High Frequency Errors Research Articles

Evaluation of brain nerve function in ICU patients with Delirium by deep learning algorithm-based resting state MRI.

The purpose of this study was to explore the value of resting-state magnetic resonance imaging (MRI) based on the brain extraction tool (BET) algorithm in evaluating the cranial nerve function of patients with delirium in intensive care unit (ICU). A total of 100 patients with delirium in hospital were studied, and 20 healthy volunteers were used as control. All the subjects were examined by MRI, and the images were analyzed by the BET algorithm, and the convolution neural network (CNN) algorithm was introduced for comparison. The application effects of the two algorithms were analyzed, and the differences of brain nerve function between delirium patients and normal people were explored. The results showed that the root mean square error, high frequency error norm, and structural similarity of the BET algorithm were 70.4%, 71.5%, and 0.92, respectively, which were significantly higher than those of the CNN algorithm (P < 0.05). Compared with normal people, the ReHo values of pontine, hippocampus (right), cerebellum (left), midbrain, and basal ganglia in delirium patients were significantly higher. ReHo values of frontal gyrus, middle frontal gyrus, left inferior frontal gyrus, parietal lobe, and temporal lobe and anisotropy scores (FA) of cerebellums (left), frontal lobe, temporal lobe (left), corpus callosum, and hippocampus (left) decreased significantly. The average diffusivity (MD) of medial frontal lobe, superior temporal gyrus (right), the first half of cingulate gyrus, bilateral insula, and caudate nucleus (left) increased significantly (P < 0.05). MRI based on the deep learning algorithm can effectively improve the image quality, which is valuable in evaluating the brain nerve function of delirium patients. Abnormal brain structure damage and abnormal function can be used to help diagnose delirium.

Quantitative susceptibility mapping using plug-and-play alternating direction method of multipliers

Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R2 = 0.98, p < 0.05) with COSMOS and no significant bias (bias = 0.007 ± 0.012). PnP-BM4D QSM achieved excellent quality when assessed using structural similarity index metric (SSIM = 0.860), high frequency error norm (HFEN = 58.5), cross correlation (CC = 0.804), and mutual information (MI = 0.475) and also maintained good conspicuity of fine features. In glioblastoma datasets, PnP-BM4D QSM showed higher performance (IQGrade = 2.4 ± 0.4, ISGrade = 2.7 ± 0.3, IQRank = 3.7 ± 0.3, ISRank = 3.9 ± 0.3) compared to MEDI (IQGrade = 2.1 ± 0.5, ISGrade = 2.1 ± 0.6, IQRank = 2.4 ± 0.6, ISRank = 2.9 ± 0.2) and FANSI-TGV (IQGrade = 2.2 ± 0.6, ISGrade = 2.1 ± 0.6, IQRank = 2.7 ± 0.3, ISRank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.

Reliability and accuracy of ultrasound image analyses completed manually versus an automated tool.

Analysis of Brightness-mode ultrasound-captured fascicle angle (FA) and fascicle length (FL) can be completed manually with computer-based programs or by automated programs. Insufficient data exists regarding reliability and accuracy of automated tools. Therefore, the purpose of this study was to determine the test-retest reliability of automatic and manual ultrasound analyses, while determining accuracy of the automatic tool against the manual equivalent. Twenty-three participants (mean ± SD; age = 24 ± 4 years; height = 172.2 ± 10.5 cm; body mass = 73.1 ± 16.1 kg) completed one laboratory visit consisting of two trials where vastus lateralis muscle architecture was assessed with ultrasound. Images were taken at both lower (10 MHz) and higher frequency (12 MHz). Images were analyzed manually in an open-source imaging program and automatically using a separate open-source macro function. Test-retest reliability statistics were calculated for automatic and manual analyses. Accuracy was determined with validity statistics and were calculated for automatic analyses. The results show that manual ultrasound analyses for FA and FL for both lower and higher frequency displayed good reliability (ICC2,1 = 0.75–0.86). However, automatic ultrasound analyses for FA and FL revealed moderate reliability (ICC2,1 = 0.61–0.72) for the lower frequency images and poor reliability (ICC2,1 = 0.16–0.27) for higher frequency images. When assessed against manual techniques, automatic analyses presented greater total error (TE) and standard error of the estimate (SEE) for FA at lower frequency (constant error (CE) = −3.91°, TE = 5.57°, SEE = 3.45°) than higher (CE = −2.78°, TE = −4.54°, SEE = 2.45°). For FL, the higher frequency error (CE = 0.92 cm, TE = 2.12 cm, SEE = 1.15 cm) was similar to lower frequency error (CE = 1.98 cm, TE = 3.66 cm, SEE = 1.57 cm). The findings overall show that manual analyses had good reliability and low absolute error, while demonstrating the automated counterpart had poor to moderate reliability and large errors in analyses. These findings may be impactful as they highlight the good reliability and low error associated with manually analyzed ultrasound images and validate a novel automatic tool for analyzing ultrasound images. Future work should focus on improving reliability and decreasing error in automated image analysis tools. Automated tools are promising for the field as they eliminate biases between analysts and may be more time efficient than manual techniques.

