【作者】 艾进聪；

【导师】 王松岭；

【作者基本信息】 华北电力大学（河北） ， 热能工程， 2004， 硕士

【摘要】 针对离心风机的运行状态判别和多类故障诊断问题,论文首先对电厂离心风机几种常见机械故障进行实验模拟,对其产生机理、频谱特征等进行了试验研究;在此基础上,基于统计模式识别理论,对于初始特征生成、特征空间维数压缩、运行状态判别和故障分类等问题进行了研究,提出了特征空间异常判别方法和多子空间故障识别方法,诊断结果表明上述方法能有效解决离心风机的状态监测和故障识别问题;最后开发了离心风机状态监测与故障诊断的软硬件系统。更多还原

【Abstract】 In accordance with the problems of rotating machinery condition monitoring and fault diagnosis, several kinds of common mechanical faults is simulated in a large fan test-bed and the fault mechanism and its spectrum characteristic are researched. Based on which, a serial of problems are studied in conjunction with statistical pattern recognition techniques, such as initial feature obtaining, feature extraction, condition distinguishing, fault diagnosis, etc. the feature space abnormal state recognition method and the multi-KL subspace method are proposed. The value of the method has been showed in the fault diagnosis of fans. In the end, a fan performance monitoring and fault diagnosis system was developed in this thesis.更多还原