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摘要:
为实现航空发动机传感器与执行结构在故障情形下的故障幅值估计及信息重构，缓解故障对发动机性能的影响，在已有故障检测和故障隔离算法的基础上，提出一种基于修正的广义似然比（GLR）方法的信息重构算法。针对某型民用涡扇发动机的传感器与执行机构发生恒偏差与漂移故障的情形下进行了仿真验证。结果表明：基于修正的GLR方法对传感器和执行机构恒偏差和漂移故障的故障幅值估计具有较高的精度，两种故障情形下故障幅值的估计值的均方根误差均不超过0.005，故障部件信息重构后故障对系统性能的影响得到有效缓解。
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关键词:
- 航空发动机 /
- 故障诊断 /
- 故障幅值估计 /
- 广义似然比(GLR) /
- 信息重构
Abstract:In order to realize the fault magnitude estimation and information reconstruction of aero-engine sensor and actuator in fault condition and to accommodate the influence of fault on engine performance, based on the fault detection and fault isolation algorithms, a reconstruction algorithm based on a modified generalized likelihood ratio (GLR) method is proposed. Aimed at the constant deviation fault and drift fault of sensors and actuators of a certain type of civil turbofan engine, a simulation experiment was implemented. The simulation results show that the modified GLR method has higher accuracy for fault magnitude estimation of sensors and actuators with constant deviation and drift fault. The root mean square error of the fault magnitude estimation does not exceed 0.005 in both fault types. And after the information reconstruction of fault component, the effect of the fault on the system performance is effectively accommodated.
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图 1 航空发动机传感器和执行机构信息重构系统结构
Figure 1. Information reconstruction system structure of aero-engine sensors and actuators
图 4 Nl传感器漂移故障下，故障信息重构前后，主燃油流量和7个可测参数变化趋势
Figure 4. Variation of main fuel flow and seven measurable parameters before and after fault information reconstruction under Nl sensor drift fault
图 5 Nl传感器漂移故障下，故障信息重构前后，4个不可测参数变化趋势
Figure 5. Variation of four unmeasurable parameters before and after fault information reconstruction under Nl sensor drift fault
图 6 VBV执行机构漂移故障下，故障信息重构前后，主燃油流量和7个可测参数变化趋势
Figure 6. Variation of main fuel flow and seven measurable parameters before and after fault information reconstruction under VBV actuator drift fault
图 7 VBV执行机构漂移故障下，故障信息重构前后，4个不可测参数变化趋势
Figure 7. Variation of four unmeasurable parameters before and after fault information reconstruction under VBV actuator drift fault
表 1 恒偏差故障下的故障幅值估计RSME计算结果
Table 1. Calculation results of RSME of constant deviation fault magnitude estimation
传感器参数 RSME 执行机构参数 RSME Nl 0.001 3 Wfm 0.003 8 Nh 0.001 5 VBV 0.004 7 P25 0.002 1 VSV 0.003 6 Ps3 0.001 6 T25 0.002 3 T3 0.001 7 T45 0.002 4 
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表 2 漂移故障下的故障幅值估计RSME计算结果
Table 2. Calculation results of RSME of drift fault magnitude estimation
传感器参数 RSME 执行机构参数 RSME Nl 0.001 4 Wfm 0.004 2 Nh 0.001 8 VBV 0.004 8 P25 0.002 8 VSV 0.004 3 Ps3 0.002 1 T25 0.002 5 T3 0.002 1 T45 0.002 7
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