Error Compensation Algorithm Research Articles

Detection and compensation of installation eccentricity of photoelectric encoder based on double highpass filter

As a precision position sensor, the photoelectric encoder has difficulty avoiding eccentricity or tilt error in the industrial manufacturing and assembly process. At present, manual error correction is often used to adjust. The adjustment efficiency is low, and it has difficulty cooperating with other types of error compensation methods. In view of these problems, we proposed a photoelectric encoder eccentricity error detection and compensation method based on digital signal bandpass filtering that effectively corrects the signal deviation caused by the installation eccentricity in the output signal and judges the direction and magnitude of the eccentricity error to realize the encoding correction of eccentricity and inclination error of the device. The mathematical model of the eccentric error generation principle of the photoelectric encoder combined with the Lissajous figure was derived. We then demonstrated the design of a photoelectric encoder error detection platform to detect photoelectric encoders of different diameters in real time. Finally, using the advantages of field programmable gate array high-speed parallel processing, the error compensation algorithm was written into the development chip to improve the efficiency of processing the encoder output error signal. This method can adapt to the eccentricity error correction and compensation of different models of photoelectric encoders and can greatly improve the efficiency and accuracy compared with previous detection methods.

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

Photoelectric encoders are widely used in high-precision measurement fields such as industry and aerospace because of their high precision and reliability. In order to improve the subdivision accuracy of moiré grating signals, a particle swarm optimization compensation model for grating the subdivision error of a photoelectric encoder based on parallel iteration is proposed. In the paper, an adaptive subdivision method of a particle swarm search domain based on the honeycomb structure is proposed, and a raster signal subdivision error compensation model based on the multi-swarm particle swarm optimization algorithm based on parallel iteration is established. The optimization algorithm can effectively improve the convergence speed and system accuracy of traditional particle swarm optimization. Finally, according to the subdivision error compensation algorithm, the subdivision error of the grating system caused by the sinusoidal error in the system is quickly corrected by taking advantage of the high-speed parallel processing of the FPGA pipeline architecture. The design experiment uses a 25-bit photoelectric encoder to verify the subdivision error algorithm. The experimental results show that the actual dynamic subdivision error can be reduced to ½ before compensation, and the static subdivision error can be reduced from 1.264″ to 0.487″ before detection.

Investigation of Systematic Errors of an Indirect Resonant Planar Material Characterization Method

Indirect measurement principles have always been presented as a solution to save simulation and modeling efforts for complex permittivity extraction methods. However, detailed investigations on remaining systematic errors as well as recommendation guidelines for reference material selection are missing in the literature. In this article, typical systematic error sources of a planar coplanar waveguide over ground material sensor are investigated. An indirect error compensation algorithm is presented, and its ability to compensate the main error sources is simulatively analyzed. A measurement setup is created by considering the specified requirements. The measurement principle is validated by measuring three different plastics. Overall, the results are plausible and have uncertainties of the same or lower order of magnitude compared with the state of the art. However, the findings show that indirect planar methods suffer from fundamental problems, which limit the achievable measurement uncertainty. The findings of this work can be used as a basis for decision-making when considering an indirect planar measurement principle.

Matlab-OpenDSS 연계 모의를 이용한 배전 계통의 스마트 인버터 전압 제어 방안 연구

PV Generator at the end of the distribution line affects the direction of the line current and causes voltage increase. Various DER outputs connected to the distribution system have different control characteristics for each connection point. The DER connection point can greatly influence the inverter function and parameter settings. The smart inverter model presented in this paper is a model of simultaneously considering voltage stability of DER linked distribution systems and analyzed at PCC with Matlab-COM. The PCC Voltage when finally stabilized after using Volt-Var function can be adjusted more when there is a margin for the reactive power output. Dynamic Voltage Error Compensation (DVEC) algorithm presented in this paper that automatically refers volt-var curve and measured moving average voltage and finally compensate reactive power output of smart inverter.

