基于VWM-GRA的新型Fuzzy-FMEA复杂装备风险评估方法

失效模式和影响分析(Failure Mode and Effect Analysis,FMEA)是一种识别和预防复杂装备潜在故障模式的风险评估方法,然而,现有FMEA方法采用等权重和精确数表征不确定情形下的风险因素评估信息,导致风险优先数(Risk Priority Number,RPN)难以准确评估复杂装备故障模式的风险优先级。针对这一难题,文中提出了一种基于变权方法-灰色关联分析(Variable Weight Method-Grey Relation Analysis,VWM-GRA)的新型Fuzzy-FMEA复杂装备风险评估方法。在风险因素权重分配方面,在模糊熵值法的基础上,考虑风险评估信息对风险因素权重的影响,构建风险因素变权综合模型以动态调整风险因素权重值,据此确定风险因素的客观变权重;在风险优先数排序方面,在模糊语言变量表征风险因素评估信息的基础上,考虑风险因素评估信息不确定性量化对故障模式排序精度的影响,构建故障模式模糊灰色关联分析模型,以获取评估信息数据序列间的相对关联度,据此评估故障模式的风险优先级。最后,通过航空发动机主轴轴承的故障模式风险实例,分析验证文中方法的有效性。案例分析表明:该方法能够有效解决不确定情形下准确评估复杂装备故障模式风险优先级的难题。

Complete Convergenceand Complete Moment Convergence for Weighted Sums of ANA Random Variables

In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

Multimodel Ensemble Forecast of Global Horizontal Irradiance at PV Power Stations Based on Dynamic Variable Weight

In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical models,namely,the China Meteorological Administration Wind Energy and Solar Energy Prediction System,the Mesoscale Weather Numerical Prediction System of China Meteorological Administration,the China Meteorological Administration Regional Mesoscale Numerical Prediction System-Guangdong,and the Weather Research and Forecasting Model-Solar,and observational data from four photovoltaic(PV)power stations in Yangjiang City,Guangdong Province.The results show that compared with those of the monthly optimal numerical model forecasts,the dynamic variable weight-based ensemble forecasts exhibited 0.97%-15.96%smaller values of the mean absolute error and 3.31%-18.40%lower values of the root mean square error(RMSE).However,the increase in the correlation coefficient was not obvious.Specifically,the multimodel ensemble mainly improved the performance of GHI forecasts below 700 W m^(-2),particularly below 400 W m^(-2),with RMSE reductions as high as 7.56%-28.28%.In contrast,the RMSE increased at GHI levels above 700 W m^(-2).As for the key period of PV power station output(02:00-07:00),the accuracy of GHI forecasts could be improved by the multimodel ensemble:the multimodel ensemble could effectively decrease the daily maximum absolute error(AE max)of GHI forecasts.Moreover,with increasing forecasting difficulty under cloudy conditions,the multimodel ensemble,which yields data closer to the actual observations,could simulate GHI fluctuations more accurately.

VW-UM模型在采场稳定性评价中的应用

为避免地下采场稳定性常权分析时容易出现"状态失衡"的问题,将变权重理论(VW)引入其中,结合未确知测度理论(UM)建立采场稳定性VW-UM评价模型。基于对采场稳定性影响最大的14项指标,计算其未确知测度(UM)函数,运用层次分析法(AHP)确定各指标常权重,再通过VW理论细化各指标权重的取值,最后根据置信度识别准则预测采场风险等级。用VW-UM模型分析新桥矿和焦家矿5个采场的稳定性,得出各采场的风险等级。实例分析表明,指标权重在常权重的基础上需根据指标值确定,这样使得分析结果的准确度比传统评价模型要高。

基于VW模型的土地可持续利用评价及时空特征分析——以安徽省市域为例

研究目的:揭示安徽省各地市土地可持续利用程度及时空格局特征,实现土地资源可持续利用。研究方法:文献资料法、变权模型(VW模型)、层次分析法(AHP)。研究结果:(1)2005—2013年安徽省各地市土地可持续利用指数总体偏低,介于轻度不可持续(III1)到临界可持续(II1)状态之间;(2)从土地可持续利用指数的变化情况来看,增速最慢的为马鞍山市,增速低于2%,增速较缓慢的地区为合肥、阜阳、六安、芜湖、铜陵、黄山,年均增长率介于2%—3%之间,其余地市土地可持续利用指数年均增长率较快,均超过了3%;(3)土地可持续利用程度在空间上呈现一定的地域特征,总体上看,土地可持续利用指数由高到低依次为江南地区、江淮地区、淮河以北地区。研究结论:安徽省土地可持续利用程度总体较差,但各地市土地可持续利用程度不断提升,土地可持续利用格局呈良性发展态势。

