Research on Particle Swarm Compensation Method for Subdivision Error Optimization of Photoelectric Encoder Based on Parallel Iteration

Hou, Han; Cao, Guohua; Ding, Hongchang; Li, Kun

doi:10.3390/s22124456

Cited by 5 publications

(6 citation statements)

References 14 publications

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“…Non-contact sensors mainly include optical sensors, capacitive sensors [22,23], magnetoresistive sensors [24][25][26] and inductive sensors [27,28]. Optical sensors are categorized as photoelectric encoders [29][30][31] or grating sensors [32][33][34]. Their advantages are high measurement resolution and accuracy.…”

Section: Of 29mentioning

confidence: 99%

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Modelling, Linearity Analysis and Optimization of an Inductive Angular Displacement Sensor Based on Magnetic Focusing in Ships

Wang

et al. 2023

JMSE

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A sensor for measuring the crankshaft angle of the main engine in ships is designed. Compared with the existing crankshaft angle encoder, this design’s advantage is that there is no need to add a gear system at the free end of the crankshaft, reducing machining complexity. The purpose of providing high angle resolution over a wide speed range is achieved. Inductive angular displacement sensors (IADSs) require an eddy current magnetic field as a medium to generate the induced voltage. The induced voltage also requires a complex linearization calculation to obtain a linear relationship between angle and voltage. Therefore, a model of the inductive angular displacement sensor based on magnetic focusing (IADSMF) is proposed. Magnetic focusing is introduced into the IADS to replace the eddy current magnetic field with a focusing magnetic field. The main disadvantage of traditional IADSs, which is that they cannot reduce the eddy current magnetic field, is mitigated. An approximate square−shaped focusing magnetic field (12.4 × 12.4 mm2) is formed using the magnetic field constraint of the magnetic conductor. When the receiving coil undergoes a position change relative to the square−shaped focusing magnetic field, the voltage generated via the receiving coil is measured using the electromagnetic induction principle to achieve angular displacement measurement. A mathematical model of the IADSMF is derived. Induced voltages at different frequencies and rotational speeds are simulated and analyzed via MATLAB. The results show that frequency is the main factor affecting the induced voltage amplitude. The sensitivity of the IADSMF is 0.2023 mV/°. The resolution and measurement of the IADSMF range from 0.06° and 0–360°. Compared with a conventional planar coil−based IADS, the eddy current loss is reduced from 2.1304 to 0.3625 W. Direct linearization of the angular displacement with the induced voltage is achieved through designing a square−shaped focusing field and receiving coil. After optimizing the sensor structure with the optimization algorithm, the linearity error is 0.6012%. Finally, this sensor provides a theoretical basis and research ideas for IADS development in ships and navigation.

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Section: Of 29mentioning

confidence: 99%

“…Linearity error is calculated through comparing the simulated voltage profile with the ideal voltage profile, i.e., LIWPSO finds a set of structural parameters that minimize the sensor linearity error. The updated formulas [27] of the LIWPSO particle velocity and position can be obtained via (28) and (29), respectively:…”

mentioning

confidence: 99%

Modelling, Linearity Analysis and Optimization of an Inductive Angular Displacement Sensor Based on Magnetic Focusing in Ships

Wang

et al. 2023

JMSE

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“…To reduce the optical encoders’ SDE, multiple subdivision algorithms [ 17 , 18 , 19 , 20 ] have been proposed, many commercial integrated circuits [ 21 ] have been developed, and numerous gratings with special shapes [ 22 , 23 , 24 ] and devices with special dimensions [ 25 , 26 ] have been applied. Recently, the error compensation models based on particle swarm optimization have been applied to the optical encoders to compensate the SDE [ 27 , 28 , 29 ]. Although there are many research outcomes, there are few studies on the single-field scanning absolute linear encoder’s SDE.…”

Section: Introductionmentioning

confidence: 99%

Methods for Reducing Subdivision Error within One Signal Period of Single-Field Scanning Absolute Linear Encoder

