采用一组卡尔曼滤波器检测发动机传感器故障
FAILURE DETECTION OF ENGINE SENSORS WITH A BANK OF KALMAN FILTERS
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摘要: 在发动机全功能数字电子控制系统中,提高传感器工作的可靠性是十分重要的,除了不断对传感器本身的性能加以改进提高外,现在广泛地采用了余度技术。近二十年来对解析余度(Analyt ical Redundancy)进行了广泛的研究,解析余度(AR)方法是基于各状态变量之间存在的解析关系,在系统可观条件下,利用无故障的输出测量值去估计(构造)已故障传感器正常工作状态时的输出信息,从而实现对故障的检测、隔离与重构,保证控制系统具有预定的控制性能。Abstract: A detection method is presented for sensor failures in FADEC engine.In order to avoid that the output of a fault sensor affects other system states through state feadback,we use a bank of Kalman filters in which different combinations of sensor outputs as inputs of the filters are fed to each filter.According to the characteristics of innovation sequences of each filter,the failure can be detected and isolated.The sample frequencis are different in feedback control path and computation of innovation sequences.When a failure has occured in one sensor but before the failure affects other system states,the failure can be detected and isolated effectively.Therefore,the effects of failure on the outputs of other sensors are avoided.A digital simulation has been made for a rotational speed and temperature control system of a twin spool turbine engine.The simulation results show that this failire detection and isolation method is effective.
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