A diagnosis method on abrupt faults of nonlinear system in learning approach is provided by a detector which is designed to detect, identify and diagnose the faults in the dynamic nonlinear system.

针对一类非线性系统给出一种基于学习方法的突变故障诊断方法，设计了一个观测器，以此来检测、辨识和诊断一类非线性系统动态系统的故障。

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Based on decision tree combined strategy and multiple kernel learning support vector machines, a new fault diagnosis method is proposed to improve the precision and speed of fighter fault diagnosis.

为了提高歼击机故障诊断的准确性与实时性，提出一种基于决策树型组合策略的多重核学习支持向量机诊断方法。

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The method which has definite physical meaning, can change fault diagnosis model to adapt to the variability and uncertainty of the plant by learning the fault diagnosis err.

该方法物理意义明确，可以通过对故障诊断误差的学习，实时修正故障模型，实现对不确定性和慢时变性对象的鲁棒故障诊断。

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