Efficient phase-shift error compensation algorithm based on probability density function

In non-digital projection systems, the inaccuracy of phase shifts is one of the most important nonlinear errors. In this paper, an efficient and universal compensation algorithm is proposed, which does not need to find the exact phase shift amounts, but to compensate the periodical errors by a universal two-coefficient error model. With this model, only two error coefficients should to be searched for any multi-step phase shift algorithm. To find the error coefficients, a correlation process and a tool known as the probability density function (PDF) are used. First, a set of pre-simulated PDF curves are generated with the different error coefficients. Second, a practical PDF curve from captured fringes is calculated. Finally, the correlation process is carried out to locate the most similar simulated PDF curve, whose error coefficients are the practical ones. In this paper, we demonstrate the compensation for three, four and five-step phase-shifting algorithms separately. Experimental results show that this method has high universality, and can meet the requirements of rapid and high accuracy measurement.

Short‐circuit current constrained unit commitment and transmission switching model for improving renewable integration: An MILP formulation

The increased penetration of large-scale renewable energy resources results in the significant reduction of the system short-circuit current (SCC) level, challenging current protection systems. In real-time operation, several conventional synchronous generators are committed to maintaining the SCC level at a range that can be identified by the protection system. This limits the hosting capacity of renewable energy integration. This paper investigates the impacts of transmission switching (TS) and unit commitment (UC) on SCC magnitude and derives several linear expressions of SCC constraints for optimal control to restrain the SCC level to the desired range. Besides, an error compensation algorithm is developed to mitigate the linearization error. Numerical results carried out on the standard IEEE test systems show that the proposed method can effectively confine the SCC magnitude to the desired range while increasing the penetration of renewable energy. Comparison results with other methods highlight that the proposed method can achieve a higher level of renewable energy integration without violating SCC constraints.

STEREO VISION INFORMATION SYSTEM USING MEDIAN THEOREM AND ATTITUDE COMPENSATION WITH NONLINEAR DIFFERENTIAL EQUATIONS

Using computer vision technology to obtain and analyze biomechanical information is an important research direction in recent years. However, the linear model in the computer vision system cannot accurately describe the geometric relationship of the camera imaging, so it is difficult to realize human posture recognition in high-precision mechanics information. Therefore, how to improve the recognition accuracy is very important. In this paper, we apply nonlinear differential equations to stereo computer vision (SCV) information systems. And based on the median theorem, a nonlinear posture recognition and error compensation algorithm based on BP neural network is proposed to reduce the recognition error. The test set uses the Leeds Motion Pose (LSP) dataset to verify the performance of the algorithm. Experimental results show that the compensated median filter of BP neural network can eliminate glitches in attitude data. Superimposing the output attitude error compensation value with the attitude estimation value can greatly reduce the root-mean-square error of the attitude angle. The result of gesture recognition is closer to reality. Compared with traditional algorithms, the cyclomatic complexity of the proposed BP neural network algorithm has a much lower growth rate in high-order calculations, which indicates that the proposed BP neural network algorithm is more concise and scalable.

Research on motion track error detection and compensation algorithm based on MEMS sensor

Due to various errors in actual use, MEMS inertial sensors have large errors in the detection of motion trajectories. Therefore, it is necessary to analyse and model the errors to decrease the impact of error sources on the detection system. This errors mainly include systematic random errors and accumulated errors generated during double integral operation, and different filtering methods are used for different types of errors. For random errors, the wavelet fuzzy threshold method is used to filter the sensor output signal. For the accumulated error, the zero-state adaptive compensation algorithm is used to correct the acceleration and integral velocity. Experiments show that the wavelet threshold denoising algorithm combined with the zero-state adaptive compensation algorithm can enhance the preciseness of the MEMS inertial sensor in object trajectory detection.

