Axis Transformation Research Articles

Unanticipated Fault Detection and Isolation of Telescope Drive System Based on Luenberger Observer and Axes Transformation

Unanticipated Fault Detection and Isolation of Telescope Drive System Based on Luenberger Observer and Axes Transformation

Control strategy for three-phase four-switch active power filter based on positive sequence extraction in stationary coordinate fundamental reference frame

Traditional three-phase four-switch active power filter often uses the method of phase-locked loop (PLL) and low-pass filter for harmonic detection, which seriously affects the detection accuracy. In order to improve the detection accuracy, a lock-free three-phase four-switch active power filter based on fundamental positive sequence extraction is proposed. The harmonic detection adopts the fundamental positive sequence extraction method, and the rotation coordinate axis transformation adopts the phase-locked loop (PLL) free method. Compared with the traditional three-phase four-switch active power filter, this method does not require a phase-locked loop and a low-pass filter, and does not need complex coordinate transformation[2].The control method is simpler. Finally, simulation results prove the effectiveness of the control method.

Robust thin-plate splines for multivariate spatial smoothing

A novel family of multivariate robust smoothers based on the thin-plate (Sobolev) penalty that is particularly suitable for the analysis of spatial data is proposed. The proposed family of estimators can be expediently computed even in high dimensions, is invariant with respect to rigid transformations of the coordinate axes and can be shown to possess optimal theoretical properties under mild assumptions. The competitive performance of the proposed thin-plate spline estimators relative to their non-robust counterpart is illustrated in a simulation study and a real data example involving two-dimensional geographical data on ozone concentration.

Improved Power Control of DFIGs Driven by Wind Turbine under Unbalanced Grid Voltage

AbstractUndesired oscillation components appear in active and reactive powers, electromagnetic torque and DC-link voltage of doubly fed induction generators (DFIGs) connected to unbalanced grid voltage. These components oscillate at double source frequency as a result of negative sequence components in voltage and current. Different direct power control (DPC) techniques were studied in literatures to damp these oscillations. However, these techniques require sequence decomposition process, axes transformation of stator voltage/current and estimation of different power components which complicate the overall control system. This paper presents a simplified DPC of DFIGs in stationary reference frame under normal and unbalanced grid voltage. Decomposition process, axes transformation and compensation power terms are totally eliminated. Vector proportional- integral (VPI) controllers are designed to regulate stator active and reactive powers. The performance of the proposed DPC scheme using VPI and proportional-integral-resonant (PIR) controllers is analyzed and compared under different operating conditions. Bode diagram of open loop and closed loop control using VPI and PIR are studied to illustrate stability, steady state and transient response of the two controllers. Also, the performance of proposed technique and previous DPCs designed in synchronous reference frame is compared to prove the validity of proposed one. The results show that proposed DPC using VPI has superior performance in steady state and transient conditions with simple implementation.

Matlab-based simulations of a three-phase induction motor for dynamic studies

The aim of this paper is to develop a generalized MATLAB program to study the dynamic behavior of a three-phase induction motor. The d-q axis transformation theory is applied in rotor reference frame to study the motor dynamics. A general-purpose MATLAB program is developed and used for the dynamic simulation of a 5HP, 460V, 60Hz, 4-poles induction motor. The developed program is used to study the effect of variation of Stator Resistance (Rs), Moment of Inertia (J), and Load Torque (TL) at t=0.7sec during transient state. The results obtained show that, the torque-speed characteristic curve and mechanical rotor speed-time characteristics of induction motor depend upon the rotor resistance and the moment of inertia. Also, during the simulation of the motor under loaded torque at t=0.7sec, the results showed an increase in the initial starting torque and it reduces from 2000Nm – 0Nm as the operating time progressed. A sudden residual increase occurred in the torque from 0-1000Nm at the loaded time t=0.7sec, and the mechanical rotor speed increased at starting time from 0-1800rpm with respect to operating time and suddenly experienced a drop from 1800rpm to about 1700rpm at the loaded time of t=0.7 sec. The developed program is particularly useful for machine designers in the manufacture of various types of induction machines.

