et al. 2021

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3D interference fringe pattern recognition using a plasmonic sensing circuit is proposed. The plasmonic sensing in the form of a panda ring comprises of an embedded gold grating at the microring center. WGM (whispering gallery mode) is observed at the microring center with suitable parameters. The dark soliton of 1.50µm wavelength excites the gold grating which leads to electron cloud oscillation and forms the electron densities where the trapped electrons inside the silicon microring are transported via wireless connection using WGM and cable connection. The spindown    1 and spin-up    0 result from the electron cloud oscillation. By using the changes in gold lengths, the excited electron pattern recognition can be manipulated, where the values "0 and "1"' are useful for pattern recognition. The fringe patterns of the plasmonic interferometric sensor are recorded, which means that the novel 3D pattern recognition can be possibly implemented and used in many applications. Therefore, the plasmonic sensing circuit can be used to form the quantum code, quantum encryption, quantum sensor, and pattern recognition.

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A 7.4 kHz, 20-bit image encoder with a CMOS linear image sensor

Cited by 17 publications

References 17 publications

Stain-Detection and Anti-Stain Algorithms Based on Dual Detector Data Interchange in Image-Type Displacement Measurement Technology

Stain-Detection and Anti-Stain Algorithms Based on Dual Detector Data Interchange in Image-Type Displacement Measurement Technology

Improving the subdivision accuracy of photoelectric encoder using particle swarm optimization algorithm

3D Fringe Pattern Coding and Recognition Using Plasmonic Sensing Circuit

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