A High-Frequency Motion Error Compensation Algorithm Based on Multiple Errors Separation in BiSAR Onboard Mini-UAVs

In this article, a high-frequency motion error compensation algorithm for mini-unmanned aerial vehicle (UAV)-based bistatic synthetic aperture radar (BiSAR) system is proposed. Compared with the traditional SAR system platform, the mini-UAV is more vulnerable to interference from the external environment. Thus, the motion error of mini-UAV-based BiSAR systems always contains both low- and high-frequency components. Meanwhile, the independent transmitter and receiver sources would introduce more than one high-frequency motion error component, and the variance of the high-frequency motion error also needs to be considered. This article first establishes a high-frequency motion error model and the corresponding Doppler phase signal for the mini-UAV-based BiSAR system. Then, multiple forms and multiple components errors are separated and estimated on the azimuth phase. Next, the complex spatial variance is accurately modeled and compensated by estimating the platforms’ motion errors. It is suggested from the simulation and experimental results that the proposed algorithm can compensate for the motion error with complex forms under the mini-UAV-based BiSAR system condition.

Error Compensation of Strapdown Inertial Navigation System for the Boom-Type Roadheader under Complex Vibration

The strapdown inertial navigation system can provide the navigation information for the boom-type roadheader in the unmanned roadway tunneling working face of the coal mine. However, the complex vibration caused by the cutting process of the boom-type roadheader may result in significant errors of its attitude and position measured by the strapdown inertial navigation system. Thus, an error compensation method based on the vibration characteristics of the roadheader is proposed in this paper. In order to further analyze the angular and linear vibration of the fuselage, as the main vibration sources of the roadheader, the dynamic model of the roadheader is formulated based on the cutting load. Following that, multiple sub-samples compensation algorithms for the coning and sculling errors are constructed. Simulation experiments were carried out under different subsample compensation algorithms, different coal and rock characteristics, and different types of roadheader. The experimental results show that the proposed error compensation algorithm can eliminate the effect of the angular and linear vibration on the measurement accuracy. The coning and sculling error of the strapdown inertial navigation system can reduce at least 52.21% and 42.89%, respectively. Finally, a strapdown inertial navigation error compensation accuracy experiment system is built, and the validity and superiority of the method proposed in this paper are verified through calculation and analysis of the data collected on the actual tunneling work face.

Scanning error detection and compensation algorithm for white-light interferometry

As the primary error source in white-light interferometry (WLI), the error of scanning steps directly affects coherence peak sensing and greatly lowers the measurement accuracy. Based on the least-squares iterative algorithm, we present an algorithm to detect and compensate for scanning error in WLI. The actual scanning step is calculated from the continuous moving fringes with an iterative algorithm, and the surface is reconstructed with the calculated scanning steps to make compensation. Both simulations and experiments indicate that the high-accuracy measurements can be implemented under disturbance over a wide frequency band. The proposed algorithm could relax the environment requirement of white-light interferometer application.

Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring

Global navigation satellite system (GNSS)-based synthetic aperture radar interferometry (InSAR) employs GNSS satellites as transmitters of opportunity and a fixed receiver with two channels, i.e., direct wave and echo, on the ground. The repeat-pass concept is adopted in GNSS-based InSAR to retrieve the deformation of the target area, and it has inherited advantages from the GNSS system, such as a short repeat-pass period and multi-angle retrieval. However, several interferometric phase errors, such as inter-channel and atmospheric errors, are introduced into GNSS-based InSAR, which seriously decreases the accuracy of the retrieved deformation. In this paper, a deformation retrieval algorithm is presented to assess the compensation of the interferometric phase errors in GNSS-based InSAR. Firstly, the topological phase error was eliminated based on accurate digital elevation model (DEM) information from a light detection and ranging (lidar) system. Secondly, the inter-channel phase error was compensated, using direct wave in the echo channel, i.e., a back lobe signal. Finally, by modeling the atmospheric phase, the residual atmospheric phase error was compensated for. This is the first realization of the deformation detection of urban scenes using a GNSS-based system, and the results suggest the effectiveness of the phase error compensation algorithm.

