基于SFCE与规则推理的发动机集成故障诊断方法

针对发动机磨损过程的复杂性以及故障症状(磨粒信息)与故障原因之间对应关系的不确定性,首先对磨粒数量特征信息进行了模糊化,建立了某发动机典型磨损故障的模糊规则库。针对单一故障诊断方法的局限性,引入了对称模糊交互熵的故障推理方法,在此基础上建立了基于对称模糊交互熵和规则推理相结合的发动机故障诊断模型。本模型首先采用对称模糊交互熵对故障原因进行"过滤",滤除出现可能性较小的原因,然后利用规则推理进一步确认最后的故障原因。实例表明,该方法在发动机多症状多原因的复杂情况下能够取得较好的诊断结果。     

统计能量分析法及其损耗因子确定方法综述

统计能量分析法(SEA)在中高频段被广泛用于预测复杂结构的振动和噪声传递,本文阐述了统计能量分析法及其在船舶上的应用和局限性。统计能量分析法将结构划分成若干子系统,这些子系统以在窄频带内存储的振动能量和模态数的多少为特征,耦合损耗因子和内损耗因子分别用来表示各子系统之间的耦合程度和能量的损失程度,是统计能量分析法应用中的重要参数,本文综述了近四十年来国内外统计能量分析法研究中确定损耗因子的方法。     

新疆铁路百里风区大风特征统计分析

通过对新疆铁路百里风区大风特征统计分析,归纳出百里风区具有风速高、风期长、季节性强、风向稳定、起风速度快等规律,并得到不同时距风速统计关系和风区风速地域分布特征,为今后新疆铁路大风地区完善行车组织办法和防风减灾工程研究提供依据。     

大众品牌汽车在华车型整车匹配性能统计分析

大众汽车集团是中国汽车工业最早、最成功的国际合作伙伴之一,除江淮大众外,其主要的合资公司为上汽大众和一汽大众,文章主要是统计一汽大众、上汽大众所有大众品牌在售乘用车车型信息、销量、动力性、经济性、整备质量等相关参数,从车机箱搭载维度、整车性能表现维度、发动机搭载形式和性能维度以及车辆整备质量维度等方面进行整车匹配性能统计分析。     

微机模糊控制 3：第三讲模糊语言及其应用

模糊语言是模糊控制的理论基础。自然语言中某些单词，词组等通过模糊集合的描述和模糊揄转换成计算可以接受的数学模型，就可以实现计算机控制。     

基于自适应神经网络模糊推理系统的交叉口交通冲突数预测

自适应神经网络模糊系统在建立对象输入和输出关系时,与传统的数学方法不同,它是基于数据的建模。本文利用这一系统特性,建立平面交叉口交通冲突数与进入交叉口内的左转交通量、右转交通量、直行交通量和行人过街交通量之间模型,提出自适应神经网络模糊系统预测交叉口冲突数的方法,建立一种快速获取交通冲突数的预测方法,为交通冲突数的调查开辟了新的途径。     

基于自适应模糊神经网络的交通流状态预测

研究交通流状态的分类、识别与预测,建立了基于模糊聚类及模式识别的交通流状态自适应模糊神经推理系统.对大量交通流历史特征数据采用模糊聚类法进行状态分类并进行模式识别,得到系统的原始输入输出数据集.建立交通流状态预测的自适应模糊神经系统,以交通流特征数据及其识别结果作为训练数据集进行系统参数及模糊规则的训练与确定,直到误差在控制范围内,并进行系统检测和复核.仿真及其检测和复核结果表明系统预测的准确率在 95%以上.     

Ultimate strength assessment of simply supported pitted platings: A new stochastic approach based on Monte Carlo simulation

The ultimate strength assessment of platings affected by random corrosion wastage is a key factor for the reliable design of new ships and the structural health monitoring of aged structures, as pitting corrosion wastage significantly affects the ultimate capacity of platings under compression. In this respect, significant efforts have been undertaken in the last decade to assess the ultimate strength drop-off of pitted platings under compression and several interpolating design formulas, based on a large number of FE simulations, have been developed. Nevertheless, current Rules and guidelines don't provide any explicit strength check criterion for pitted platings. Hence, the main aim of current research is the development of a new framework for the ultimate strength assessment of pitted platings, based on a stochastic approach and the endorsement of Monte Carlo simulation. A new formula, which allows evaluating the statistical properties of the plating ultimate strength in presence of random corrosion wastage, is developed. Subsequently, a benchmark study is carried out, to compare the new formula with the existing ones available in literature and a wide set of FE simulations, carried out by Ansys APDL. Current results are discussed, and the effectiveness of the new formula is verified.     

Fatigue assessment of ship structures based on equivalent wave probability (EWP) concept (1st report): Proposal of EWP concept and its verification by 8600TEU container ship's onboard hull monitoring

A long-term fatigue assessment method based on EWP concept is proposed. ‘Equivalent wave probability (EWP)’ is the fictitious (H_S, T_m)'s joint probability distribution function (JPDF), for which the frequency distribution of the stress variance R², f(R²), calculated by spectral fatigue assessment agrees with the observed one. By choosing probability function p(R²) to fit f(R²), the R²'s statistical model (R2SM) which represents the relation between the EWP parameters and R²'s population parameters is developed, and the Bayesian inference, which can estimate the EWP parameters from the measured R² data is developed. The EWP at the reference position (RP) can be determined by Bayesian inference from the measured R² through the R2SM at RP. To accurately estimate the measured f(R²) at the target position (TP) from the EWP at RP, an R2SM correction factor at TP, denoted by α_TP, is introduced in the process of assimilating R2SM. The resulting R2SM, which has been assimilated by Bayesian inference using measured data, is referred to as data-assimilated R2SM (DAR2SM). The fatigue assessment using EWP at RP as the input of DAR2SM at TP is called Bayes-EWP-DAR2SM analysis. The validity of Bayes-EWP-DAR2SM analysis is verified by using the long-term (about four years) multi(12)-position hull monitoring (HM) data of an 8,600TEU container ship. The fatigue damages estimated by Bayes-EWP-DAR2SM based solely on the stress history of a single sensor are in agreement with measurements with sufficient accuracy, independent of the chosen data assimilation period. This demonstrates that the multi-position fatigue assessment solely through HM at one RP based on EWP concept is realized.     

考虑电堆寿命的氢燃料电池汽车能量管理策略研究

提出了一种在满足动力性需求并且以氢燃料电池堆作为主要能源的前提下,能有效延长电堆使用寿命的能量管理策略。提出将需求功率 SG滤波后再进行规则控制的能量管理策略,将多种循环工况的结果进行手动优化后作为训练数据集,设计三输入一输出的自适应神经模糊推理系统控制器,根据其输出结果再进行一次滤波最终形成基于自适应神经模糊推理系统优化的能量管理策略。使用CLTC-P循环工况对能量管理策略进行仿真验证,结果表明,基于自适应神经模糊推理系统优化的能量管理策略能有效延长氢燃料电池剩余使用寿命,相比滤波加规则策略剩余使用寿命增加了33%,并能保持动力电池SOC处于适宜水平。