Sensorless control of permanent magnet synchronous motor based on adaptive back-EMF observer

Aiming at the problem that the change of motor parameters in actual operation will significantly reduce the control accuracy of the motor, this paper proposes a sensorless control method of permanent magnet synchronous motor based on an adaptive back-EMF observer. Firstly, in the sensorless vector control algorithm, the mathematical model of the permanent magnet synchronous motor based on the coordinate axis transformation is established, online identification of permanent magnet synchronous motor flux linkage, and the adaptive back EMF observer is constructed. The parameters update the motor model to achieve accurate control of the rotor position and speed of the permanent magnet synchronous motor. Then the back-EMF observer and the adaptive back-EMF observer are verified in the simulation environment. Then the simulation model of the back-EMF observer and the adaptive back-EMF observer is carried out, and the comparison analysis is made. Finally, a permanent magnet synchronous motor control platform is built in the laboratory, and the method proposed in this paper is verified. The results show that, under the condition that the permanent magnet synchronous motor parameters change, the online identification of the parameters and the accurate speed of the permanent magnet synchronous motor can be realized control.

Data Reduction Analysis on UTM-LST External Balance

Abstract: The effective use of wind-tunnel testing in determining aerodynamic properties of a body is very much dependent upon the reliability and speed with which wind-tunnel data can be reduced. The operating efficiency of the wind tunnels is substantially improved by the capability of providing lower aerodynamic coefficients in real time, or online, which decreases the expensive wind-tunnel time necessary for each test. This paper describes a system for presenting reduced wind-tunnel data in real time for UTM-LST. The requirements for data-handling equipment and data reduction procedures for wind tunnels are quite diverse, and depend upon the wind tunnel design and the type of tests for which they are used. The supersonic wind tunnels mentioned in this description have a variety of force-balance systems and are used for force tests, pressure tests, and other research projects. Consequently, the problems associated with in order to solve this diversity we build a computerized program where we can find the transformation of axis and aerodynamic characteristics at ease. This program can find the values of different aerodynamic coefficients with certain angle of attacks.

S117 Endoscopic Ampullectomy - Where Do We Stand Today?

Introduction: The first endoscopic ampullectomy was done in 1983 by Suzuki et al. Since then the technique has been questioned regarding its place in management of ampullary lesions due concerns linked with oncological clearance. The European society of Gastrointestinal endoscopy(ESGE) and the Japanese Gastroenterological Endoscopy society(JGES) have recommendations on endoscopic ampullectomy but American Society of Gastrointestinal endoscopy does not have similar recommendations. Fritzsche et al used Delphi method to draft recommendations but no consensus was reached on 51% of questions. This study aims to investigate the ability of endoscopic ampullectomy to achieve complete resection of the ampullary lesions. Methods: We reviewed the literature from 2010 to 2022 to evaluate endoscopic ampullectomy for its ability to resect the ampullary lesions completely. "Endoscopic ampullecomy", "endoscopic papillectomy" were used as search words in Pubmed.A pooled odd's ratio was then computed. Statistical software "R" version 4.2.0 was used for data analysis. Results: We identified 21 studies, two of these studies provided information on successful resection and one was a meta analysis comparing endoscopic ampullectomy with surgical ampullectomy/ pancreatic duodenctomy. Ten more articles were identified from this meta analysis and included in our study. A total of 877 patients were included from a total of 12 studies. 674 patients had complete resection and did not require any additional treatment.A pooled Odd's ratio[95%CI] of 4.10[1.92-8.77] was computed Figure(A). No significant publication bias was noted Figure(B).One of the study by Kim et al was identified as an outlier and an influencer Figure(C). Conclusion: Endoscopic ampullectomy is effective in complete resection of ampullary lesions with average odds of successful resection of 4. The limitations of this study stems of missing information on the nature of lesions and the size of lesions resected. Also the duration of follow up was not included in most studies. Unlike the JGES, the definition of complete resection was not defined in any study. However the study provides supportive evidence that resection of ampullary lesions is possible endoscopically, without the morbidity and mortality associated with Whipple procedure/ Surgical ampullectomy.Figure 1.: A) Shows the forest plot with odds ratio from the individual studies and pooled Odd's ratio, The results have been subjected to exponential axis transformation. B) Funnel plot showing the publication bias. C) Buajat plot

Current Sensor Fault-Tolerant Control for Five-Phase PMSM Drives Based on Third-Harmonic Space

