基于模糊统计的不确定质量特性控制图研究

不确定质量特性采用专家评分、语言评价等测量手段,使常规的控制图方法难以适用。文章以不确定质量特性评分数据为基础,提出了评判模糊数统计特征的求取方法,并以特征数构建不同类型的评判模糊数隶属函数,以过程均值模糊数割集的上下限作为控制线,以评分样本模糊数割集的上下限为控制图描点数据,以描点数据与控制线之间的位置关系进行异常报警,实现不确定质量特性控制图的绘制,最后在Matlab环境下,以具体的应用实例验证了方案的可行性。

基于模糊统计的不确定质量特性过程能力指数计算模型

具有不确定质量特性的过程评价存在许多模糊信息,无法直接估算过程的能力指数,使能力指数在这种场合的应用受到限制。为了利用不确定质量特性的主观评价数据估算模糊过程能力指数,文章提出了利用模糊评分数据估计评价结果的模糊统计特征值的方法,并利用模糊统计特征值计算不确定质量特性过程能力指数,最后将不同模糊能力指数进行比较,分析结果表明文章所采用的模糊能力指数对过程中心偏移及质量损失的方面具有较高的灵敏性。

参数不确定下的磁悬浮双转子系统的动态特性

目前,关于电磁轴承支承特性的研究大多是基于PID类传递函数明确的控制算法展开的,而非线性控制算法的模糊属性导致难以建立电磁轴承的支承刚度和阻尼模型,系统的支承特性存在不确定性,从而难以对此类磁悬浮系统的动力学特性展开研究。为此,针对支承特性不确定下的磁悬浮双转子系统,首先,运用有限元法建立了磁悬浮双转子系统的理论模型;其次,将电磁轴承支承特性中的不确定量转化为‘未知而有界’的区间;最后,基于Chebyshev正交多项式的区间分析方法对磁悬浮双转子系统的动态特性展开了研究。研究结果表明,低频峰值响应的不确定度与等效刚度和阻尼呈现幂函数变化关系。

典型非线性系统的自适应BP神经网络跟踪控制器设计

基于BP神经网络针对一类典型的非线性系统,设计成自适应跟踪控制方案。利用神经网络在线辨识,并将辨识结果加入到控制器的设计中,不但增强了控制器对于不确定非线性系统的鲁棒性,而且使跟踪误差渐进收敛于零。仿真结果证明了这种方法的可行性。

Characterizing uncertainty in pavement performance prediction

Taking variability and uncertainty involved in performance prediction into account, in order to make the prediction reliable and meaningful, a distribution-based method is developed to predict future PSI. This method, which is based on the AASHTO pavement performance model, treats predictor variables as random variables with certain probability distributions and obtains the distribution of future PSI through the method of Monte-Carlo simulation. A computer program PERFORM using Monte Carlo simulation is developed to implement the numerical computation. Simulation results based on pavement and traffic parameters show that traffic, surface layer material property, and initial pavement performance are the most significant factors affecting pavement performance. Once the distribution of future PSI is determined, statistics such as the mean and the variance of future PSI are readily available.

Effect of Uncertainty of Grid DEM on TOPMODEL:Evaluation and Analysis

TOPMODEL,a semi-distributed hydrological model,has been widely used.In the process of simulation of the model,Digital Elevation Model(DEM) is used to provide the input data,such as topographic index and distance to the drainage outlet;thus DEM plays an important role in TOPMODEL.This study aims at examining the impacts of DEM uncertainty on the simulation results of TOPMODEL.In this paper,the effects were evaluated mainly from quantitative and qualitative aspects.Firstly,DEM uncertainty was simulated by using the Monte Carlo method,and for every DEM realization,the topographic index and distance to the drainage outlet were extracted.Secondly,the obtained topographic index and the distance to the drainage outlet were input to the TOPMODEL to simulate seven rain-storm-flood events,and four evaluation indices,such as Nash and Sutcliffe efficiency criterion(EFF),sum of squared residuals over all time steps(SSE),sum of squared log residuals over all time steps(SLE) and sum of absolute errors over all time steps(SAE) were recorded.Thirdly,these four evaluation indices were analyzed in statistical manner(minimum,maximum,range,standard deviation and mean value),and effect of DEM uncertainty on TOPMODEL was quantitatively analyzed.Finally,the simulated hydrographs from TOPMODEL using the original DEM and realizations of DEM were qualitatively evaluated under each flood cases.Results show that the effect of DEM uncertainty on TOPMODEL is inconsiderable and could be ignored in the model’s application.This can be explained by:1) TOPMODEL is not sensitive to the distribution of topographic index and distance to the drainage outlet;2) the distri-bution of topographic index and distance to the drainage outlet are slightly affected by DEM uncertainty.