Smooth polishing with non-linear compensation

ObjectiveSmooth polishing has a good improvement on the medium and high frequency errors of the workpiece, but the surface accuracy of the workpiece will be damaged subsequently. MethodsTherefore, a nonlinear compensation method is proposed. The realization mechanism, mathematical model and compensation effect of nonlinear compensated smooth polishing are illustrated separately and verified by experiments. In addition, the process parameters and motion trajectory are optimized by theoretical simulation. ResultThe experimental results demonstrate that the full-band error of the workpiece can be improved simultaneously by the smooth polishing method based on nonlinear compensation. SignificanceThe number of iterations for the figuring experiments and smooth polishing is greatly reduced by the nonlinear compensation model, which is significantly beneficial to improve the surface convergence speed and lower the manufacturing cost.

Amplitude compensation using homodyne detection for inverse synthetic aperture LADAR.

Inverse synthetic aperture LADAR (ISAL), based on an electro-optic in-phase and quadrature (I/Q) modulator, and homodyne detection, has high pulse repetition frequency, simple structure, and minimum intra-pulse phase errors. Homodyne detection can implement the de-chirp operation in the optical domain, while the output amplitude is susceptible to light intensity. However, the modulated optical signal amplitude fading, induced by radio frequency devices and the I/Q modulator, is quite tricky to measure and be compensated for. In this work, the effect of amplitude distortion on the ISAL system is analyzed. A simple and effective compensation method (based on homodyne detection) is proposed, followed by some experiments. The improvement of homodyne signal power to the compensated signal compared with non-compensated signal was about 1 dB (26%), and the image quality of our ISAL system along range direction was also improved by using the proposed method. Moreover, the image of an extended target was acquired via our ISAL system with 500 mW transmitting power at a distance of 1.1 km.

Expanding the Non-Invasive Diagnosis of Acute Rejection in Kidney Transplants Through Detection of Donor-Derived DNA in Urine: Proof-of-Concept Study.

BackgroundApproximately 10%-20% of kidney transplant (KT) recipients suffer from acute rejection (AR); thus, sensitive and accurate monitoring of allograft status is recommended. We evaluated the clinical utility of donor-derived DNA (dd-DNA) detection in the urine of KT recipients as a non-invasive means for diagnosing AR.MethodsUrine samples serially collected from 39 KT recipients were tested for 39 single-nucleotide variant loci selected according to technical criteria (i.e., high minor allele frequency and low analytical error) using next-generation sequencing. The fraction of dd-DNA was calculated and normalized by the urine creatinine (UCr) level (%dd-DNA/UCr). The diagnostic performance of %dd-DNA/UCr for AR was assessed by ROC curve analysis.ResultsThere was an increasing trend of %dd-DNA/UCr in the AR group before subsequent graft injury, which occurred before (median of 52 days) histological rejection. The serum creatinine (SCr) level differed significantly between the AR and non-AR groups at two and four months of follow-up, whereas %dd-DNA/UCr differed between the groups at six months of follow-up. The combination of %dd-DNA/UCr, SCr, and spot urine protein (UPtn)/UCr showed high discriminating power, with an area under the ROC curve of 0.93 (95% confidence interval 0.81-1.00) and a high negative predictive value of 100.0%.ConclusionsAlthough the dd-DNA-based test cannot eliminate the need for biopsy, the high negative predictive value of this marker could increase the prebiopsy probability of detecting treatable injury to make biopsy an even more effective diagnostic tool.

