Model-based detection of critical driving situations with fuzzy logic decision making

A precise knowledge about the current driving condition is getting increasingly important for future driver assistance systems like global chassis control or collision avoidance systems for avoiding any critical driving situation. Moreover a precise knowledge about the driving situation can be used in testing, in evaluation, and for comparison of new passenger cars. A two degree of freedom model of vehicle lateral dynamics is used to derive a characteristic velocity stability indicator (CVSI). The CVSI is used to distinguish between different driving and stability conditions (i.e. understeering, oversteering, and neutralsteering). This forms the basis for a driving condition detection system with fixed thresholds. It is then extended to a detection system with fuzzy logic thresholds. The CVSI and the fuzzy systems are compared experimentally using (i) a slalom test drive on an icy road and (ii) a stationary circular test drive on a dry asphalt road.     

Fabrication and frequency response of a complex ultrasonic transducer for multilayer evaluation

To characterize the thickness of a corrosive fluid system's coated facilities, such as pipes, tubes, tanks, and structural members, a complex ultrasonic transducer capable of measuring multilayered parts was fabricated and the time and frequency responses were evaluated. The target transducer was constructed with two active dual elements made from tape-cast PbNb₂O₆ sheets and an additional thin-film active element made from sol–gel spin-coated Pb(Zr_0.52Ti_0.48)O₃ films. After adjusting the properties of each active element, a complex transducer was assembled after matching the impedance of each element and considering the minimal interference between the active layers. The impulse response of the assembled complex transducer shows excellent characteristics. Moreover, the assembled transducer's capability of accurately measuring the thickness assures that it can be directly applied to related industries.     

氧化锌颗粒膜电阻响应-恢复特性研究

测试了氧化锌颗粒膜电阻响应-恢复特性，讨论了颗粒形态，加热电压、环境气氛、气氛浓度和注入方式等因素对电阻响应-恢复特性的影响。结果表明，随着加热电压的升高，电阻响应-恢复的速度和程度明显加大；断续注入时颗粒膜电阻值的响应随着浓度的增加逐步减弱．     

Electrospinning of collagen-chitosan complex

The collagen-chitosan complex nanofibers have been prepared for the first time by electrospinning. The mixed HFP/TFA (the volume ratio of 90/10) was found to be the appropriate solvent for electrospinning. The concentration of the spinning solution and the ratio of chitosan/collagen were varied and adjusted to get smooth nanofibers. It was found that the diameter of the spun fibers became thick with the concentration of the solution increasing and became fine with the ratio of the chitosan/collagen increasing. We have characterised the molecular interactions in collagen-chitosan complex by Fourier transform infrared spectroscopy. The spun fibers are designed to mimic the native extracellular matrix for tissue engineering and to develop functional biomaterials.     

Consistency retention method for CNC machine tool digital twin model

Computer Numerical Control Machine Tool (CNCMT) Digital Twin (DT) model is a carrier for complex, time-varying, coupled data of CNCMT, which can theoretically provide a time-varying high-fidelity model. However, there are still many difficulties in its implementation process. And the key issue is how to realize the updated DT model with performance attenuation and validate it. In order to solve this problem, a model consistency retention method for CNCMT DT model is studied and proposed in this paper. Firstly, the framework of consistency retention method for DT model is designed including both digital space and physical space. The principles of data management and performance attenuation update in digital space are elaborated. Then, the implementation method for consistency retention of CNCMT DT model is studied in terms of performance attenuation update workflow for wear and other damage separately. Finally, a case study for the establishment and application of high-fidelity test bench DT model that focusing on rolling guide-rail is carried out to show the implementation flow of the proposed method and verify its operability and effectiveness.     

Digital twin modeling method based on biomimicry for machining aerospace components

High-performance aerospace component manufacturing requires stringent in-process geometrical and performance-based quality control. Real-time observation, understanding and control of machining processes are integral to optimizing the machining strategies of aerospace component manufacturing. Digital Twin can be used to model, monitor and control the machining process by fusing multi-dimensional in-context machining process data, such as changes in geometry, material properties and machining parameters. However, there is a lack of systematic and efficient Digital Twin modeling method that can adaptively develop high-fidelity multi-scale and multi-dimensional Digital Twins of machining processes. Aiming at addressing this challenge, we proposed a Digital Twin modeling method based on biomimicry principles that can adaptively construct a multi-physics digital twin of the machining process. With this approach, we developed multiple Digital Twin sub-models, e.g., geometry model, behavior model and process model. These Digital Twin sub-models can interact with each other and compose an integrated true representation of the physical machining process. To demonstrate the effectiveness of the proposed biomimicry-based Digital Twin modeling method, we tested the method in monitoring and controlling the machining process of an air rudder.     

Adaptive synchronization of the complex dynamical network with double non-delayed and double delayed coupling

To simulate more realistic networks, we introduce a complex dynamical network model with double non-delayed and double delayed coupling and further investigate its synchronization phenomenon in this paper. Based on Lyapunov stability theory, adaptive synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, the complex dynamical network with double non-delayed and double delayed coupling can asymptotically synchronize to a given trajectory. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulation results show the method is effective.     

基于群智能混合算法的物流配送路径研究

针对物流车辆路径优化问题,考虑到基本蚁群算法有收敛速度慢、易陷入局部最优的缺点,采用了一种双种群蚁群算法,在蚁群的基础上引入差分进化(DE)和粒子群算法(PSO)。通过在PSOAS种群和DEAS种群之间建立一种信息交流机制,使信息能够在两个种群中传递,以免某一方因错误的信息判断而陷入局部最优点。通过matlab仿真实验测试,表明该群智能混合算法可以较好地解决TSP的问题。     

基于网络药理学技术研究黄芪?枸杞子药对治疗溃疡性结肠炎的作用机制

黄芪?枸杞子药对治疗溃疡性结肠炎的临床疗效确切,然而作用机制不明. 采用网络药理学技术研究黄芪?枸杞子配伍抗溃疡性结肠炎的潜在作用机制. 利用整合药理学平台、String数据库、David 数据库等系统检索中药化学成分和候选靶标,通过分析药物和疾病蛋白靶标互作关系,筛选关键靶标并进行基因GO功能和KEGG通路富集分析,构建“中药?核心成分?关键靶标?主要通路”多维调控网络. 结果表明,黄芪?枸杞子可能通过作用于前列腺素 G/H 合成酶 2 (PTGS2) 等蛋白靶标,参与核转录因子(NF-κВ)、肿瘤坏死因子 (TNF) 等多个炎症和免疫相关信号通路,发挥抗溃疡性结肠炎作用. 研究结果为系统阐明黄芪?枸杞子药对治疗溃疡性结肠炎的作用机制提供参考.     

一种新的知觉分割模型*

根据知觉的最新理论研究和实验结果,提出一种新的知觉模型,并用于考查计算机视觉中的分割问题.分割问题实质上是知觉表达问题,现在分割的困难性可能是知觉上局部到整体的还原论假设造成的;分割可能不是一次完成的,而是经过整体到局部的过程才最终完成.新的知觉模型将对建立更好的分割模型提供理论基础.