According to the different forms of back electromotive force, five-phase permanent-magnet synchronous motors (FPMSMs) can be divided into two types: sinusoidal FPMSMs (SFPMSMs) and trapezoidal FPMSMs (TFPMSMs). In field-oriented-controlled FPMSM drives, current sensors may malfunction in harsh working environments. In this article, two current sensor fault-tolerant control (FTC) strategies based on third-harmonic space, respectively, corresponding to SFPMSMs and TFPMSMs are proposed. Different from three-phase motor, the decoupled model of five-phase motor contains two orthogonal subspaces. The key to both strategies is that the third-harmonic space currents are controlled at zero when current sensors malfunction. Thus, the faulty phase current can be estimated with other phase currents by using the constraint equations of current transformation. For SFPMSMs, vector control and sinusoidal pulsewidth modulation technology are used to control the third-harmonic space currents to zero. For TFPMSMs, offset axis transformation and resonant observer are adopted for third-harmonic space current estimation and the third-harmonic space currents are controlled to zero by using the estimated values as feedback of vector control. The experimental results demonstrate that the robustness of both current sensor FTC systems is well performed in the whole speed range.

An accurate dynamical model of induction generator utilized in wind energy systems

Due to the advantages of a self-excited induction generator (SEIG), it plays a main role in sources of renewable energy, such as wind turbines (WT). The regulation of terminal voltage and frequency is poor under variable rotor speed and load conditions at stand-alone operation mode. The generator terminal voltage depends on the excitation capacitance which can be controlled by a capacitor bank and static voltage compensator. The dynamical model of the machine is described by differential equations in D-Q axes transformations of the synchronously rotating frame. Many models of analysis are proposed in the literature. In those models, several approximations are used to simplify the process of calculations, such as neglecting the iron core resistance, stray load resistance, stator and rotor leakage reactance, and magnetic saturation. In this work, a comprehensive dynamic model of the SEIG-WT is performed to analyze the system performance under transient and steady-state conditions. This dynamic model considers the effect of all machine parameters variation. New analytical formulas are used for to accurate calculation of minimum and maximum values of excitation capacitance and generator rotor cut-off and maximum speed. The dynamic model results are partially compared with experimental results, and accurate agreement is shown.

BCyto: A shiny app for flow cytometry data analysis

Flow cytometry (FCM) is a widely used technique to simultaneously measure various characteristics of a cell or particle. Most of reliable software for FCM data analysis are commercially available at high costs. A few R packages are available; however, programming skills are required. In addition, currently, no package offers an interactive user interface (UI) with efficient tools for conventional FCM data analysis. BCyto is an open-source R package/shiny app that allows cell biologists with no coding skills to reliably analyse FCM data in R. BCyto provides intuitive axis transformation for better data visualization, easy visualization of compensation plots and modification of compensation matrices, fast generation of backgating and overlay plots, as well as built-in proliferation and dimensionality reduction tools. BCyto will not only improve accessibility to FCM data analysis but might also serve as an environment for the development of further R-based computational FCM algorithms.

Automatic Extraction of Mountain River Surface and Width Based on Multisource High-Resolution Satellite Images

The extraction of high-resolution geomorphic information from remote sensing images is a key technology for supporting mountain river research. Extracting small rivers (width < 90 m) from complex backgrounds based on satellite images remains a challenging issue. In this research, we propose an improved random forest (RF) algorithm, RF-ANN (artificial neural network), by using neural networks and thermal infrared data for the extraction of river surfaces. We also develop an automated river width extraction (ARWE) method based on the central axis transformation algorithm and centerline automatic correction algorithm for the automatic extraction of the river widths across the whole basin. We chose the Huangfuchuan River Basin on the Loess Plateau, China, as a case study area. Chinese GF-1 and ZY-3 satellite images were implemented as the primary data source. We extracted the bankfull river surface and river widths of the Huangfuchuan River by using these two improved methods. The results show that the RF-ANN method has a total river surface extraction accuracy of 94.7%, and the extracted river surfaces cover more than 85% of the order 3 DEM river network. By implementing high-resolution DEM and thermal infrared data, RF-ANN effectively eliminates the disturbance of shadows of mountains and other features, which ensures the high accuracy of the extracted widths. It was verified that the maximum and minimum river widths that can be extracted in the Huangfuchuan River Basin are 297.4 m and 6.1 m, respectively. The overall error of river width extraction is 0.97 m, which is less than half of the pixel length of remote sensing images. The R2 and root mean square error (RMSE) of the estimated river width values are 0.99 and 1.49, respectively. For tiny rivers with widths narrower than 10 m, the error of river width extraction is 10.9%. The error of thin rivers whose widths range from 10 to 30 m is 4.9%. For small rivers ranging from 30 to 90 and rivers wider than 90 m, the error is 1.1% and 0.6%, respectively. The new approach provides an effective method for extracting the surface and width of mountain rivers in topographically complex regions by using high-resolution satellite images, which may provide a database for estimating river carbon emissions and related research in fluvial morphology and water resource management.

