Analysis of dynamic response of the high-speed EMS maglev vehicle/guideway coupling system with random irregularity, Vehicle A new dynamic model of a high-speed EMS maglev vehicle/guideway interaction is presented. The model considers the vehicle and the guideway as an integral system and couples vertical interaction with lateral interaction. The vehicle subsystem is modeled as a multi-body system, which runs on the guideway with a constant velocity. The guideway substructure is modeled as an elastic beam. The attractive magnetic forces between vehicle and guideway are decided by controller, observer, and filter. A special simulation program is developed. Numerical results of the program are compared with test results. The results show that the coupling model is appropriate and the simulation program is credible primarily. Applications of coupling model to the investigation of the effect of irregularities on maglev system are reported at the end of the paper. The studies in this paper can be used to evaluate and optimize dynamic performances of the high-speed EMS maglev system.

Abstract:Track irregularities have an obvious effect on the running stability and ride quality of maglev trains traveling at high speeds. We developed a measurement principle and data processing method which were applied to the high speed maglev line operating. The method, which includes partial filtering, integration, resampling of signal, and a low pass Butterworth filter, was used to calculate the irregularities of the maglev line. The spectra of the sample space were evaluated. A 7-parameter power spectrum density (PSD) function of line irregularities was fitted, based on the measured data. Analysis of the results showed that the maglev stator plane irregularities were better than conventional railway vertical rail irregularities when the wavelength was 5-100 m, and worse when the wavelength was 1-5 m. The PSD of maglev guidance plane irregularities was similar to that of cross level GRSHL (German railway spectra of high irregularity) when the wavelength was 10-100 m. The irregularities were clearly worse than cross level rail irregularities in a conventional railway when the wavelength was 1-10 m. This suggests that short-wavelength track irregularities of a maglev line caused by deviation and inclination of the stator plane should be minimized by strictly controlling the machining error of functional components during construction and maintenance.

SummaryHelicobacter pylori persists deep in the human gastric mucus layer in a harsh, nutrient-poor environment. Survival under these conditions depends on the ability of this human pathogen to invoke starvation/stress responses when needed. Unlike many bacteria, H. pylori lacks starvation/stressresponding alternative sigma factors, suggesting an additional mechanism might have evolved in this bacterium. Helicobacter pylori produces polyphosphate; however, the role and target of polyphosphate during starvation/stress have not been identified. Here we show that polyphosphate accumulated during nutrient starvation directly targets transcriptional machinery by binding to the principal sigma factor in H. pylori, uncovering a novel mechanism in microbial stress response. A positively charged Lys-rich region at the N-terminal domain of the major sigma factor is identified as the binding region for polyphosphate (region P) in vivo and in vitro, revealing a new element in sigma 70 family proteins. This interaction is biologically significant because mutant strains defective in the interaction undergo premature cell death during starvation. We suggested that polyphosphate is a second messenger employed by H. pylori to mediate gene expression during starvation/stress. The putative 'region P' is present in sigma factors of other human pathogens, suggesting that the uncovered interaction might be a general strategy employed by other pathogens.

Remaining useful life estimation of the prognostics and health management technique is a complicated and difficult research question for maintenance. In this article, we consider the problem of prognostics modeling and estimation of the turbofan engine under complicated circumstances and propose a kernel principal component analysis-based degradation model and remaining useful life estimation method for such aircraft engine. We first analyze the output data created by the turbofan engine thermodynamic simulation that is based on the kernel principal component analysis method and then distinguish the qualitative and quantitative relationships between the key factors. Next, we build a degradation model for the engine fault based on the following assumptions: the engine has only had constant failure (i.e. no sudden failure is included), and the engine has a Wiener process, which is a covariate stand for the engine system drift. To predict the remaining useful life of the turbofan engine, we built a health index based on the degradation model and used the method of maximum likelihood and the data from the thermodynamic simulation model to estimate the parameters of this degradation model. Through the data analysis, we obtained a trend model of the regression curve line that fits with the actual statistical data. Based on the predicted health index model and the data trend model, we estimate the remaining useful life of the aircraft engine as the index reaches zero. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this prediction method that we propose. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this proposed method, the precision of the method can reach to 98.9% and the average precision is 95.8%.

No abstract