Northwestern Polytechnical University
Recent publications
Extensive solutions have been proposed to damp LCL filter resonance. However, the time delay caused by computation and modulation process aggravates the complexity of current loop analysis. In this paper, a generalized virtual impedance model for six kinds of commonly used active damping methods is proposed, and the physical meaning is established by introducing the metric of “damping factor”. To ensure system robustness in a wide range of grid conditions, a hybrid active damping strategy that combines inverter current feedback and capacitor voltage feedforward is proposed. Importantly, this method only requires inverter current and capacitor voltage sensors, which are the basic variables for over-current protection, power control and synchronization. The superposition theorem is also utilized to analyze the damping capability provided by parasitic resistances, current feedback loop and voltage feedforward loop. Finally, experimental results verify the feasibility and robustness of the proposed damping method.
The paralleled bidirectional interlinking converters (BILCs) of the hybrid AC/DC microgrid (HMG) provide a flexible and reliable power interaction way between AC and DC subgrids with high power density. A distributed unified control (DUC) is proposed for BILCs to achieve both resilience reinforcement and global economic operation of the HMG. For distributed generators (DGs), the $f_{ac}-\lambda _{ac}$ and $v_{dc}-\lambda _{dc}$ economic droop controls are employed for AC DGs and DC DGs to decrease the individual subgrid's generation expense by equaling DGs' incremental expenses (IEs). For BILCs, the normalized AC subgrid's frequency and DC subgrid's voltage are coordinated to achieve the economic power interaction (EPI), which further decreases the total generation expense (TGE). Besides economic operation, the proposed DUC is capable of adopting different MG operation modes into a unified control structure without any mode switching. Paralleled BILCs are managed to reinforce the system resilience by supporting the DC voltage or AC voltage once all DC or AC DGs fail. In addition, the proposed DUC enables BILCs with plug-and-play characteristics, resistance to the maximum acceptable communication delay, and the communication disruption robustness. The corresponding hardware-in-the-loop (HIL) results verify the effectiveness of the proposed control strategy.
Phase-locked loops (PLL) are increasingly used for position and speed estimation in speed sensorless control of permanent-magnet synchronous motors (PMSMs). In this paper, the saddle point characteristic phase-portrait is developed to explore the undesirable oscillation phenomena of PLL-based position and speed estimators for speed sensorless control. First, the large-signal model of the PLL-based position and speed estimator is established. Then, the saddle point phase-portrait method and Lyapunov-based argument are adopted to characterize its performance. It is revealed that the PLL-based position and speed estimator has infinite convergence regions. When the system state jumps from one convergence region to another, it will induce undesirable oscillations. Experimental tests are provided to verify the effectiveness of the proposed saddle point characteristic phase-portrait-based analysis.
Evidence theory provides an effective representation and handling framework for uncertain information. However, the quantification for the uncertainty of mass function in this theory is still an unsolved problem. For two types of uncertainty involved in evidence theory, conflict, and nonspecificity, many measurement methods have been proposed on the basis of requirements of axiomatic conditions. However, these existing methods proposed to measure the uncertainty of mass function are of deficiencies more or less, such as low sensitivity, counter-intuition, dispute on maximum entropy, and so on. In order to overcome the above defects, a total uncertainty measure based on the plausibility function, named as plausibility entropy, is proposed in this article, which provides a new solution to measure the uncertainty of the mass function. By embodying the plausibility function and plausibility transformation of every singleton in the frame of discernment, the new measure enlarges the Shannon’s entropy of equivalent probability mass function obtained using the plausibility transformation, and establishes a quantitative relationship between uncertainty measure and Dempster’s rule of combination. Compared with existing uncertainty measures, the proposed plausibility entropy is more sensitive to changes in a mass function. It also satisfies many desirable axiomatic properties, including non-negativity, maximum entropy, probability consistency, monotonicity, and so on. Moreover, the relationship among axiomatic properties of uncertainty measures is also discussed in this article. Numerical examples and comparison are provided to illustrate the effectiveness and rationality of the proposed plausibility entropy.
