The accurate detection of abnormal sensing information in pressure vessel can achieve fault diagnosis and elimi-nation of pressure vessels. A method of pressure vessel abnormal information detection based on extraction of the sensor frequen-cy discrimination characteristics is put forward in allusion to wide stationarity and low detection accuracy of abnormal sensing in-formation. The data sampling for the abnormal sensing information in pressure vessel is performed,and then the nonlinear time series information flow modeling of the sampling data is conducted. ARMA model is used to analyze the time-frequency character-istics of pressure vessel abnormal information to realize signal detection in combination with the sensor frequency discrimination feature extraction. The simulation results show that the method has the high detection probability for pressure vessel sensing in-formation accurate detection.%对压力容器中的异常传感信息准确检测能实现压力容器故障诊断排除.针对压力容器异常传感信息宽平稳性强,检测准确度不高的问题,提出一种基于传感器鉴频特征提取的压力容器异常信息检测方法.首先对压力容器中的异常传感信息进行数据采样,对采样数据进行非线性时间序列信息流建模,采用ARMA模型分析压力容器异常信息的时频特征,结合传感器鉴频特征提取实现信号检测.仿真结果表明,采用该方法进行压力容器传感器信息检测的准确检测概率较高.
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