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Investigation of maximum likelihood percentile estimates for transformer asset management

机译：变压器资产管理最大百分点估计的最大可能性百分点

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To achieve a suitable balance between investment and reliability, it is necessary for utilities to be able to understand the long-term behaviour of asset populations in association with the `wear-out' stage of the so called `bathtub curve'. For the case of power transformers this is made difficult due to the presence of excessive amounts of censored data. Censored data presents partial information only, e.g. transformer survival times, inhibiting the ability of asset managers to correctly identify the long-term behaviour of the population through the use of traditionally statistical methods such as the Maximum Likelihood Estimation (MLE) procedure. This paper investigates the ability of the MLE to estimate strategic percentiles of asset populations that are used to assist asset management decisions. The analytical study is performed through a series of Monte Carlo simulations and statistical measures to determine the `quality' of estimates of the 2.5 and 97.5 percentiles of the Normal and Weibull distributions, under scenarios with different sample size and percentages of censored data. The results demonstrate the ability of the MLE procedure to identify percentiles in the near tail of the distribution with reasonable accuracy, and the pessimistic nature of percentiles in the far tail when the dataset contains levels of censoring normally found in transformer populations. The results are further verified through the calculation of approximate 95% confidence intervals.
机译：为了在投资和可靠性之间实现合适的平衡，公用事业公司都必须能够了解资产群体的长期行为与所谓的“浴缸曲线”的“磨损”阶段相关联。对于电力变压器的情况，由于存在过量的截取数据，这是困难的。审查数据仅提供部分信息，例如，变压器存活时间，抑制资产管理人员通过使用传统统计方法正确识别人口的长期行为，例如最大似然估计（MLE）程序。本文调查了MLE估算了用于协助资产管理决策的资产百分比的战略百分比。分析研究通过一系列蒙特卡罗模拟和统计措施进行，以确定2.5和97.5百分位的估计的估计的估计，在具有不同样本大小和审查数据的百分比的情况下的普通和Weibull分布的估计。结果证明了MLE程序以合理的准确性识别分布近尾百分比的能力，以及当数据集包含在变压器群体中通常发现的审查水平的远尾百分比的百分比的悲观性质。通过计算近似95％置信区间的计算进一步验证了结果。

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