Evaluation on Fuzzy Variable Weight of Cultivated Land Fertility Based on GIS

[Objective] The modified variable weights based on constant weight and in- troduced theory of equalization function would better incorporate authentic index weights and make evaluation results of fertility more scientific. [Method] In Gaozhou City, the final weights of influential factors can be determined with the help of GIS and as per AHP and theory of variable weights. In addition, farmland fertility was e- valuated in an automatic and quantitative way and the spatial distribution pattern was analyzed as per fuzzy comprehensive evaluation. [Result] For farmlands at 58 505.027 8 hm2 in the city, farmlands from grade 1 to grade 8 account for 3.62%, 18.27%, 33.15%, 26.96%, 13.66%, 3.29%, 0.81% and 0.24%, respectively, which is in consistent with local condition. [Conclusion] These results have been applied di- rectly in test regions and constitute a rewarding exploration for fertility evaluation in South China.

充填管道失效风险的VW-CM模型研究

充填管道失效具有随机性和模糊性特点。为定性分析充填管道系统可靠性,通过构建变权重理论(VW)和云模型(CM)的综合评判模型,选取10个影响因素建立指标评估体系,基于变权重理论计算指标权重,通过计算云的数字特征生成指标云图,实现充填管道风险等级与指标之间的相互映射与转化,通过确定单指标测度和综合确定度,基于最大隶属度原则,对大红山铜矿、河东金矿和新城金矿3个金属矿山充填管道失效等级进行了综合评判。结果表明:大红山铜矿、河东金矿和新城金矿风险等级分别为Ⅱ级、Ⅰ级和Ⅱ级,与实际情况相符,风险评价模型计算结果可靠;通过与主成分分析-BP神经网络、PSO-SVM和变异系数-TOPSIS三种数学模型对比,发现评估结论完全一致,为充填管道失效风险评价工作提供了一条可量化的新思路。

Design and research on a variable ballast system for deep-sea manned submersibles

Variable ballast systems are necessary for manned submersibles to adjust their buoyancy.In this paper,the design of a variable ballast system for a manned submersible is described.The variable ballast system uses a super high pressure hydraulic seawater system.A super high pressure seawater pump and a deep-sea brushless DC motor are used to pump seawater into or from the variable ballast tank,increasing or decreasing the weight of the manned submersible.A magnetostrictive linear displacement transducer can detect the seawater level in the variable ballast tank.Some seawater valves are used to control pumping direction and control on-off states.The design and testing procedure for the valves is described.Finally,the future development of variable ballast systems and seawater hydraulic systems is projected.

Relationship Between Beak Morphological Variables and Body Size and Mantle Length of Male and Female Argentine Shortfin Squid(Illex argentinus)

Beak of cephalopod is an important hard tissue. Understanding the morphology of beak can yield critical infor- mation on the role of cephalopods in the ecosystem. The south patagonic stock of the Argentine shortfin squid, Illex argentinus, is not only one of the most important fishing targets, but also one of the most important species in the marine eco-system of the southwest Atlantic. A total of 430 samples ofL argentinus, including 229 females 103-346mm in mantle length （ML） and 201 males 140-298mm in ML, were collected from the area off the Exclusive Economic Zone of Argentinean waters by Chinese squid jigging vessels during February to May 2007. The morphology of their beaks was evaluated. The relationships between beak morphological variables and ML differed significantly among males and females. They could be best described by loga- rithmic functions for females and linear functions for males except for upper wing length （UWL） and lower rostrum length （LRL）, which followed exponential functions in their relationships with ML. The results showed the sexual dimorphism in the relationship between ML and beak morphology for the south patagonic stock ofL argentinus. However, no significant differ- ence was found between males and females in the relationships of beak morphological variables （except for UWL） versus body weight （BW）, suggesting that the relationship between beak morphological variables and BW can be used for estimating the biomass consumed by their predators.

基于VW-PCA的盾构刀盘驱动液压系统故障诊断

为提高盾构刀盘液压系统故障诊断的快速性和准确性,引入权值向量来改进传统主元分析法(PCA),并推导变量加权主元分析法(VW-PCA)公式。通过AMESim仿真软件建立6 450 mm土压平衡盾构刀盘驱动液压系统模型,选取12个测试变量,模拟仿真6种故障状态;运用仿真故障数据得到每一类故障的加权向量,建立变量加权主元分析模型(VW-PCA),并使用该模型对测试故障样本进行研究。结果表明:变量加权(VW)能够增强各系统变量对不同故障类型的贡献程度,变量加权主元模型(VWPCA)能够显著提高系统诊断的正确率,最大可提高50%以上。

On the Strong Laws for Weighted Sums of m-negatively Asso ciated Random Variables

In this article, the author establishes the strong laws for linear statistics that are weighted sums of a m-negatively associated(m-NA) random sample. The obtained results extend and improve the result of Qiu and Yang in [1] to m-NA random variables.