This work deals with the optimal epidemics policy-seeking problem on networks-of-networks (NoN) in the presence of unknown malicious adding-edge attacks. This problem is investigated in a framework of games-of-games (GoG), in which the conflicts between each network policymaker and the attacker are captured by a series of the Stackelberg games, while all network policymakers together compose a Nash game. First, the tolerable maximum attack magnitude is investigated and given implicitly. Then, we prove the existence of the gestalt Nash equilibrium (GNE) under mild attacks bounded by the above magnitude. A Heuristic algorithm based on iterative geometric programming is proposed to seek the GNE of the above GoG, whose asymptotical convergence is verified. Correspondingly, a greedy Heuristic strategy for the malicious attacker to compromise the NoN topology is developed. The practicability and validity of the above theoretical results and algorithms are illustrated via a simulation example.
In this article, an improved model predictive static programming (MPSP) based fault-tolerant control (FTC) scheme is proposed to solve the attitude tracking control problem of the hypersonic vehicle (HSV). In the field of HSV, the MPSP technique has been applied successfully to solve guidance problems for its high computational efficiency. While we try to address the attitude control problem directly using it. The attitude model of HSV with uncertainty and disturbance, together with the fault model of aircraft body injury, are constructed firstly. The actuator of HSV is suffering from input constraints. Then, a feasible attitude control trajectory is generated by the improved MPSP method. The methodological innovation in this paper extends MPSP technique to the direct control of the attitude of HSV both in fixed and flexible final time. By utilizing the improved MPSP technique, the complexity of processing multiple constraints and the computation are reduced. The effectiveness of the designed FTC scheme is demonstrated through simulation under different cases with actuator constraints.
Unmanned aerial vehicles (UAV) can enhance wireless transmission security by improving the secrecy rate through relaying the legitimate transmission and injecting artificial noise to the eavesdroppers. However, due to the inherent mechanical energy consumption and the long-range signal propagation pathloss, the traditional cruising and hovering UAV relay modes are deficient in energy utilization and secrecy rate, respectively. Modeling of the secrecy energy efficiency with respect to UAV mode adaptation is limited in the literature and deserves further investigation. Therefore, in this paper, we propose a secrecy rate-energy efficient UAV relay mode adaptation scheme for secure wireless communications scenarios where the eavesdropping locations are known, i.e., the eavesdropper is a hijacked internal legitimate node. In this secure system, the UAV cooperatively assists the legitimate transmissions and injects artificial interference to the eavesdropper. We investigate optimum UAV placement and relay period planning for the hovering and the cruising relay modes, respectively. By modeling the UAV modes transfer and maximizing the secrecy energy efficiency, the optimum mode adaptation ratios are obtained under both the secrecy rate-prioritized and the energy-saving criteria. In addition, the proposed UAV relay mode adaptation mechanism is further studied for each UAV task division, to adapt to the dynamic channel variations and enhance the security. Our theoretical analysis shows that the mode adaptation ratio is determined by the secrecy rate-energy gain between the cruising and the hovering modes, and by the energy consumption threshold of the UAV relays. Our numerical results demonstrate that the proposed scheme achieves higher secrecy energy efficiency than the traditional schemes.
A folded half-wavelength micro-strip resonator with a stepped impedance structure (FSIR) is designed to extend the second harmonic and affect the strength of the external electromagnetic coupling. The FSIRs of electromagnetic mutual cancellation structure and strong electric coupling structures are designed to realize the design of narrowband and broadband filters with extended second harmonic, respectively. A T- junction is designed to cascade the two high-order filters to achieve high isolation between two channels. The duplexer is fabricated on a single piece of 2-in double-sided YBCO (YBa <sub xmlns:mml="" xmlns:xlink="">2</sub> Cu <sub xmlns:mml="" xmlns:xlink="">3</sub> O <sub xmlns:mml="" xmlns:xlink="">7</sub> ) thin film on a MgO substrate with a dimension of 34.86×26.30×0.50 mm <sup xmlns:mml="" xmlns:xlink="">3</sup> , a thickness of 0.5 mm, and a dielectric constant of 9.8. At 77K, the measured central frequency of the duplexer are 910 MHz and 1100MHz, the fractional bandwidths (FBW) are 2.19% and 18.18%, the out-of-band rejections are greater than 60 dB, the two second harmonic are located at 2.4 GHz and 2.5 GHz, the insertion loss is less than 0.20 dB, and the return losses are better than 16.1 dB and 17.2 dB. The test results of the duplexer are in good agreement with the simulated ones.