Vibration error compensation algorithm in the development of laser interference absolute gravimeters

Abstract. Measurement error arising from vibration interference is recognized as the primary obstacle limiting the accuracy and stability of laser interference absolute gravimeters. The present work addresses this issue by proposing a global search optimization algorithm that determines the optimal absolute value of gravity based on the measured time–displacement coordinates of a falling body and the signal obtained from the passive vibration isolation system of the inertial reference corner cube in a laser interference absolute gravimeter. Results of numerical calculations conducted under vibration interference conditions with added white noise resulting in a signal-to-noise ratio of 40 dB demonstrate the following. The accuracy and standard deviation of the gravimeter obtained using the proposed algorithm are −0.04 µGal (1µGal=1×10-8 m s−2) and 0.24 µGal, respectively, while those values obtained by the standard least-squares solution are 10.19 and 154.11 µGal, respectively. The test results indicate that the average response of the reference value of acceleration due to gravity superimposed by a disturbance of 1.00 µGal is 1.01 µGal using the proposed algorithm and 0.87 µGal using the standard least-squares solution.

Direct position determination with phase error compensation for multiple targets using spatial sparsity

Measuring the positions of multiple targets is key in many positioning applications. Utilizing compressed sensing theory, measurements using the sparse direct position determination (DPD) methods are more accurate than the two-step methods and the traditional DPD methods. Position measurement with mobile access points (APs) expands the network coverage, increases information throughput and reduces implementation costs, which motivates us to extend sparse DPD (SDPD) to the mobility-assisted positioning system. However, one of the most critical problems in mobility-assisted positioning is the model errors coming from the AP position and velocity uncertainty. The paper proposes a phase error compensation algorithm for the SDPD algorithm based on mobile APs. The algorithm makes two key technical contributions. First, a double iteration for -norm optimization is designed to compensate phase errors and recover target distribution maps simultaneously. Second, when the data collection is incomplete or irregular, the algorithm jointly integrates the global information of target distribution maps at different APs to improve the measurement accuracy. Experimental results indicate the effectiveness of the algorithm.

Azimuth Variant Motion Error Compensation Algorithm for Airborne SAR Imaging Based on Doppler Adjustment

Conventional beam-center approximation-based motion compensation (MOCO) algorithms fail to achieve an optimally focused image in the case of the high-resolution and high-frequency (HRHF) synthetic aperture radar (SAR) system. In this letter, a novel MOCO algorithm based on Doppler adjustment is developed with the ability to compensate the azimuth variant motion error. The change of the Doppler spectrum caused by the azimuth variant motion error is investigated and is eliminated by Doppler scaling. The proposed MOCO algorithm has dramatically improved precision when compared with the conventional MOCO methods in HRHF SAR imaging. Simulation experiments and extensive comparisons with other MOCO algorithms verify the effectiveness of the proposed algorithm.

Integrator-Less Method for Phase Angle Estimation of Fundamental Frequency Positive-Sequence Component Under Adverse Condition

This article proposes an integrator-less method for phase angle estimation of unbalanced three-phase voltage systems under adverse conditions. It mainly unites abc-to- dq transform, delayed signal cancellation scheme, and a phase error compensation algorithm. It does not demand online operation of integrators, and thus, associated discretization error and instability issue are not present in the proposed method. It is also an unconditionally stable technique as it uses a real open-loop structure. Moreover, the method is relatively simple and computationally efficient due to circumventing online operations of the complex functions, such as square root, trigonometric, and inverse trigonometric. Under alike transient time conditions, the proposed method is more resistant to harmonic disturbances when compared to integrator-based similar competing techniques, such as an enhanced frequency adaptive demodulation approach and a phase error compensation-based open-loop method. The usefulness of the offered method is proved using simulated and experimental results.

Generic nonlinear error compensation algorithm for phase measuring profilometry

In this Letter, the periodical errors, which are caused by the nonlinear effect of the commercial projector and camera, are analyzed as a more generic single-coefficient model. The probability density function of the wrapped phase distributions is used as a tool to find the compensation coefficient. When the compensation coefficient is detected, on the premise of ensuring accuracy, a correlation algorithm process is used to replace the traditional iterative process. Therefore, the proposed algorithm improves the efficiency of coefficient detection dramatically. Both computer simulation and experiment show the effectiveness of this method.