Yang

Kilikevičius

et al. 2023

Sensors

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Optical encoders are widely used in accurate displacement measurement and motion-control technologies. Based on different measurement methods, optical encoders can be divided into absolute and incremental optical encoders. Absolute linear encoders are commonly used in advanced computer numerical control (CNC) machines. The subdivision error within one signal period (SDE) of the absolute linear encoder is vital to the positioning accuracy and low velocity control of CNC machines. In our paper, we study the working principle of the absolute linear encoder. We proposed two methods for reducing the SDE of the absolute linear encoder, a single-field scanning method based on the shutter-shaped Moiré fringe, as well as a method for suppressing harmonics through a phase shift of index grating. We established a SDE measuring device to determine the absolute linear encoder’s SDE, which we measured using a constant-speed approach. With our proposed methods, the SDE was reduced from ±0.218 μm to ±0.135 μm, which is a decrease of 38.07%. Our fast Fourier transformation (FFT) analysis of the collected Moiré fringe signals demonstrated that the third-, fifth-, and seventh-order harmonics were effectively suppressed.

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“…In order to improve the precision and ensure the real-time measurement, it is important to find the best the signal processing algorithm and use special hardware to accelerate the algorithm [14][15][16]. The original signal has many nonideal factors, including DC bias, high-frequency noise, low-frequency noise, harmonics and so on [17,18]. Therefore, it is necessary to introduce filtering algorithm to eliminate these interferences.…”

Section: Introductionmentioning

confidence: 99%

“…As an effective time-domain filtering method, Kalman filter, can achieve the minimum mean square error in theory as long as the appropriate state transition equation is set [17,28]. Moreover, because of its less computational cost and simple architecture, it is often used in high real-time applications, such as rocket position estimation, vehicle motion control and other fields [29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Instantaneous grating signal subdivision system with non-linear Kalman filters

Wang

Shi

Li³

et al. 2022

Optical Design and Testing XII

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Grating encoder is a sinusoidal encoder based on grating diffraction principle, which is currently utilized in many high-precision displacement systems because of its advantageous characteristics: low cost, simple structure, works in harsh environments, high reliability, and so on. The output signal of grating encoder usually contains noise interference error, amplitude inconsistency error, DC bias error, harmonic error and quadrature phase error. These non-ideal factors are the main reasons for affecting the precision of subdivision. In the traditional signal subdivision system, it is usually necessary to compensate each kind of error separately, which will consume many hardware and computing resources and cause a significant output latency, especially in the filtering section and normalization section. In this paper, a non-linear Kalman filter-based sin-cos wave subdivision method is proposed. Compared with the traditional filtering methods, non-linear Kalman filter has higher dynamic response and can provide instantaneous phasor estimation. In addition, it can simultaneously achieve filtering, amplitude normalization, decoupling DC bias, harmonic suppression, and phase compensation functions, which significantly reduces the computational burden and facilitates the implementation on low-cost processors. In this study, a non-linear Kalman filter-based signal segmentation system is implemented on an FPGA platform and verified on a six-degree-of-freedom grating ruler platform. The results show that the single-channel output delay is only 1.8us at a 50MHz clock, which has a very high real-time ability. When the frequency and amplitude of the input signal varies, the non-linear Kalman filter can track instantaneously and has high dynamic characteristics. Experimental results show the effectiveness of this method.

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Research on Particle Swarm Compensation Method for Subdivision Error Optimization of Photoelectric Encoder Based on Parallel Iteration

Cited by 5 publications

References 14 publications

Modelling, Linearity Analysis and Optimization of an Inductive Angular Displacement Sensor Based on Magnetic Focusing in Ships

Modelling, Linearity Analysis and Optimization of an Inductive Angular Displacement Sensor Based on Magnetic Focusing in Ships

Methods for Reducing Subdivision Error within One Signal Period of Single-Field Scanning Absolute Linear Encoder

Instantaneous grating signal subdivision system with non-linear Kalman filters

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