基于Stateflow电力机车变流器控制设计与实现

某出口型号交流电力机车牵引控制系统要求变流器控制逻辑具备接触器控制、牵引系统数据交互、变流器故障保护、变流器启动自检等功能。针对以上功能,基于MATLAB中的Simulink/Stateflow可视化编程工具进行牵引控制模型的搭建,遵循模块化编程理念,采用较少的程序代码编写实现复杂的逻辑控制模型,生成逻辑清晰的控制功能流程图,进行半实物仿真测试,增强控制模型的可靠性。通过该变流器产品型式试验检验,验证变流器控制逻辑的功能可以满足控制系统的需求。     

Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

Decomposition of first-order hybrid Petri nets for hierarchical control of manufacturing systems

Although hybrid Petri net (HPN) is a popular formalism in modelling hybrid production systems, the HPN model of large scale systems gets substantially complicated for analysis and control due to large dimensionality of such systems. To overcome this problem, a typical approach is to decompose the net into subnets and then control the plant through hierarchical or decentralized structures. Although this concept has been widely discussed in the literature for discrete PNs, there is a lack of research for HPNs. In this paper, a new method of decomposition of first-order hybrid Petri nets (FOHPNs) is proposed first and then the hierarchical control of the subnets through a coordinator is introduced. The advantage of using the proposed approach is validated by an existing example. A sugar milling case study is analysed by using a decomposed FOHPN model and the optimization results are compared against the results of the approaches presented in other papers. Simulation results show not only an improvement in production rate, but also show the ability to control the plant online. In addition, by using the hierarchical control structure for an FOHPN model, it is possible to reduce the cost of communication links, improve the reliability of the system, maintain the plant locally, and partially redesign the system.     

Characteristics and formation mechanism of porosities in CFRP during laser joining of CFRP and steel

An experimental investigation on the mechanism of porosity formation during the laser joining of carbon fiber reinforced polymer (CFRP) and steel is presented. The porosity morphology and distribution were characterized by optical and scanning electron microscopy, and the thermal pyrolysis behaviors were investigated by thermal analysis and designed back-side cooling experiments. The results show that there are two types of porosities in CFRP. Porosity I only appears when the heat input is more than 77.8 J/mm. It has a smooth inner wall and distributes near the bonding interface between CFRP and steel at the central area of melted zone, which is caused by gaseous products such as CO₂, NH₃, H₂O, and hydrocarbons produced by the pyrolysis of CFRP. Porosity II can be seen under all joining conditions. It has a rough inner wall and distributes far away from the bonding interface, concentrating at the final solidification locations. Porosity II is caused by the shrinkage of melted CFRP during solidification stage.     

不同晶相结构ZrO2负载铜基催化剂用于二乙醇胺脱氢反应

通过制备不同晶相结构〔单斜相(m-ZrO_2)、四方相(t-ZrO_2)和无定型(a-ZrO_2)〕ZrO_2载体,再通过沉积沉淀法制得Cu/m-ZrO_2、Cu/t-ZrO_2和Cu/a-ZrO_2催化剂,分别用于催化二乙醇胺脱氢合成亚氨基二乙酸反应。采用XRD、氮气物理吸附脱附、XPS、H_2-TPR、CO_2-TPD对催化剂的结构进行了表征。结果表明,Cu/m-ZrO_2催化剂界面更加有利于Cu~+/Cu~0稳定存在,具有更多的碱性位点,且抗氧化性较好。在二乙醇胺脱氢反应中,Cu/m-ZrO_2催化剂性能最好,反应时间为2.5 h,亚氨基二乙酸收率为97.64%。     

Present status and future prospects of plasma sprayed multilayered thermal barrier coating systems

Thermal barrier coatings (TBCs) play a pivotal role in protecting the hot structures of modern turbine engines in aerospace as well as utility applications. To meet the increasing efficiency of gas turbine technology, worldwide research is focused on designing new architecture of TBCs. These TBCs are mainly fabricated by atmospheric plasma spraying (APS) as it is more economical over the electron beam physical vapor deposition (EB-PVD) technology. Notably, bi-layered, multi-layered and functionally graded TBC structures are recognized as favorable designs to obtain adequate coating performance and durability. In this regard, an attempt has been made in this article to highlight the structure, characteristics, limitations and future prospects of bi-layered, multi-layered and functionally graded TBC systems fabricated using plasma spraying and its allied techniques like suspension plasma spray (SPS), solution precursor plasma spray (SPPS) and plasma spray –physical vapor deposition (PS-PVD).     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

Complexities of digital technology use and the teaching and learning of function

Many argue that digital technologies have the potential to enhance the teaching and learning of mathematics. However, the availability of technology is not sufficient to realise this potential. The study reported takes a detailed approach to investigate the utility of the particular offerings of the available technologies in the teaching and learning of a specific area of mathematics, functions. Sixteen affordances identified in the data are described. The complexity of the process involved in resolving a situation where particular affordances would be useful so as they are perceived and enacted is detailed. Finally, a grounded theory framework arising from the data analysis from this study that can be used to explain, predict and guide action in other digital environments is presented.     

The Role of Cell Cycle Regulators in Cell Survival—Dual Functions of Cyclin-Dependent Kinase 20 and p21Cip1/Waf1

The mammalian cell cycle is important in controlling normal cell proliferation and the development of various diseases. Cell cycle checkpoints are well regulated by both activators and inhibitors to avoid cell growth disorder and cancerogenesis. Cyclin dependent kinase 20 (CDK20) and p21^Cip1/Waf1 are widely recognized as key regulators of cell cycle checkpoints controlling cell proliferation/growth and involving in developing multiple cancers. Emerging evidence demonstrates that these two cell cycle regulators also play an essential role in promoting cell survival independent of the cell cycle, particularly in those cells with a limited capability of proliferation, such as cardiomyocytes. These findings bring new insights into understanding cytoprotection in these tissues. Here, we summarize the new progress of the studies on these two molecules in regulating cell cycle/growth, and their new roles in cell survival by inhibiting various cell death mechanisms. We also outline their potential implications in cancerogenesis and protection in heart diseases. This information renews the knowledge in molecular natures and cellular functions of these regulators, leading to a better understanding of the pathogenesis of the associated diseases and the discovery of new therapeutic strategies.     

A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.