Features of Forecasting Reliability of 6—10 kV Overhead Electric Lines According to Statistics of Their Failures and Reconditionings

IF 0.3 Q4 ENERGY & FUELS
V. Basmanov, V. Kholmanskikh
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引用次数: 0

Abstract

This work is aimed at forecasting justification of the failure time of the 6—10 kV overhead electric lines (OEL) during the normalized period in its operation based on comparison with the statistics of failures and reconditionings on the previous intervals with the use of the OEL availability function, statistical availability coefficient, normalized forecasting interval and the accepted values of the availability coefficient on the forecasting interval. To achieve the goal set the OEL is described as an object of a multiple action, its failure and reconditioning flows are accepted as the simplest Poisson, and for the theoretical analysis of the variation character in the availability coefficient, the probability theory methods along with a mass service were used. The most significant result is justification of the use for the forecasting of the OEL failure time of a new convenient exponential expression of its availability function on the normalized period of time being forecasted. Unlike the accepted in the theory of reliability the availability function with two parameters T and Tr.av (average times of work and reconditionings), the proposed expression uses one parameter of distribution (virtual non-failure operating time). The significance of the results obtained consists in that controlling the dynamics of the variation in the statistical coefficient of availability of the OEL on the previous time intervals makes it possible to forecast its failure time during the forthcoming normalized periods of operation.
6 - 10kv架空线路故障及检修统计预测可靠性的特点
本工作旨在通过使用OEL可用性函数、统计可用性系数、,归一化的预测区间和预测区间上的可用性系数的可接受值。为了实现目标集,OEL被描述为多重作用的对象,其故障和修复流被认为是最简单的泊松,对于可用性系数的变化特征的理论分析,使用了概率论方法和大规模服务。最重要的结果是证明了在预测的归一化时间段上使用其可用性函数的新方便指数表达式来预测OEL故障时间的合理性。与可靠性理论中公认的具有两个参数T和Tr.av(工作和修复的平均时间)的可用性函数不同,所提出的表达式使用一个分布参数(虚拟无故障运行时间)。所获得结果的重要性在于,控制OEL可用性统计系数在先前时间间隔上的变化动态,可以预测其在即将到来的标准化运行期间的故障时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.70
自引率
33.30%
发文量
38
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