Gas Turbine Engine and Sensor Fault Diagnosis Using Optimization Techniques
Gas Turbine Engine and Sensor Fault Diagnosis Using Optimization Techniques
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DOI：
10.2514/2.6050
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发表时间：
2002-09
影响因子：
1.9
通讯作者：
M. Zedda;Riti Singh
中科院分区：
文献类型：
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作者：
M. Zedda;Riti Singh
介绍了一种用于燃气涡轮机发动机部件和传感器性能分析的诊断系统。该系统估计的性能参数表示的故障状态的发动机部件的测量噪声和偏差的存在。测量不确定性甚至会影响发动机运行条件的参数设置。估计是通过一个ad hoc遗传算法的目标函数的boptimization。遗传算法使用精确的非线性稳态性能模型的发动机。该技术所需的唯一统计假设涉及测量噪声和故障传感器和发动机部件的最大允许数量，这是作为一个约束条件。该方法已在低涵道比涡扇发动机模型上进行了试验，结果表明，该方法具有较高的精度。
A diagnostic system is described for performance analysis of gas turbine engine components and sensors. The system estimates the performance parameters expressing the fault condition of the engine components in the presence of measurement noise and biases. The measurement uncertainty is supposed to affect even the parameters setting the operating condition of the engine. Estimation is performed through bptimization of an objective function by means of an ad hoc genetic algorithm. The genetic algorithm uses an accurate nonlinear steady-state performance model of the engine. The only statistical assumption required by the technique concerns the measurement noise and the maximum allowed number of faulty sensors and engine components, which is enclosed as a constraint. The technique has been thoroughly tested with the model of a low bypass ratio turbofan, and the results show the high level of accuracy achieved.