With the rapid development of More-Electric Aircrafts (MEAs), integrated starter-generator (ISG) with less volume and weight has become the development trend in aircraft power system applications. Advantages of high reliability and excellent power generation quality make the brushless wound-rotor synchronous starter-generator (BLWRSSG) most attractive candidate for the ISG system in aircraft application. In this paper, four key technologies to achieve a high-performance BLWRSSG are comprehensively reviewed, including 1) high-efficient brushless excitation technology, 2) high-performance starting control technology, 3) rotor position estimation technology, and 4) rotating rectifier fault diagnosis technology. In each key technology, the basic operation principle, merit and demerit, and application of different topologies or methods in the literature are discussed and compared in depth. This paper contributes to a thorough understanding of operation principle and key technologies of the BLWRSSG system, and provide a reference to researchers and engineers involved in research of aircraft ISG system.
Flexible solid-state Zn-ion batteries (ZIBs) have garnered considerable attention for next-generation power sources, but the corrosion, dendrite growth, and interfacial problems severely hinder their practical applications. Herein, a high-performance flexible solid-state ZIB with a unique heterostructure electrolyte is facilely fabricated through ultraviolet-assisted printing strategy. The solid polymer/hydrogel heterostructure matrix not only isolates water molecules and optimizes electric field distribution for dendrite-free anode, but also facilitates fast and in-depth Zn2+ transport in the cathode. The in situ ultraviolet-assisted printing creates cross-linked and well-bonded interfaces between the electrodes and the electrolyte, enabling low ionic transfer resistance and high mechanical stability. As a result, the heterostructure electrolyte based ZIB outperforms single-electrolyte based cells. It not only delivers a high capacity of 442.2 mAh g-1 with long cycling life of 900 cycles at 2 A g-1 , but also maintains stable operation under mechanical bending and high-pressure compression in a wide temperature range (-20 °C to 100 °C).
Reduced graphene oxide (rGO) supercapacitors usually featured poor capacitive characteristics. As a simple, nonclassical redox molecule, amino hydroquinone dimethylether was firstly coupled with rGO, which boosted rGO capacitance to 523...
Background Structural variations (SVs) refer to variations in an organism’s chromosome structure that exceed a length of 50 base pairs. They play a significant role in genetic diseases and evolutionary mechanisms. While long-read sequencing technology has led to the development of numerous SV caller methods, their performance results have been suboptimal. Researchers have observed that current SV callers often miss true SVs and generate many false SVs, especially in repetitive regions and areas with multi-allelic SVs. These errors are due to the messy alignments of long-read data, which are affected by their high error rate. Therefore, there is a need for a more accurate SV caller method. Result We propose a new method-SVcnn, a more accurate deep learning-based method for detecting SVs by using long-read sequencing data. We run SVcnn and other SV callers in three real datasets and find that SVcnn improves the F1-score by 2–8% compared with the second-best method when the read depth is greater than 5×. More importantly, SVcnn has better performance for detecting multi-allelic SVs. Conclusions SVcnn is an accurate deep learning-based method to detect SVs. The program is available at
Microorganisms capable of converting toxic selenite into elemental selenium (Se0) are considered an important and effective approach for bioremediation of Se contamination. In this study, we investigated the mechanism of reducing selenite to Se0 and forming Se nanoparticles (SeNPs) by food-grade probiotic Lactobacillus casei ATCC 393 (L. casei ATCC 393) through proteomics analysis. The results showed that selenite added during the exponential growth period of bacteria has the highest reduction efficiency, and 4.0 mM selenite decreased by nearly 95% within 72 h and formed protein-capped-SeNPs. Proteomics analysis revealed that selenite induced a significant increase in the expression of glutaredoxin, oxidoreductase, and ATP binding cassette (ABC) transporter, which can transport glutathione (GSH) and selenite. Selenite treatment significantly increased the CydC and CydD (putative cysteine and glutathione importer, ABC transporter) mRNA expression level, GSH content, and GSH reductase activity. Furthermore, supplementation with an additional GSH significantly increased the