摘要
提出了旋转机械启动过程故障诊断的一种新框架—混合SVM-HMM方法。该方法把SVM的输出信息通过sigmoid函数和高斯模型转化为后验概率的形式,并把它引入到HMM模型隐状态的观测概率。根据模拟实验数据计算表明,该方法是十分有效的。
A new method for diagnosis of rotary -machine in whole running - up process is proposed. This architecture converts the output of support vector machine (SVM) into the form of posterior probability which is computed by the combined use of sigmoid function and Gauss model, it acts as a probability evaluator in the hidden states of hidden Markov models (HMM). Experiments show the architecture is very effective.
出处
《汽轮机技术》
北大核心
2008年第6期445-447,450,共4页
Turbine Technology
基金
国家自然科学基金资助项目(50405023)