【摘要】 在分析了生产过程两类故障的特点和常规故障诊断方法的缺陷的基础上 ,提出了生产过程早期故障检测与诊断方法。利用故障发生后过程系统中相关变量或征兆信息之间的解析冗余关系 ,将它们的动态趋势信息通过人工神经网络进行融合 ,避免了常规方法故障检测与诊断的滞后性。理论分析和仿真表明了该故障诊断方法的有效性。更多还原

【Abstract】 Based on the analysis of characteristics of two classes of technical process fault and defects of two familiar fault detection and diagnosis methods , this paper introduced an early fault detection and diagnosis method for technical process. Taking advantage of quatitative redundant relationship of some dependent variables or symptoms in the process system after fault happened , the method avoid the lag which often appeared in familiar fault detection and diagnosis methods by utilization of dynamic tread information of the variables or symptoms which is fused through artificial neural network. Theoretical analysis and simulation examples demonstrated that this method could achieve early fault detection and diagnosis for technical process.更多还原