reduction rate of selenite, while GSH depletion significantly inhibited the reduction of selenite, indicating that GSH-mediated Painter-type reaction may be the main pathway of selenite reduction in L. casei ATCC 393. Moreover, nitrate reductase also participates in the reduction process of selenite, but it is not the primary factor. Overall, L. casei ATCC 393 effectively reduced selenite to SeNPs by GSH and nitrate reductase-mediated reduction pathway, and the GSH pathway played the decisive role, which provides an environmentally friendly biocatalyst for the bioremediation of Se contamination. IMPORTANCE Due to the high solubility and bioavailability of selenite, and its widespread use in industrial and agricultural production, it is easy to cause selenite to accumulate in the environment and reach toxic levels. Although the bacteria screened from special environments have high selenite tolerance, their safety has not been fully verified. It is necessary to screen out strains with selenite-reducing ability from nonpathogenic, functionally known, and widely used strains. Herein, we found food-grade probiotic L. casei ATCC 393 effectively reduced selenite to SeNPs by GSH and nitrate reductase-mediated reduction pathway, which provides an environmentally friendly biocatalyst for the bioremediation of Se contamination.
Developing robust oxygen reduction reaction (ORR) electrocatalysts with high activity and durability remains great challenging while noble metal aerogels (NMAs) hold great potential because of their hierarchically porous morphology, excellent activity, and self‐supported characteristic. Herein, a general molecular engineering strategy to synthesize molecule‐noble metal aerogels (M‐NMAs) via 3D assembly of metal nanoparticles (e.g., Pt, Pd, Au, Ag, and PtPd NPs) induced by metalloporphyrin as cross‐linkers is reported. Due to the well synergy of NMAs and porphyrin molecule in creating the facile reaction pathway for ORR catalysis, these M‐NMAs demonstrate boosted ORR activity and durability in different electrolytes. Particularly, the best PtPd‐based M‐NMA delivers 1.47 A mgPt⁻¹ and 2.13 mA cm⁻² in mass and specific activities, which are 11.3 and 14.2 times higher than those of the commercial Pt/C catalyst, respectively. Thus, this work not only provides a simple and universal functional engineering approach of NMAs with catalytic molecules, but also opens an avenue of the rational design for superior ORR electrocatalysts.
Aluminum hydride (AlH3) is a promising fuel component of solid propellant, but its stabilization is still challenging. Herein, surface functionalization of hydrophobic perfluoropolyether (PFPE) followed by ammonium perchlorate (AP) coating has been implemented. In particular, AlH3@PFPE@xAP (x = 10, 30, 50, or 64.21%) composites (AHFPs) were prepared by a spray-drying technique. The PFPE-functionalized AlH3 with a hydrophobic surface shows an increased water contact angle (WCA) from 51.87° to 113.54°. Compared with pure AlH3, the initial decomposition temperatures of AHFPs were increased by 17 °C, and the decomposition properties of AP in the AHFPs were also enhanced with significantly decreased peak temperature and fairly increased energy output. Moreover, the decomposition induction time of AHFPs-30% was improved by almost 1.82 times that of raw AlH3, which indicates that the coatings of PFPE and AP could improve the stability of AlH3. The maximum flame radiation intensity of AHFPs-30% was 21.6 × 103, which is almost 7.71 times that of pure AlH3 (2.8 × 103).
Research on human mobility drives the development of economy and society. How to predict when and where one will go accurately is one of the core research questions. Existing work is mainly concerned with performance of mobility prediction models. Since accuracy of predict models doesn’t indicate whether or not one’s mobility is inherently easy to predict, there has not been a definite conclusion about that to what extent can our predictions of human mobility be accurate. To help solve this problem, we describe the formalized definition of predictability of human mobility, propose a model based on additive Markov chain to measure the probability of exploration, and further develop an information theory based method for quantifying the predictability considering exploration of human mobility. Then we extend our method by using mutual information in order to measure the predictability considering external influencing factors, which has not been studied before. Experiments on simulation data and three real-world datasets show that our method yields a tighter upper bound on predictability of human mobility than previous work, and that predictability increased slightly when considering external factors such as weather and temperature.
