加速寿命试验三参数威布尔分布的极小变异-极大似然估计

目的 在加速试验中,对寿命服从三参数威布尔分布的产品进行可靠性评估与寿命预测,解决形状参数小于1时传统方法难以计算的问题。方法 利用三参数威布尔分布与指数分布之间的转换关系,以变异系数误差最小为优化目标,在确定最优位置参数估计值的基础上,应用拟极大似然方法估计分布模型中的其余参数,建立极小变异–极大似然估计（MV-MLE）。根据加速寿命试验中失效机理不变的原则,在失效机理等同条件下,将该方法推广至多应力水平下的可靠寿命评估。结果 在单一应力与多应力水平下,通过仿真模拟验证了所提方法的有效性。与传统方法相比,在小样本条件下,所提方法可提高形状参数（机理等同性参数）估计精度40%以上。结论 所提方法对于三参数威布尔分布的参数估计和寿命评估具有较高精度,能够有效克服传统方法的不足,在加速寿命试验评估中具有良好的应用效果。     

Location wise comparison of mixture distributions for assessment of wind power potential: A parametric study

Scientific literature discussed various types of mixture models and models derived from maximum entropy principle using short-term wind speed data for their relative assessment. The literature on suitability of these mixture models for long-term data is rarely available. However, for correct assessment of wind power potential both wind speed and wind direction are equally important. Therefore, in this paper, both wind speed and wind direction are simultaneously analyzed using several types of mixture distribution and compared the same with conventional Weibull distribution. For wind speed and wind power density assessment, the mixture distributions such as Weibull--Weibull distribution, Gamma--Weibull distribution, Truncated Normal--Weibull distribution, Truncated Normal--Normal distribution, proposed Truncated Normal--Gamma distribution and Gamma--Gamma distribution along with MEP-distribution are compared with conventional 2-parameter Weibull distribution. Similarly, for wind direction analysis, the finite mixtures of von-Mises distribution are compared with conventional von-Mises distribution. Judgment criteria include R², RMSE, Kolmogorov--Smirnov test and relative percentage error in wind power density. The sites selected are the three onshore locations of India, viz., Calcutta, Trivandrum, and Ahmedabad. The results show that for wind speed assessment, mixture distribution performs better than the conventional Weibull distribution for analyzing wind power density. However, location wise comparison of all mixture distribution is of prime importance. For wind direction analysis, finite mixture of two von-Mises distributions proved to be a suitable candidate for Indian climatology.     

Wind power potential assessment for three buoys data collection stations in the Ionian Sea using Weibull distribution function

The present article utilizes wind measurements from three buoys data collection stations in Ionian Sea to study the wind speed and power characteristics using the Weibull shape and scale parameters. Specifically, the site dependent, annual, and monthly mean patterns of mean wind speed, Weibull parameters, frequency distribution, most probable wind speed, maximum energy carrying wind speed, wind power density and wind energy density characteristics have been analyzed. The Weibull distribution was found to represent the wind speed distribution with more than 90% accuracy, in most of the cases. Moreover, the correlation between the percentages of times the wind speed was above cut-in-speed and the measured mean wind speed for the three selected sites, as the correlation between the aforementioned percentages and the scale parameter c were examined and were found linear. At all these sites, no definite increasing or decreasing trends in annual mean wind speed values could be detective over the data reporting period. The mean values of wind speed, scale parameter, most probable wind speed, maximum energy carrying wind speed, wind power and wind energy density values showed higher values during winter time and lower in summer time in Pylos and Zakynthos. Moreover, Pylos and Zakynthos were found to be the best sites from wind power harnessing point of view.     

