Application of dynamic ontology modeling techniques in power equipment fault prediction

Xinyao Feng, Yingwei Liang, Shaoguang Liu, Xiaolu Li, Hanyang Xie
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Abstract

Power equipment failure prediction method has the problem of high cumulative deterioration, and a power equipment failure prediction method based on dynamic ontology modeling technology is designed to solve the above problem. It evaluates the health status of power equipment, clarifies the performance degradation range of equipment according to the characteristics reflected in different stages, constructs a residual life judgment model by combining the mechanism of reliability function, clarifies the performance degradation conditions and failure threshold of power equipment, and optimizes the fault prediction process by using dynamic ontology modeling technology. The test results showed that the mean values of cumulative degradation of the power equipment failure prediction method in the paper and three other power equipment failure prediction methods are 1.612, 3.263, 3.207, and 3.234, respectively, indicating that the power equipment failure prediction method designed after incorporating dynamic ontology modeling technique has higher use value.
动态本体建模技术在电力设备故障预测中的应用
电力设备故障预测方法存在累积劣化率高的问题,针对这一问题,设计了一种基于动态本体建模技术的电力设备故障预测方法。对电力设备的健康状态进行评估,根据不同阶段所反映的特征明确设备的性能退化范围,结合可靠性函数机理构建剩余寿命判断模型,明确电力设备的性能退化条件和故障阈值,利用动态本体建模技术优化故障预测流程。试验结果表明,本文提出的电力设备故障预测方法与其他三种电力设备故障预测方法的累积退化均值分别为1.612、3.263、3.207和3.234,表明结合动态本体建模技术设计的电力设备故障预测方法具有更高的使用价值。
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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