Real-time clock recovery algorithm with high clock frequency offset tolerance

We propose a full real-time clock recovery algorithm based on the Gardner algorithm with extended first-in-first-out (FIFO), data buffer, and add/delete state machine parts. The proposed algorithm has long-term stable bit error rate (BER) performance as well as tolerates a maximum clock frequency offset up to 330 ppm when we conducted a real-time experiment with high clock frequency errors on the Altera Stratix-V 5SGXMA7K2F40C3 FPGA platform with a symbol rate of 2.5 GBaud.

Diagnosis and prognosis of epidemic inflammatory bowel disease under convolutional neural network algorithm and nonlinear equation model

this study was to analyze the effect of optimization algorithm based on convolutional neural network (CNN) on the image quality of magnetic resonance enterography (MRE) for small intestine, and explore the diagnosis and prognosis of epidemic inflammation bowel disease (IBD) with the MRE under the optimization algorithm and nonlinear equation model. The residual network structure (RNS) was incorporated into the CNN algorithm to establish an optimization algorithm, which was compared with other algorithms in terms of the peak signal to noise ratio (PSNR), structural similarity (SSIM), and high frequency error norm (HFEN). 392 patients suspected as IBD in the Gastroenterology Department were selected as the research objects. They were divided into a Crohn’s disease (CD) group (243 cases), an ulcerative colitis (UC) group (78 cases), an indeterminate enteritis (IDE) group (49 cases), and a non-IBD group (22 cases). The intestinal manifestations, clinical manifestations, MRE imaging manifestations, and gastrointestinal lesion distribution of patients in different groups were compared to analyze the diagnostic value of MRE for epidemic IBD. It was found that the optimized CNN algorithm showed better PSNR, SSIM, and HFEN than other algorithms. The percentages of patients with diarrhea in the CD group and UC group were 67.90% and 100%, respectively. The pediatric ulcerative colitis activity index (PUCAI) score of patients in the UC group showed that the number of patients with mild activity was at most 40 (51.28%). The Crohn’s disease activity index (CDAI) score showed that there were 197 of patients in the CD group (81.07%) with severe activity. In the CD group, the numbers of patients suffered with lesions in proximal colon, terminal ileum, and upper gastrointestinal tract were 125 (51.44%), 127 (52.26%), and 132 (54.32%), respectively. In the UC group, there were 32 (41.03%), 51 (65.38%), and 25 (32.05%) patients with lesions in the rectum, distal colon, and proximal colon, respectively. The diagnostic sensitivity and specificity of MRE for epidemic IBD was 95.18% and 46.7%, respectively. It indicated that the image quality of the optimization algorithm based on the CNN algorithm was improved greatly. Under the nonlinear equation model, the image characteristics of MRE in patients with different diseases were various, and the diseased parts were greatly different. MRE showed high sensitivity and specificity in the diagnosis of epidemic IBD. This study could provide a reference basis for the clinical diagnosis and prognosis of patients with epidemic IBD.

Numerical study on spatial scale characteristics of sound scattering by a static isentropic vortex

The scattering of acoustic waves by a vortex is a fundamental problem of the acoustic waves propagation in complex flow field, which plays an important role in academic research and engineering application for sound source localization, acoustic target recognition and detection, the far field noise prediction, such as aircraft wake vortex identification, detection and ranging, acoustic target forecasting in turbulent shear flow, acoustic measurement and sound source localization in wind tunnel test, etc. The nonlinear scattering phenomenon occurs when acoustic wave passes through the vortex, which is mainly related to the length-scale ratio between the wavelength of acoustic wave and the core radius of the vortex. In this paper, a plane acoustic wave passing through a stationary isentropic vortex is numerically simulated by solving a two-dimensional compressible, unsteady Euler equation. A sixth-order linear compact finite difference scheme is employed for spatial discretization. Time integration is performed by a four-stage fourth-order Runge-Kutta method. The eighth-order spatial compact filter scheme is adopted to suppress high frequency errors. At the far field boundaries, buffer layer is applied to handle the outgoing acoustic wave. Under the matching condition, the accuracy of the numerical results is verified by comparing with the previous direct numerical simulation results. The acoustic scattering cross-section method is introduced to analyze the effects of different length-scale ratio on the acoustic pulsation pressure, acoustic scattering effective sound pressure and acoustic scattering energy. Scattering occurs when sound waves pass through the vortex, the acoustic field in front of the vortex is basically unaffected, and the acoustic wave front remains intact. A “vacuum” region is formed slightly below the acoustic field directly behind the vortex, and two primary interference bands and several secondary interference bands are formed on the upper and lower sides of the vortex. As the length-scale ratio increases, the sound scattering decreases and the influence of the vortex flow field on the acoustic field gradually weakens. The influence region of effective sound pressure of acoustic scattering is mainly concentrated behind the vortex. With the increase of the length scale ratio, the influence gradually increases and extends to the upstream, and then the influence region gradually decreases to the vicinity of the vortex. When the length scale ratio is greater than or equal to 6, the location of the maximum effective sound pressure of sound scattering jumps from the upper right to the lower right of the vortex. The influence of acoustic wave wavelength change on the acoustic scattering energy can be divided into three parts. With the increase of the length scale ratio, the maximum sound scattering energy presents four different stages.