SOME LIMIT THEOREMS FOR WEIGHTED SUMS OF ARRAYS OF NOD RANDOM VARIABLES

In this paper the authors study the complete, weak and almost sure convergence for weighted sums of NOD random variables and obtain some new limit theorems for weighted sums of NOD random variables, which extend the corresponding theorems of Stout [1], Thrum [2] and Hu et al. [3].

Boundedness of Marcinkiewicz Integrals in Weighted Variable Exponent Herz-Morrey Spaces

In this paper, under natural regularity assumptions on the exponent function, we prove some boundedness results for the functions of Littlewood-Paley, Lusin and Marcinkiewicz on a new class of generalized Herz-Morrey spaces with weight and variable exponent, which essentially extend some known results.

基于VW-FDA的盾构机液压系统故障诊断方法研究

盾构机规模庞大,施工过程中检测变量众多,液压系统故障易发。为了实现在线监测,提高液压系统故障诊断的准确性,探究与盾构机适应的快速准确有效的故障识别方法,提出使用加权因子与传统费歇尔判别法相结合的加权费歇尔判别法(Variable-Weighted-Fisher Discriminant Analysis,VW-FDA)。通过AMESim软件建立推进系统模型,仿真四类故障,运用仿真故障数据得到每一类故障的加权向量,建立VWFDA模型。结果表明:对于盾构机液压推进系统,VW-FDA比传统FDA具有更强的故障诊断能力,能够将故障信息进行有效的分类,正确地做出故障诊断。

Spatial Prediction of Soil Salinity in a Semiarid Oasis: Environmental Sensitive Variable Selection and Model Comparison

Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.

Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China

Achieving water purity in Poyang Lake has become a major concern in recent years, thus appropriate evaluation of spatial and temporal water quality variations has become essential. Variations in 11 water quality parameters from 15 sampling sites in Poyang Lake were investigated from 2009 to 2012. An integrative fuzzy variable evaluation(IFVE) model based on fuzzy theory and variable weights was developed to measure variations in water quality. Results showed that: 1) only chlorophyll-a concentration and Secchi depth differed significantly among the 15 sampling sites(P < 0.01), whereas the 11 water quality parameters under investigation differed significantly throughout the seasons(P < 0.01). The annual variations of all water quality variables except for temperature, electrical conductivity, suspended solids and total phosphorus were considerable(P < 0.05). 2) The IFVE model was reasonable and flexible in evaluating water quality status and any possible ′bucket effect′. The model fully considered the influences of extremely poor indices on overall water quality. 3) A spatial analysis indicated that anthropogenic activities(particularly industrial sewage and dredging) and lake bed topography might directly affect water quality in Poyang Lake. Meanwhile, hydrological status and sewage discharged into the lake might be responsible for seasonal water quality variations.

Risk assessment of floor water inrush in coal mines based on MFIM-TOPSIS variable weight model

Floor water inrush is one of the main types of coal mine water hazards.With the development of deep mining,the prediction and evaluation of floor water inrush is particularly significant.This paper proposes a variable weight model,which combines a multi-factor interaction matrix(MFIM)and the technique for order performance by similarity to ideal solution(TOPSIS)to implement the risk assessment of floor water inrush in coal mines.Based on the MFIM,the interaction between seven evaluation indices,including the confined water pressure,water supply condition and aquifer water yield property,floor aquifuge thickness,fault water transmitting ability,fracture development degree,mining depth and thickness and their influence on floor water inrush were considered.After calculating the constant weights,the active degree evaluation was used to assign a variable weight to the indices.The values of the middle layer and final risk level were obtained by TOPSIS.The presented model was successfully applied in the 9901 working face in the Taoyang Mine and four additional coal mines and the results were highly consistent with the engineering situations.Compared with the existing nonlinear evaluation methods,the proposed model had advantages in terms of the weighting,principle explanation,and algorithm structure.

Toeplitz Type Operator Associated to Singular Integral Operator with Variable Kernel on Weighted Morrey Spaces

Suppose T^k,l and T^k,2 are singular integrals with variable kernels and mixed homogeneity or ±I （the identity operator）. Denote the Toeplitz type operator by T^b=k=1∑^QT^k,1M^bT^k,2 where M^bf= bf. In this paper, the boundedness of Tb on weighted Morrey space are obtained when b belongs to the weighted Lipschitz function space and weighted BMO function space, respectively.

A variable weight approach for evidential reasoning

A variable weight approach was proposed to handle the probability deficiency problem in the evidential reasoning （ER） approach. The probability deficiency problem indicated that the inadequate information in the assessment result should be less than that in the input. However, it was proved that under certain circumstances, the ER approach could not solve the probability deficiency problem. The variable weight approach was based on two assumptions： 1） the greater weight should be given to the rule with more adequate information; 2） the greater weight should be given to the rules with less disparate information. Assessment results of two notional case studies show that 1） the probability deficiency problem is solved using the proposed variable weight approach, and 2） the information with less inadequacy and more disparity is provided for the decision makers to help reach a consensus.