A fault prediction method for catenary of high-speed rails based on meteorological conditions

Fault frequency of catenary is related to meteorological conditions. In this work, based on the historical data, catenary fault frequency and weather-related fault rate are introduced to analyse the correlation between catenary faults and meteorological conditions, and further the effect of meteorological conditions on catenary operation. Moreover, machine learning is used for catenary fault prediction. As with the single decision tree, only a small number of training samples can be classified correctly by each weak classifier, the AdaBoost algorithm is adopted to adjust the weights of misclassified samples and weak classifiers, and train multiple weak classifiers. Finally, the weak classifiers are combined to construct a strong classifier, with which the final prediction result is obtained. In order to validate the prediction method, an example is provided based on the historical data from a railway bureau of China. The result shows that the mapping relation between meteorological conditions and catenary faults can be established accurately by AdaBoost algorithm. The AdaBoost algorithm can accurately predict a catenary fault if the meteorological conditions are provided. Document type: Articl

Enhanced Crystallinity of Triple-Cation Perovskite Film via Doping NH\u3csub\u3e4\u3c/sub\u3eSCN

The trap-state density in perovskite films largely determines the photovoltaic performance of perovskite solar cells (PSCs). Increasing the crystal grain size in perovskite films is an effective method to reduce the trap-state density. Here, we have added NH4SCN into perovskite precursor solution to obtain perovskite films with an increased crystal grain size. The perovskite with increased crystal grain size shows a much lower trap-state density compared with reference perovskite films, resulting in an improved photovoltaic performance in PSCs. The champion photovoltaic device has achieved a power conversion efficiency of 19.36%. The proposed method may also impact other optoelectronic devices based on perovskite films

Efficient Planar Heterojunction Perovskite Solar Cells with Li-doped Compact TiO\u3csub\u3e2\u3c/sub\u3e Layer

Perovskite solar cells (PSCs) have been developed rapidly in recent time, and efficient planar PSCs are regarded as the most promising alternative to the Si solar cells. In this study, we demonstrated that Li-doping of compact TiO2 can reduce the density of electron traps and increase the conductivity of the electron transport layer (ETL) of PSCs. Due to the improved electronic property of ETL, the Li-doped compact TiO2 based planar heterojunction PSCs exhibit negligible hysteretic J-V behavior. Comparing with the undoped compact TiO2 based PSCs, the power conversion efficiency (PCE) of the Li-doped compact TiO2 film based PSCs is improved from 14.2% to 17.1%. Fabrication of highly efficient planar PSCs provides a pathway for commercialization of PSCs

Large-scale Synthesis of β-SiC Nanochains and Their Raman/Photoluminescence Properties

Although the SiC/SiO2 nanochain heterojunction has been synthesized, the chained homogeneous nanostructure of SiC has not been reported before. Herein, the novel β-SiC nanochains are synthesized assisted by the AAO template. The characterized results demonstrate that the nanostructures are constructed by spheres of 25–30 nm and conjoint wires of 15–20 nm in diameters. Raman and photoluminescence measurements are used to explore the unique optical properties. A speed-alternating vapor–solid (SA-VS) growth mechanism is proposed to interpret the formation of this typical nanochains. The achieved nanochains enrich the species of one-dimensional (1D) nanostructures and may hold great potential applications in nanotechnology

Manufacturing and Supply Chain Flexibility: Building an Integrative Conceptual Model Through Systematic Literature Review and Bibliometric Analysis

The purpose of this study is twofold: first, to establish the current themes on the topic of manufacturing and supply chain flexibility (MSCF), assess their level of maturity in relation to each other, identify the emerging ones and reflect on how they can inform each other, and second, to develop a conceptual model of MSCF that links different themes connect and highlight future research opportunities. The study builds on a sample of 222 articles published from 1996 to 2018 in international, peer-reviewed journals. The analysis of the sample involves two complementary approaches: the co-word technique to identify the thematic clusters as well as their relative standing and a critical reflection on the papers to explain the intellectual content of these thematic clusters. The results of the co-word analysis show that MSCF is a dynamic topic with a rich and complex structure that comprises five thematic clusters. The value chain, capability and volatility clusters showed research topics that were taking a central role in the discussion on MSCF but were not mature yet. The SC purchasing practices and SC planning clusters involved work that was more focused and could be considered more mature. These clusters were then integrated in a framework that built on the competence–capability perspective and identified the major structural and infrastructural elements of MSCF as well as its antecedents and consequences. This paper proposes an integrative framework helping managers keep track the various decisions they need to make to increase flexibility from the viewpoint of the entire value chain

60 GHz mixer

This interim report aims to give the reviewer the knowledge and understanding of the subject matter: the 60 GHz mixer. Simulating an IEEE based research paper is an important way to achieving a better understanding of more efficient mixer. First, this is demonstrated by a brief, concise and non-exhaustive literature review at hand. The key concepts shall be discussed. Next is a brief discussion of the practical methodology in simulating this circuit. This also includes the personal mastery and understanding of the proprietary industrial software, Cadence SpectreRF. This shall be capped off with a brief run on future considerations.Bachelor of Engineerin

A Nonlinear Calibration Algorithm Based on Harmonic Decomposition for Two-Axis Fluxgate Sensors

Nonlinearity is a prominent limitation to the calibration performance for two-axis fluxgate sensors. In this paper, a novel nonlinear calibration algorithm taking into account the nonlinearity of errors is proposed. In order to establish the nonlinear calibration model, the combined effort of all time-invariant errors is analyzed in detail, and then harmonic decomposition method is utilized to estimate the compensation coefficients. Meanwhile, the proposed nonlinear calibration algorithm is validated and compared with a classical calibration algorithm by experiments. The experimental results show that, after the nonlinear calibration, the maximum deviation of magnetic field magnitude is decreased from 1302 nT to 30 nT, which is smaller than 81 nT after the classical calibration. Furthermore, for the two-axis fluxgate sensor used as magnetic compass, the maximum error of heading is corrected from 1.86° to 0.07°, which is approximately 11% in contrast with 0.62° after the classical calibration. The results suggest an effective way to improve the calibration performance of two-axis fluxgate sensors

Single-Dimension Perturbation Glowworm Swarm Optimization Algorithm for Block Motion Estimation

In view of the fact that the classical fast motion estimation methods are easy to fall into local optimum and suffer the high computational cost, the convergence of the motion estimation method based on the swarm intelligence algorithm is very slow. A new block motion estimation method based on single-dimension perturbation glowworm swarm optimization algorithm is proposed. Single-dimension perturbation is a local search strategy which can improve the ability of local optimization. The proposed method not only has overcome the defect of falling into local optimum easily by taking use of both the global search ability of glowworm swarm optimization algorithm and the local optimization ability of single-dimension perturbation but also has reduced the computation complexity by using motion vector predictor and terminating strategies in view of the characteristic of video images. The experimental results show that the performance of the proposed method is better than that of other motion estimation methods for most video sequences, specifically for those video sequences with violent motion, and the searching precision has been improved obviously. Although the computational complexity of the proposed method is slightly higher than that of the classical methods, it is still far lower than that of full search method