Optimizing management in autoimmune hepatitis with liver failure at initial presentation

Autoimmune hepatitis (AIH) is a disease of unknown etiology,its hallmark being ongoing hepatic inflammation.By its very nature,it is a chronic condition,although increasingly,we are becoming aware of patients with acute presentations,some of whom may have liver failure.There are very limited published data on patients with AIH with liver failure at initial diagnosis,which consist mostly of small retrospective studies.As a consequence,the clinical features and optimal management of this cohort remain poorly defined.A subset of patients with AIH who present with liver failure do respond to corticosteroids,but for the vast majority,an urgent liver transplantation may offer the only hope of long-term survival.At present,there is uncertainty on how best to stratify such a cohort into responders and non-responders to corticosteroids as soon as possible after hospitalization,thus optimizing their management.This editorial attempts to answer some of the unresolved issues relating to management of patients with AIH with liver failure at initial presentation.However,it must be emphasized that,at present,this editorial is based mostly on small retrospective studies,and it is an understatement that multicenter prospective studies are urgently needed to address this important clinical issue.

Comparison of GUF and Monte Carlo methods to evaluate task-specific uncertainty in laser tracker measurement

Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplement, the Monte Carlo method, were used to estimate the uncertainty of task-specific laser tracker measurements. First, the sources of error in laser tracker measurement were analyzed in detail, including instruments, measuring network fusion, measurement strategies, measurement process factors(such as the operator), measurement environment, and task-specific data processing. Second, the GUM and Monte Carlo methods and their application to laser tracker measurement were presented. Finally, a case study involving the uncertainty estimation of a cylindricity measurement process using the GUF and Monte Carlo methods was illustrated. The expanded uncertainty results(at 95% confidence levels) obtained with the Monte Carlo method are 0.069 mm(least-squares criterion) and 0.062 mm(minimum zone criterion), respectively, while with the GUM uncertainty framework, none but the result of least-squares criterion can be got, which is 0.071 mm. Thus, the GUM uncertainty framework slightly underestimates the overall uncertainty by 10%. The results demonstrate that the two methods have different characteristics in task-specific uncertainty evaluations of laser tracker measurements. The results indicate that the Monte Carlo method is a practical tool for applying the principle of propagation of distributions and does not depend on the assumptions and limitations required by the law of propagation of uncertainties(GUF). These features of the Monte Carlo method reduce the risk of an unreliable measurement of uncertainty estimation, particularly in cases of complicated measurement models, without the need to evaluate partial derivatives. In addition, the impact of sampling strategy and evaluation method on the uncertainty of the measurement results can also be taken into account with Monte Carlo method, which plays a guiding role in measurement planning.

Qualification of Three Analytical Wake Models

The decrease of wind velocity （wake losses） in downstream area of wind turbine is generally quantified using wake models. The overall estimated power of wind farm varies according to reliability of wake model used, however it＇s unclear which model is most appropriate and able to give a high performance in predicting wind velocity deficit. In this subject, a qualification of three analytical wake models （Jensen, lshihara and Frandsen） based on three principal criteria is presented in this paper： （i） the parsimony which characterizes the inverse of model complexity, （ii） the accuracy of estimation in which wake model is compared with the experimental data and （iii） imprecision that is related to assumptions and uncertainty on the value of variables considered in each model. This qualitative analysis shows the inability of wake models to predict wind velocity deficit due to the big uncertainty of variables considered and it sensitivity to wind farm characteristic.

