【24h】

A Novel Prediction Method for Analog Circuits Based on Gaussian White Noise Estimation

机译:基于高斯白噪声估计的模拟电路预测新方法。

获取原文

摘要

Research on prediction about analog circuits is rarely conducted, and the only methods are prognosis of few special features extracted from output without guarantee of integrity and rationality of prognostic information, which hence influences prognostic precision. In this paper, a novel prediction method for analog circuits is proposed. In this method, time domain output waveforms in initial state and components degradation state are extracted at first, then white noise estimation is conducted to estimate the change between waveforms according to principles of noise estimation based on Kalman filter so as to obtain more reasonable fault indicators from more complete information, thereafter, a novel degradation tendency model of analog circuits is constructed according to newly obtained fault indicators, model adaption is conducted to the new model through particle filter, and prognostic method is conducted to remaining useful performance of analog circuits. Finally, experimental verification is conducted to the above conclusion.
机译:很少进行关于模拟电路的预测的研究,唯一的方法是从输出中提取少量特殊特征的预后,而不能保证预后信息的完整性和合理性,从而影响预后的准确性。本文提出了一种新的模拟电路预测方法。该方法首先提取初始状态和部件退化状态下的时域输出波形,然后根据基于卡尔曼滤波的噪声估计原理进行白噪声估计以估计波形之间的变化,从而获得更合理的故障指标。然后从更完整的信息出发,根据新获得的故障指标,建立一种新型的模拟电路退化趋势模型,通过粒子滤波对模型进行模型自适应,并采用预测方法对模拟电路保持有用的性能。最后,对上述结论进行了实验验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号