TAD-Net: tooth axis detection network based on rotation transformation encoding

The tooth axes, defined on 3D tooth model, play a key role in digital orthodontics, which is usually used as an important reference in automatic tooth arrangement and anomaly detection. In this paper, we propose an automatic deep learning network (TAD-Net) of tooth axis detection based on rotation transformation encoding. By utilizing quaternion transformation, we convert the geometric rotation transformation of the tooth axes into the feature encoding of the point cloud of 3D tooth models. Furthermore, the feature confidence-aware attention mechanism is adopted to generate dynamic weights for the features of each point to improve the network learning accuracy. Experimental results show that the proposed method has achieved higher detection accuracy on the constructed dental data set compared with the existing networks.

Attitude propagation using slewing and rotational transformations of a single axis

• An analytical attitude transformation for an axis that slews along a conical trajectory was derived. • Error free attitude propagation was achieved using the slewing and rotational transformation of a single axis. • Attitude was propagated without error for an axisymmetric vehicle with time dependent angular rate magnitude. A new analytical method to compute the slewing transformation of an axis that moves along a conical trajectory centered on a fixed axis was derived. The result was used to increase the attitude propagation accuracy using a single axis by incorporating the slewing motion of the angular rate vector into the attitude propagation algorithm. It was shown that when the slew rate of the angular rate vector has a fixed orientation in the body frame and has a magnitude proportional to the angular rate vector magnitude, the attitude can be propagated with only numerical roundoff error. The findings not only agree with previously published results, but provide an additional new solution due to the commutative property of the associated slewing and rotational transformations. The algorithm was applied to pure coning motion having time dependent angular rate magnitude and the coning motion of axisymmetric vehicles with time dependent angular rate magnitude. Numerical examples that demonstrate the improvement in accuracy are included.

Efficient gene targeting in soybean using Ochrobactrum haywardense-mediated delivery of a marker-free donor template.

Gene targeting (GT) for precise gene insertion or swap into pre-defined genomic location has been a bottleneck for expedited soybean precision breeding. We report a robust selectable marker-free GT system in soybean, one of the most economically important crops. An efficient Oh H1-8 (Ochrobactrum haywardense H1-8)-mediated embryonic axis transformation method was used for the delivery of CRISPR-Cas9 components and donor template to regenerate T0 plants 6–8 weeks after transformation. This approach generated up to 3.4% targeted insertion of the donor sequence into the target locus in T0 plants, with ∼ 90% mutation rate observed at the genomic target site. The GT was demonstrated in two genomic sites using two different donor DNA templates without the need for a selectable marker within the template. High-resolution Southern-by-Sequencing analysis identified T1 plants with precise targeted insertion and without unintended plasmid DNA. Unlike previous low-frequency GT reports in soybean that involved particle bombardment–mediated delivery and extensive selection, the method described here is fast, efficient, reproducible, does not require a selectable marker within the donor DNA, and generates nonchimeric plants with heritable GT.

Additive manufacturing with fibre-reinforcement – design guidelines and investigation into the influence of infill patterns

PurposeFibre-reinforced additive manufacturing (FRAM) with short and continuous fibres yields light and stiff parts and thus increasing industry acceptance. High material anisotropy and specific manufacturing constraints shift the focus towards design for AM (DfAM), particularly on toolpath strategies. Assessing the design-property-processing relations of infill patterns is fundamental to establishing design guidelines for FRAM.Design/methodology/approachSubject to the DfAM factors performance, economy and manufacturability, the efficacy of two conventional infill patterns (grid and concentric) was compared with two custom strategies derived from the medial axis transformation (MAT) and guided by the principal stresses (MPS). The recorded stiffness and strength, the required CPU and print time, and the degree of path undulation and effective fibre utilisation (minimum printable fibre length) associated with each pattern, served as assessment indices for different case studies. Moreover, the influence of material anisotropy was examined, and a stiffness-alignment index was introduced to predict a pattern’s performance.FindingsThe highest stiffnesses and strengths were recorded for the MPS infill, emphasising the need for tailoring print paths rather than using fixed patterns. In contrast to the grid infill, the concentric infill offered short print times and reasonable utilisation of continuous fibres. The MAT-based infill yielded an excellent compromise between the three DfAM factors and experimentally resulted in the best performance.Originality/valueThis constitutes the first comprehensive investigation into infill patterns under DfAM consideration for FRAM, facilitating design and processing choices.