Lung lobe segmentation in computed tomography (CT) images can be regarded as essential supporting information for the diagnosis and treatment of lung diseases, yet it is a challenging uncertainty for the complex segmentation task due to the diverse structures like indistinguishable pulmonary arteries and veins, unpredictable pathological deformation and blurring pulmonary fissures. To circumvent these challenges, we present a productive deep learning network based on multi‐feature fusion and ensemble learning approach to highlight pulmonary fissure representation and suppress other structures for lung lobe segmentation in CT images. Considering that pulmonary fissures are the physical boundaries of lung lobes, a multi‐feature fusion approach is presented to integrate original images, enhanced fissure magnitude images, and enhanced fissure orientation images to highlight shape representation for semantic segmentation. In addition, a deep‐supervised ensemble learning network is employed to combine multiple inducers for lung lobe segmentation improvement. The performance of the proposed deep learning model is validated in experiments with an available dataset, it acquired a high IoU value and a low Hausdorff distance compared with manual references. Experimental results demonstrate that the proposed computational model based on multi‐feature fusion and deep‐supervised ensemble learning framework has an improved predictive performance than many state‐of‐the‐art deep neural networks in lung lobe segmentation.
Luminescence clusters composed of organic ligands and metals have gained significant interests as scintillators owing to their great potential in high X-ray absorption, customizable radioluminescence, and solution processability at low temperatures. However, X-ray luminescence efficiency in clusters is primarily governed by the competition between radiative states from organic ligands and nonradiative cluster-centered charge transfer. Here we report that a class of Cu4I4 cubes exhibit highly emissive radioluminescence in response to X-ray irradiation through functionalizing biphosphine ligands with acridine. Mechanistic studies show that these clusters can efficiently absorb radiation ionization to generate electron-hole pairs and transfer them to ligands during thermalization for efficient radioluminescence through precise control over intramolecular charge transfer. Our experimental results indicate that copper/iodine-to-ligand and intraligand charge transfer states are predominant in radiative processes. We demonstrate that photoluminescence and electroluminescence quantum efficiencies of the clusters reach 95% and 25.6%, with the assistance of external triplet-to-singlet conversion by a thermally activated delayed fluorescence matrix. We further show the utility of the Cu4I4 scintillators in achieving a lowest X-ray detection limit of 77 nGy s⁻¹ and a high X-ray imaging resolution of 12 line pairs per millimeter. Our study offers insights into universal luminescent mechanism and ligand engineering of cluster scintillators.
Large‐area continuous covalent organic frameworks (COFs) film is highly desirable for the large‐scale continuous selective photocatalytic coupling of benzylamine (BA); however, traditional synthetic methods for preparing COFs films still suffer from the issues of harsh reaction condition, film breakage, and high energy‐consumption. Herein, a room‐temperature strategy is reported for making large‐area continuous imine‐based COFs film through the “infiltration‐reaction‐assembly” mechanism, demonstrating that such strategy is quite universal for making four types of large‐area COFs films. The as‐made PyTTA‐TPA (PyTTA: 1,3,6,8‐tetrakis(4‐aminophenyl)pyrene, TPA: p‐benzaldehyde) COFs film exhibits excellent catalytic performance for selective photocatalytic coupling of benzylamine (BA) with a high conversion rate of 98.2% and high selectivity of 97% in 3 h, which is the best photocatalytic performance in all reported photocatalysts. In addition, the as‐made COFs film is quite general for achieving photocatalytic coupling of other amine derivatives with outstanding photocatalytic performance of ≈100% conversion rate. Overall, this work brings a significant development for the room‐temperature synthesis of large‐area continuous COFs film to photocatalytic reaction.
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9,802 members
tang wei
  • School of Automation
Weihong Qi
  • School of Materials Science and Engineering
Ming Luo
  • Department of Advanced Manufacturing Engineering
Lei Du
  • School of Automation
Heng Li
  • School of Materials Science and Engineering
127 West Youyi Road, 710072, Xi’an, Shaanxi, China