Deep Learning Approach for Generating MRA Images From 3D Quantitative Synthetic MRI Without Additional Scans.

Quantitative synthetic magnetic resonance imaging (MRI) enables synthesis of various contrast-weighted images as well as simultaneous quantification of T1 and T2 relaxation times and proton density. However, to date, it has been challenging to generate magnetic resonance angiography (MRA) images with synthetic MRI. The purpose of this study was to develop a deep learning algorithm to generate MRA images based on 3D synthetic MRI raw data. Eleven healthy volunteers and 4 patients with intracranial aneurysms were included in this study. All participants underwent a time-of-flight (TOF) MRA sequence and a 3D-QALAS synthetic MRI sequence. The 3D-QALAS sequence acquires 5 raw images, which were used as the input for a deep learning network. The input was converted to its corresponding MRA images by a combination of a single-convolution and a U-net model with a 5-fold cross-validation, which were then compared with a simple linear combination model. Image quality was evaluated by calculating the peak signal-to-noise ratio (PSNR), structural similarity index measurements (SSIMs), and high frequency error norm (HFEN). These calculations were performed for deep learning MRA (DL-MRA) and linear combination MRA (linear-MR), relative to TOF-MRA, and compared with each other using a nonparametric Wilcoxon signed-rank test. Overall image quality and branch visualization, each scored on a 5-point Likert scale, were blindly and independently rated by 2 board-certified radiologists. Deep learning MRA was successfully obtained in all subjects. The mean PSNR, SSIM, and HFEN of the DL-MRA were significantly higher, higher, and lower, respectively, than those of the linear-MRA (PSNR, 35.3 ± 0.5 vs 34.0 ± 0.5, P < 0.001; SSIM, 0.93 ± 0.02 vs 0.82 ± 0.02, P < 0.001; HFEN, 0.61 ± 0.08 vs 0.86 ± 0.05, P < 0.001). The overall image quality of the DL-MRA was comparable to that of TOF-MRA (4.2 ± 0.7 vs 4.4 ± 0.7, P = 0.99), and both types of images were superior to that of linear-MRA (1.5 ± 0.6, for both P < 0.001). No significant differences were identified between DL-MRA and TOF-MRA in the branch visibility of intracranial arteries, except for ophthalmic artery (1.2 ± 0.5 vs 2.3 ± 1.2, P < 0.001). Magnetic resonance angiography generated by deep learning from 3D synthetic MRI data visualized major intracranial arteries as effectively as TOF-MRA, with inherently aligned quantitative maps and multiple contrast-weighted images. Our proposed algorithm may be useful as a screening tool for intracranial aneurysms without requiring additional scanning time.

Stable and Accurate Filtering Procedures

High frequency errors are always present in numerical simulations since no difference stencil is accurate in the vicinity of the pi -mode. To remove the defective high wave number information from the solution, artificial dissipation operators or filter operators may be applied. Since stability is our main concern, we are interested in schemes on summation-by-parts (SBP) form with weak imposition of boundary conditions. Artificial dissipation operators preserving the accuracy and energy stability of SBP schemes are available. However, for filtering procedures it was recently shown that stability problems may occur, even for originally energy stable (in the absence of filtering) SBP based schemes. More precisely, it was shown that even the sharpest possible energy bound becomes very weak as the number of filtrations grow. This suggest that successful filtering include a delicate balance between the need to remove high frequency oscillations (filter often) and the need to avoid possible growth (filter seldom). We will discuss this problem and propose a remedy.