Significance of Rare Mineral Resources to Strategic Emerging Industries

As non-renewable natural resources, rare minerals＇ are extensively used as important raw materials in strategic emerging industries. As global consumption continues to increase over recent years, international competition in the area of rare mineral minerals has been escalating. On the basis＇ of the identification of 22 rare mineral resources of six categories and analysis of their applications in strategic emerging industries, this paper has adopted a three-factor analytical framework and designed nine indicators from the three dimensions of supply risks, environmental impacts and economic impacts of restricted supply to conduct a quantitative evaluation of the strategic significance of rare mineral resources. The result indicates that the strategic significance of platinum-group metals is the highest and the strategic significance of cesium is the lowest. In order to further increase the reliability of evaluation results, this paper has employed the Monte Carlo simulation for uncertainty analysis＇. Simulation result demonstrates that after the impacts＂ of individual indicators have been taken into account, the results＇ of this paper＇s evaluation of 22 rare mineral resources remain valid. Given the growing significance of rare mineral resources to strategic emerging industries, China should formulate a national strategy on rare mineral resources＇, strive to inerease the supply security of key raw materials for strategic emerging industries and achieve the sustainable development and utilization of rare mineral resources for national security of natural resources.

Robust Stability Analysis of a Kind of Combined Integrating Control System

This paper offeres an exact study on the robust stability of a kind of combined integrating control system, and the robust stability belongs to the analysis of a kind of quasi-polynomial with two independent time delays. The parameters of stable space under time delay uncertainty are fixed after Rekasius transformation, and then a new cluster treatment of characteristic roots (CTCR) procedure is adopted to determine the stable space. By this strategy we find that the unstable space is not continuous and both Karitonov vertices theory and Edge theory are unable to be extended to quasi-polynomial under time delay uncertainty.

国外采油新技术(二)

简要介绍了国外一些石油公司近期研究和开发应用的部分采油工程新技术 ,其中包括不会发生气锁的游动凡尔、喷射泵提高气井产量技术、在线采油工程软件、非冷却型压缩机密封填料和油藏不确定特性测试技术。

Fatigue reliability assessment for bridge welded details using long-term monitoring data

A reliability assessment method of fatigue life based on the long-term monitoring data is developed for welded details in steel box girder,and the application research is presented with examples of welded rib-to-deck details in Runyang Bridges. Firstly the fatigue damage limit-state function is established based on S-N curves and Miner's rule,and the probability distribution characteristics of the coefficients in the function are discussed in detail. The uncertainties in fatigue loading effects are mainly studied based on long-term monitoring data. In the traditional studies,only the uncertainty of equivalent stress range is considered in fatigue reliability assessment. However,stress cycle number is also treated as a random variable in this paper because we know traffic flow every day differs in a thousand ways. Then the optimization method is employed to calculate the fatigue reliability. After studying the changing law of the reliability indices with time and the effect of the randomness of stress cycle number on reliability,the effect of the traffic growth on the reliability is studied. This study shows that the uncertainty in the fatigue life of the welded details can be well studied based on structural health monitoring,so it is necessary to carry out long-term strain monitoring of the welded details for accurate fatigue reliability assessment during the whole service period.

Effect of the uncertainty in soil-water characteristic curve on the estimated shear strength of unsaturated soil

Most failures or instabilities of geotechnical structures commonly result from shear failure in soil. In addition, many infrastructures are constructed within the unsaturated zone. Therefore, the determination of shear strength of unsaturated soil is crucial in geotechnical design. The soil-water characteristic curve(SWCC) is commonly used to estimate the shear strength of unsaturated soil because the direct measurement is time-consuming and costly. However, the uncertainty associated with the determined SWCC is rarely considered in the estimation of the shear strength. In this paper, the uncertainties of SWCC resulted from different factors are reviewed and discussed. The variability of the estimated shear strength for the unsaturated soil due to the uncertainty of SWCC associated with the best fit process is quantified by using the upper and lower bounds of the determined SWCC. On the other hand, the uncertainties of the estimated shear strength due to different initial void ratios or different confining pressures are quantified by adopting different SWCCs. As a result, it is recommended that the measured SWCC from the conventional Tempe cell or pressure plate needs to be corrected by considering different stress levels in the estimation of the shear strength of unsaturated soil.

