针对相关电子设备在运行中故障率不确定导致可靠度难以识别的问题,本研究设计了一个改进型的电子设备可靠性评估系统。利用平均无故障运行时间模型对电力设备的时间特征进行监测,采用最小二乘拟合设备的MTBF-T曲线,通过对设备可靠性发展趋势分析推测设备的运行寿命和故障发生概率。利用AMSAA技术对MTBF-T模型进行融合,获取该设备处于整个周期的相应阶段。采取长短期记忆网络算法提高本研究模型对电子设备故障的判别与预测的正确度。试验结果表明,通过本算法进行数据质量核查的准确度高达90%以上,表明该系统对提升故障判别准确度具有较强的实用性。

For the problem that the failure rate of related electronic equipment in operation is uncertain,resulting in difficult to identify the reliability.In this paper,an improved reliability evaluation system for electronic equipment is designed.The Mean Time Between Failure (MTBF-T) model is used to monitor the time characteristics of the power equipment,and the MTBF-T curve of the equipment is fitted by least squares.The operating life and failure probability of the equipment are predicted by analyzing the reliability development trend of the equipment.The MTBF-T model is fused with AMSAA technology to obtain the corresponding stage of the whole cycle of the equipment.The Long Short Term Memory (LSTM) algorithm is adopted to improve the accuracy of the model's identification and prediction of electronic equipment faults.The experiment results show that the accuracy of data quality verification by this algorithm is more than 90%,which indicates that the research system has strong practicability to solve the problem of improving the accuracy of fault discrimination.