A Cutter Selection Method for 2 1/2-Axis Trochoidal Milling of the Pocket Based on Optimal Skeleton

The trochoidal toolpath is generated based on skeleton. However, several different skeletons can be extracted from one pocket. To improve the efficiency of trochoidal rough milling, a cutter selection method basing the optimal skeleton is proposed. Firstly, for a pocket, preliminary skeleton curves and nodes are extracted according to the principle of medial axis transformation. A skeleton extraction method is given that the skeleton is a combination of skeleton curves generated by randomly connecting the preliminary skeleton curves under nodes constraint. A set of skeletons can be obtained by repeatedly extracting skeleton. Furthermore, an optimization model based on the shortest machining time is established, and then the optimization model is solved by the Genetic Algorithm to determine the optimal tool combination and skeleton. The developed approach is validated in trochoidal milling a pocket for cutter selection. The experimental results show that the method can significantly improve the processing efficiency.

An Active Fault-Tolerant Control Strategy for Current Sensors Failure for Induction Motor Drives Using a Single Observer for Currents Estimation and Axes Transformation

This paper proposes a fault-tolerant control technique against current sensors failure in direct torque controlled induction motors drives, based on a new modification of Luenberger observer for currents estimation and axes transformation for vector rotation. Several important aspects are covered in the proposed algorithm, such as the detection of sensors failure, the isolation of faulty sensors, and the reconfiguration of the control system by a correct estimation. A logic circuit ensures fault detection by analyzing the residual signal between the measured and estimated quantities, while a single observer performs the task of estimating the line currents. In addition, a decision logic circuit isolates the erroneous signal and simultaneously selects the appropriate estimated current signal. An axes transformation ensures rotation from (a,b) to (α,β), which keeps a low-cost control using only two current sensors. The proposed scheme is tested on MATLAB/Simulink environment and experimentally validated in a laboratory prototype mainly containing a dS1104 card and 4 kW induction motor.

Manifestation of lattice topology data model for indoor navigation path based on the 3D building environment

Abstract Navigation, also known as discovering one’s direction, is a complex human activity. To produce effective routes, it relies on knowledge of the surroundings’ precise geometry and semantic information. Complex geometrical data can be precisely delineated with the improvement of 3D geometric models. A precise 3D geometric model containing a specifically built-in Building Information Modelling (BIM) environment can be integrated into the Geographical Information System platform for indoor path generation to satisfy the requirements of indoor location-based services. Therefore, this paper proposes an approach to evaluate a 3D indoor topology network called a lattice topology data model (LTDM) for the floor-level paths in a 3D multipatch-based model. The LTDM requires the geometric information of the integrated BIM model to identify the indoor space and bounding lines for indoor network generation. The novelty of this study is in the application of the replacement of cell values into vector length for pathfinding through a combination of the Poincaré duality theorem and Dijkstra’s algorithm. The Campus Infrastructure Building model was chosen to validate the proposed method. Multiple space centroid pairs within the floor level were randomly selected to identify the shortest path using the LTDM principle. Paths drawn from the Medial Axis Transformation were compared with LTDM-generated paths for availability testing. The average floor-level path availability was 112% due to the generation of extra paths reflecting real-life situations. The LTDM paths were compared with on-site measurements for accuracy tests, and the average error rate was 3.18%. The results show that the implementation of the LTDM generates an excellent topology data network.

Sensorless FOC Strategy for Current Sensor Faults in Three-Phase Induction Motor Drives

Current sensors are required in Field-Oriented Control (FOC) strategies of Three-Phase Induction Motor (TPIM) drives. Nevertheless, the current sensors are subject to different electrical/mechanical faults which reduce the safety and dependability of the drive system. Single phase current sensor Fault-Tolerant Control (FTC) for sensorless TPIM drives using flux observer and Extended Kalman Filter (EKF) is proposed in this research. In the suggested FTC scheme, current sensor fault detection is based on axes transformation, a logic circuit is served as the fault isolation and reconstruction of faulted currents are achieved through flux observer and EKF. The presented FTC system is capable of detecting and localizing the current sensor fault and switching the drive system to tolerant FOC mode without the rotor speed measurement. The effectiveness of the suggested FTC system is confirmed by experiments on a 0.75kW TPIM drive platform.