High Frequency Response Current Self-Demodulation Method for Sensorless Control of Interior Permanent Magnet Synchronous Motor

In the sensorless control, high frequency (HF) rotating sinusoidal voltage injection method requires the position error compensation algorithms to eliminate the side effect of system delay. However, the implementation complexity of the system is increased and the optimization of dynamic performance is hard to realize. This paper presents a system delay-free rotor demodulation method without constructing assistive demodulation signal and using position error compensation algorithm. The improvement of position estimation accuracy and the simplification of rotor position demodulation are achieved in the proposed method. Firstly, the side effect of the system delay on HF induced current and rotor position estimation is analyzed in detail. Secondly, the idea of eliminating system delay angle in HF current is proposed based on vector operations. The positive- and negative-sequence components of HF current are used to demodulate rotor position information by a vector algorithm. Simultaneously, the system delay angle is offset in the demodulation process. Thirdly, the rotor position angle is precisely solved by a normalized PLL. Furthermore, the proposed method can also be applied for both HF rotating voltage injection and HF orthogonal square-wave voltage injection. The effectiveness and advantages of the proposed method are validated experimentally.

Clock synchronization error compensation algorithm based on BP neural network model

Error compensation is an important guarantee method to ensure the accuracy of clock synchronization in underwater sensor networks. Existing research methods mainly use linear fitting and least square method to compensate for clock synchronization parameters. Underwater wireless sensor network nodes are mobile, which leads the network nodes to be always in a time-varying state. In the process of synchronous forwarding, the position where the node sends and receives data packets will change, resulting in a relative moving distance, leading the dynamic delay to an increase in. In this way, as the number of forwarding nodes increases, the error of the clock gradually increases, causing the synchronization accuracy of the underwater sensor wireless network to gradually decrease. The existing underwater wireless sensor network clock synchronization algorithm does not fully consider the dynamic time delay caused by the movement of the node with the ocean current. It only uses the time stamp mechanism to solve the clock synchronization parameters, and then uses the traditional linear fitting to refine the synchronization parameters. The accurate solution of dynamic time delay is a key factor of synchronization accuracy. The use of traditional optimization algorithms to refine the synchronization parameters can easily fall into a local optimum, which makes the synchronization accuracy not high. Therefore, the existing traditional research on clock synchronization algorithms cannot well solve the problem of clock synchronization accuracy caused by node mobility. However this type of method does not consider the clock synchronization accuracy of node movement affected by ocean currents. To solve this problem, this paper proposes a clock synchronization error compensation algorithm based on BP neural network model. First, the deep-sea Lagrangian ocean current model is used to describe the movement of underwater nodes and simulate the movement speed of underwater nodes, and then a clock synchronization parameter model is established, and finally a BP neural network clock synchronization error compensation model is build, which conforms to the underwater environment, and the excitation function is defined, and regular term factor and compensatory factor are introduced to avoid model over-fitting. The BP neural network model clock synchronization error compensation algorithm is established for error back propagation. Simulation experiments show that compared with the comparison algorithm TSHL, MM-sync, and MU-sync, the accuracy of clock synchronization, namely the error between clock synchronization time and standard time, increased by 37.42%, 17.29% and 21.86%, and the mean square error is significantly reduced.

Undersampling homodyne I/Q interferometry for ultra-low-frequency vibration calibration

In order to overcome the limitations associated with existing homodyne laser interferometry for ultra-low-frequency vibration calibration, undersampling homodyne I/Q interferometry is proposed in this letter. Limitation of time-consuming quadrature error compensation algorithm is avoided by using hardware error compensation with a specially designed homodyne interferometry optical configuration, while limitation of high Nyquist frequency is avoided by applying Kalman I/Q signal unwrapping with deeply under-sampled fringe phase signals. The effectiveness of the proposed method is verified through simulation and experiment. Experimental results indicate that sampling frequency can be reduced by 30 times for movement measurement at 1 m/s while quadrature error is compensated in real-time. It can, therefore, be concluded that the proposed method is effective for ultra-low-frequency vibration calibration.