基于HMM的传感器位置优化模型

The Optimization Model of Sensors Set Based on Hidden Markov Model

首先介绍了隐马尔可夫模型(HMM)理论,并对HMM健康状态评估的基本程序和方法进行了研究。HMM对系统健康状态评估具有所需样本少、识别精度高及分类明显等优点,利用隐马尔可夫模型对传感器的不同位置进行评估,从定量的角度对传感器位置的优劣进行评价,提出了利用隐马尔可夫模型对传感器在不同位置上的效果进行评价的方法。最后,利用齿轮箱实验数据,分析验证了方法的实施流程和有效性。

The theory of hidden Markov model is introduced firstly. The design processes and methods of PHM based on HMM are investigated. HMM is more smaller sample size and higher discerning accuracy. The rationality of sensors set which is based on the hidden Markov model is evaluated to take the quantitative point of view. Then the evaluating method of different sensors sets based on HMM is put forward. At last, the effectiveness of process and method is validated used the data of gear case.