High‐performance dynamic magnetic resonance image reconstruction and synthesis employing deep feature learning convolutional networks

AbstractThis research paper shows an effective deformable complex 3D image reconstruction and image synthesis technique by consolidating needed high‐level features from convolutional Neural Network (CNN) system. By recognize inherent deep feature representations in image patches for morphological changes in medicinal imaging information discovery. Various performance measurements, High Frequency Error Norm (HFEN), Mean Squared Error MSE, peak Signal‐to‐noise‐ratio (PSNR), Structural Similarity Index (SSI), are utilized to inspect different dataset. As presented in the paper outcomes, the proposed method can accomplish predominant performance compared with other cutting‐edge techniques with either low or high‐level features in terms of the synthesis and reconstruction rate. The proposed deep learning algorithm has a training time of 5 seconds with 0.97 SSI and 0.15 HFEN. In all investigations, the outcome shows that the proposed image synthesis and reconstruction framework reliably exhibited progressively precise outcomes when contrasted with best in class.

Pseudospecteral method with linear damping effect and de-aliasing technique in solving nonlinear PDEs

Pseudospectral method is an alternative of finite differences and finite elements method to solve nonlinear partial differential equations (PDEs), especially in nonlinear waves. The Pseudospectal method is very efficient because it use the fast fourier transform to calculate discrete Fourier transform in the algorithm. In this paper, the Pseudospectral scheme is modified by adding the linear damping effect and de-aliasing technique, and has been tested in Ostrovsky equation, where Ostrovsky equation is a modified of Korteweg-de Vries equation with an addition of background Earth’s rotation. The addition of the linear damping is to prevent the possibility of radiated waves re-entering from the boundaries and disturbing the main wave structure. Most of the numerical simulations occur with the aliasing errors due to pollution of numerically calculated Fourier transform by higher frequencies component because of the truncation of the series. To prevent this, the de-aliasing technique is implemented on the nonlinear term and linear damping region by setting of the amplitudes to be zero at the end of both boundaries. Therefore, the simulation results of Pseudospectral method will be smooth without any high frequency errors even for the high amplitude of the waves from initial condition.

Research on PMSM Low-speed Sensorless Control Strategy based on Rotating High Frequency Injection Method

In this paper, by studying the Permanent Magnet Synchronous Motor (PMSM) position sensorless control strategy, a method for error compensation of current responsed by high frequency error signal is proposed. Since the high-frequency carrier current contained in the stator current causes the erroneous adjustment of the current regulator, the control system contains a high-frequency error signal, which affects the motor rotor position and speed estimation accuracy. The high-frequency error voltage signal is extracted in the stationaryα − β coordinate system, and the high-frequency error response current in the stator current is estimated, and the estimation system is compensated. The PMSM position sensorless control system based on the rotating high frequency voltage injection method and the Matlab-Simulink system model of the error compensation are established. The results show that the speed and position estimation are more accurate after error compensation, and the steady-state error is smaller, which improves the smoothness of the motor at low speed.

Real time monitoring technology for full aperture grating diffraction wavefront with high frequency error

To improve the grating ruling efficiency and success rate, this report documents a method to indirectly measure the error trajectory of space coordinates produced by ruling and indexing systems. The errors were corrected based on the proposed active control system. According to the residual errors after correction, a mathematical model of the full aperture grating diffraction wavefront with high frequency error information was reconstructed in real time. Based on this mathematical model, two gratings were ruled with or without the aid of an error correction system, respectively, and the reconstructed grating diffraction wavefront values were obtained to verify the effectiveness of this method. For larger gratings, the grating diffraction wavefront can also be reconstructed in real time with long time ruling. The experimental result demonstrated that the grating quality can be judged by monitoring the grating diffraction wavefront in real time.

