针对现有监测报警方法难以适应工况变化和融合多元数据的缺点,提出基于Parzen窗估计的设备状态综合报警方法.该方法动态估计多元监测数据的联合概率密度函数,以局部分布边缘包络作为报警边界,随着监测数据的不断积累,逐步提高正常和故障概率分布估计的准确性,形成符合设备个性化状态发展历程的动态报警区域.通过对转子试验台和加热炉风机监测数据分析,验证了该方法的有效性.%To improve the adaptability of traditional monitoring and alarming methods and fuse multiple monitoring parameters, a comprehensive alarm method for condition monitoring based on Parzen window estimation was proposed. The joint probability density function of multiple monitoring parameters was estimated to describe the distribution of monitoring data. The alarm boundary was set with Parzen window function of monitoring data located in the marginal distribution area. Along with accumulation of monitoring data, the alarm boundary was continuously adjusted to accommodate new operation performance. The proposed method was evaluated with monitoring data measured on rotor test rig and heating furnace fan. Results showed that faults under different running conditions are well identified.
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