基于混沌变量的航空发动机性能监控与故障诊断

Aeroengine Performance Monitoring and Fault Diagnosis Based on Chaos Variable

针对在利用综合加权法计算表征发动机整体性能的综合指数时,各参数的权系数难于确定,本文提出利用混沌变量确定各参数的权系数,使优化得到的综合指数值比采用专家调查法所得到的综合指数值更能灵敏、准确地反映发动机整体性能的变化情况,提高了发动机性能正常与否的识别率,并以此来发现发动机潜在早期故障,防止故障的扩大。通过对某型涡扇发动机进行监控,证明该方法确实有效。

While the synthetic weighted method is used to calculate the synthetic exponent characterizing the overall engine performance, the weights of every parameter are difficult to determine. To solve this problem, a method of chaos variable was introduced. The synthetic exponent optimized by chaos variable is more sensitive and accurate than the one gained by the expert investigation method in reflecting the overall engine performance change. This method improves the successful rate of identifying whether the engine performance is normal or not, and can be used to detect the potential incipient fault, thus prevents the spread of the fault. The validity of this method is verified by monitoring a turbofan engine.