An Analysis of Errors in Online English Writing made by Thai EFL Authors

English writing produced by Thai EFL authors inevitably contains errors of various types. Errors can lead to not only wrong interpretations but also unfavorable criticism. This study is an endeavor to examine errors of English writing made by Thai EFL authors on the Tourism Authority of Thailand Website and to suggest revisions to each error found. To do this, the information on tourist destinations in five provinces in the lower north of Thailand, namely, Phitsanulok, Sukhothai, Phetchabun, Uttaradit, and Tak, was collected. The gathered data consisted of 230 pieces of the information which contained 2,559 sentences. The data were analyzed by applying the framework of Dulay, Burt, &amp; Krashen’s surface structure taxonomy (1982). The results revealed that almost half of all the considered sentences (44.78%) contained errors. Based on the framework, errors of omission were found to be the most frequent, followed by those of misformation, addition, and misordering, respectively. Interestingly, the results also showed that the mechanical errors, not in the list of the framework, occurred with the highest frequency. Based upon research findings, online English writing made by Thai EFL authors need more proofreading, especially on the types of errors committed at the highest frequency according to or beyond the framework. However, in focusing on high frequency errors, it is to be noted that miscellaneous occurred the least yet should not be ignored in the correcting process.

Non-Linear Mathematical Modelling for Phase Locked Loop

Design of Phase Locked Loop (PLL) plays a vital role in transceiver field. Phase Locked Loop comprises of three blocks, namely Phase and frequency detector, loop filter and voltage-controlled oscillator. The greater advancements in CMOS technology such as high frequency, high speed, low noise and phase error leads to low-cost PLL This work aims to develop higher order non-linear models of general Phase Locked Loop. The condition of stability and choice of loop filter is also determined. Based on the analysis, the transfer function for PLL is determined.

Improving the performance of single point diamond turning surface with ion beam figuring

Single point diamond turning (SPDT) can directly produce high precision optical parts, but some regularity micro structure in residual surface, and turning processing characteristics limit the surface quality to further improve. Ion beam figuring (IBF), as the last process of optical processing, can remove certain mid and high frequency errors, improve the surface performances without destroying their forms. Therefore, it is proposed to combine SPDT and IBF to manufacturing ultra-high precision surface. Two samples of diamond-turned sphere aluminum mirror were used in this experiment. One samples with surface PV and RMS 226 nm and 12.6 nm decreased to 113 nm and 7.7 nm after ion beam figuring, another sample was improved in the same degree, and the turning marks is removed with surface roughness decreased to 2.8 nm from 3 nm. The experimental results indicate that IBF can remove the turning marks and improve the surface precision in a certain range without destroying the surface form.

Hybrid Modulated Model Predictive Control in a Modular Multilevel Converter for Multi-Terminal Direct Current Systems

In this paper a hybrid modulated model predictive control (HM2PC) strategy for modular-multilevel-converter (MMC) multi-terminal direct current (MTDC) systems is proposed for supplying power to passive networks or weak AC systems, with the control objectives of maintaining the DC voltage, voltage stability and power balance of the proposed system. The proposed strategy preserves the desired characteristics of conventional model predictive control method based on finite control set (FCS-MPC) methods, but deals with high switching frequency, circulating current and steady-state error in a superior way by introducing the calculation of the optimal output voltage level in each bridge arm and the specific duty cycle in each Sub-Module (SM), both of which are well-suited for the control of the MMC system. In addition, an improved multi-point DC voltage control strategy based on active power balanced control is proposed for an MMC-MTDC system supplying power to passive networks or weak AC systems, with the control objective of coordinating the power balance between different stations. An MMC-HVDC simulation model including four stations has been established on MATLAB/Simulink (r2014b MathWorks, Natick, MA, USA). Simulations were performed to validate the feasibility of the proposed control strategy under both steady and transient states. The simulation results prove that the strategy can suppress oscillations in the MMC-MTDC system caused by AC side faults, and that the system can continue functioning if any one of the converters are tripped from the MMC-MTDC network.

Study on Surface Morphology of Vibration Assisted Cutting

Vibration assisted cutting is widely regarded as an effective technique due to the characteristics of friction reversal and intermittent cutting. However, there are few studies on surface morphology of vibration assisted cutting machining. The high frequency error (surface roughness) and low frequency error (surface error) of the surface topography are obtained by the decomposition and reconstruction of the wavelet packet in this paper for the in-depth investigating of the surface morphology. The influence of vibration assisted cutting parameters on surface topography are revealed by calculating the surface evaluation parameters such as surface roughness, PV value and root mean square error. In this paper, two-dimensional wavelet packet analysis is conducted on the surface morphology of vibration assisted cutting. Finally, the influence of surface roughness and shape error on vibration assisted cutting are obtained. Through the analysis, it can be found that, along with the increase of the minor axis of vibration assisted cutting parameters, the surface roughness, PV value and root mean square deviation become larger during the processing.