An interval effective independence method for optimal sensor placement based on non-probabilistic approach

This paper presents an interval effective independence method for optimal sensor placement, which contains uncertain structural information. To overcome the lack of insufficient statistic description of uncertain parameters, this paper treats uncertainties as non-probability intervals. Based on the iterative process of classical effective independence method, the proposed study considers the eliminating steps with uncertain cases. Therefore, this method with Fisher information matrix is extended to interval numbers, which could conform to actual engineering. As long as we know the bounds of uncertainties, the interval Fisher information matrix could be obtained conveniently by interval analysis technology. Moreover, due to the definition and calculation of the interval relationship, the possibilities of eliminating candidate sensors in each iterative process and the final layout of sensor placement are both presented in this paper. Finally, two numerical examples, including a five-storey shear structure and a truss structure are proposed respectively in this paper. Compared with Monte Carlo simulation, both of them can indicate the veracity of the interval effective independence method.

Fast changing processes in radiotelemetry systems of space vehicles

The method of processing of the non-stationary casual processes with the use of nonparametric methods of the theory of decisions is considered. The use of such methods is admissible in telemetry systems in need of processing at real rate of time of fast-changing casual processes in the conditions of aprioristic uncertainty about probabilistic properties of measured process.

Discriminant Models for Uncertainty Characterization in Area Class Change Categorization

Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.

Modified perturbation method for eigenvalues of structure with interval parameters

In overcoming the drawbacks of traditional interval perturbation method due to the unpredictable effect of ignoring higher order terms,a modified parameter perturbation method is presented to predict the eigenvalue intervals of the uncertain structures with interval parameters.In the proposed method,interval variables are used to quantitatively describe all the uncertain parameters.Different order perturbations in both eigenvalues and eigenvectors are fully considered.By retaining higher order terms,the original dynamic eigenvalue equations are transformed into interval linear equations based on the orthogonality and regularization conditions of eigenvectors.The eigenvalue ranges and corresponding eigenvectors can be approximately predicted by the parameter combinatorial approach.Compared with the Monte Carlo method,two numerical examples are given to demonstrate the accuracy and efficiency of the proposed algorithm to solve both the real eigenvalue problem and complex eigenvalue problem.

A method for detection and quantification of meshing characteristics of harmonic drive gears using computer vision

A lack of accurate description of the meshing characteristics and the corresponding frictional mechanism of the harmonic drive gear has limited progress toward modeling the hysteresis stiffness. This paper presents a method for detection and quantification of the meshing characteristics of the harmonic drive gear based on computer vision. First, an experimental set-up that integrates a high speed camera system with a lighting system is developed, and the image processing is adopted to extract and polish the tooth profiles of the meshed teeth pairs in each acquired video sequence. Next, a physical-mathematical model is established to determine the relative positions of the selected tooth pair in the process of the gear engagement, and the combined standard uncertainty is utilized to evaluate the accuracy of the calculated kinematics parameters. Last, the kinematics analysis of the gear engagement under the ultra-low speed condition is performed with our method and previous method, and the influence of the input rotational speed on the results is examined. The results validate the effectiveness of our method, and indicate that the conventional method is not available in the future friction analysis. It is also shown that the engaging-in phase is approximately a uniform motion process, the engaging-out phase is a variable motion process, and these characteristics remain unchanged with the variation of the input rotational speed. Our method affords the ability to understand the frictional mechanism on the meshed contact surfaces of the harmonic drive gear, and also allows for the dynamic monitoring of the meshing properties.