The failure prediction technique plays an important role in enhancing security, reducing life cycle cost and improving maintenance and logistic efficiency for equipment. The Hidden Markov Model (HMM) is one of failure prediction techniques to solve prognostic problem for buck switch power. The health degeneration process is analyzed in detail, and the output ripple voltage, inductance current and output power are selected as monitoring parameters. Each slate of sample series is used to train HMM. And then the observation sequences of signals to be measured are tested by the model above. So we can gel the likelihood possibility of signals 10 be measured. Experimental results show that this method can accurately predict switching power supply condition.%故障预测技术在提高设备的安全性、减少生命周期费用和提高维修保障效率等方面发挥了重要作用；采用隐马尔可夫模型(HMM)的故障预测方法,解决了Buck型开关电源的故障预测问题；详细分析了开关电源健康退化过程,并选择输出纹波电压、电感电流和输出功率作为监测参数；利用各个状态的样本序列来训练HMM,然后利用该模型对待测信号的观测序列进行测试,从而获得待测信号的似然概率,预测设备当前所在状态；实验结果表明,该方法可以准确地对开关电源进行故障预测.
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