可靠性数据在民机故障诊断中的应用研究

可靠性数据是故障统计历史信息的记录,数据内隐含着大量对维修人员排故具有指导意义的信息,为达到提高工作效率,减少排故时间,以保证航班正点运营的目的,提出将可靠性数据应用于民机故障诊断的计算模型。利用从可靠性报表中收集到的数据对某航空公司主力机型A320-200飞机的空调系统常发故障进行诊断,首先用粗糙集(RS)对8个可能导致温度控制组件超温故障的部件进行分析,初步总结出3个故障源,然后计算综合故障概率,最后用Weibull分布验证以上诊断结论。结果表明,该法的引入能实现故障源的精确定位,并在实际中成功排故,大大缩短维修时间。     

Dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain)

In this study we developed a dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain). The data used to develop the model were obtained from a network of permanent plots, of between 10 and 55-year-old, which the Unidade de Xestión Forestal Sostible (Sustainable Forest Management Unit) of the University of Santiago de Compostela has set up in pure plantations of this species of pine in its area of distribution in Galicia. In this model, the initial stand conditions at any point in time are defined by three state variables (number of trees per hectare, stand basal area and dominant height), and are used to estimate stand volume, classified by commercial classes, for a given projection age. The model uses three transition functions expressed as algebraic difference equations of the three corresponding state variables used to project the stand state at any point in time. In addition, the model incorporates a function for predicting initial stand basal area, which can be used to establish the starting point for the simulation. This alternative should only be used when the stand is not yet established or when no inventory data are available. Once the state variables are known for a specific moment, a distribution function is used to estimate the number of trees in each diameter class, by recovering the parameters of the Weibull function, using the moments of first and second order of the distribution (arithmetic mean diameter and variance, respectively). By using a generalized height–diameter function to estimate the height of the average tree in each diameter class, combined with a taper function that uses the above predicted diameter and height, it is then possible to estimate total or merchantable stand volume.     

北京市大气环境二氧化硫浓度分布初探

利用北京市大气自动监测系统冬季逐时二氧化硫浓度监测资料，分析研究了对数正态分布，Ｗｅｉｂｕｌｌ分布，指数分布等常用分布模型对监测资料人布推迟合的适用性，并估算出各种分布模型的参数值。研究发现城区及高百分位数二氧化硫浓度频率分布符合Ｗｅｉｂｕｌｌ分布，近郊及背景站的浓度分布符合常用的对数正态分布，二氧化硫浓度的频率分布不符合指数分布规律。     

基于Weibull分布的测控装备寿命预测方法研究

目的利用寿命预测技术定期对测控装备的状态进行评估,挖掘装备潜在使用价值,降低出现故障的风险,为装备的更新维护提供参考依据。方法分析测控装备的特点,针对性地选用基于数据驱动的寿命预测技术,并重点分析基于Weibull分布的测控装备的寿命预测方法。结果通过数学公式推导,给出了采用最大似然估计法对二参数Weibull分布进行参数估计时的求解方法。结论对测控装备的寿命预测和可靠性评估提供科学的参考依据。     

逆Weibull分布环境因子及其统计分析

首先给出了逆Weibull分布环境因子的定义;然后给出了极大似然估计和Bayes估计方法,针对装备试验数据较少的情况,采用Fisher信息阵确定先验分布;最后对不同的估计方法进行了仿真分析,结果表明Bayes估计方法比极大似然估计有更高的精度和更小的偏差.     

A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing,Malaysia

Studies of wind direction receive less attention than that of wind speed; however, wind direction affects daily activities such as shipping, the use of bridges, and construction. This research aims to study the effect of wind direction on generating wind power. A finite mixture model of the von Mises distribution and Weibull distribution are used in this paper to represent wind direction and wind speed data, respectively, for Mersing (Malaysia). The suitability of the distribution is examined by the R² determination coefficient. The energy analysis, that is, wind power density, only involves the wind speed, but the wind direction is vital in measuring the dominant direction of wind so that the sensor could optimize wind capture. The result reveals that the estimated wind power density is between 18.2 and 25 W/m², and SSW is the most common wind direction for this data.     

基于复合应力加速寿命试验的高速列车电子产品可靠度计算方法研究

目的 解决目前加速寿命试验一般不用于估计产品可靠度,而采用可靠性预计和应力-强度模型计算可靠度时可能存在因参数误差而影响其估计精度的问题.方法 提出一种基于加速寿命试验的高速列车电子产品使用可靠度计算方法,采用温度、湿度、振动综合应力和广义Egring模型对高速列车电子产品开展加速寿命试验.结果 通过试验数据可评估出产...