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Support Vector Machine Based Online Composite Helicopter Rotor Blade Damage Detection System

机译:基于支持向量机的在线复合直升机转子叶片损伤检测系统

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This work explores a feasibility of using vibratory hub loads and support vector machine (SVM) to predict damage and hence the life consumption of the composite helicopter rotor blade. Generally, the initial part of the composite's life is dominated by matrix cracking; the intermediate part by debonding/delamination and the final failure due to fiber breakage. The simulated hub loads under various damage levels are obtained using a comprehensive aeroelastic analysis of the composite rotor blade with physics based damage modes and are then linked with the life consumption of the blade using a phenomenological model. The SVM is used for classification of the useful life of the blade into three classes which are useful to decide the prognostic action. The performance of the blade damage detection system is demonstrated using simulated hub loads obtained using a two-cell airfoil section representing the stiff-inplane blade. The model based hub load variations are contaminated with noise to simulate the real data. It is observed that the SVM based damage detection system is more robust, reliable and easy to implement than the rotating frame measurement based methods.
机译:这项工作探索了使用振动轮毂负载和支持向量机(SVM)来预测复合材料直升机旋翼桨叶的损坏以及使用寿命的可行性。通常,复合材料寿命的开始部分主要是基体开裂。中间部分通过脱胶/分层和由于纤维断裂而导致的最终破坏。使用基于物理的损伤模式,通过对复合材料转子叶片进行全面的气动弹性分析,可以获得在各种损伤水平下的模拟轮毂载荷,然后使用现象学模型将其与叶片的寿命消耗联系起来。 SVM用于将刀片的使用寿命分为三类,这三类有助于确定预后措施。叶片损坏检测系统的性能通过使用模拟的轮毂载荷进行了演示,该载荷是使用代表刚性平面叶片的两格翼型截面获得的。基于模型的轮毂负载变化被噪声污染,以模拟实际数据。可以观察到,与基于旋转框架测量的方法相比,基于SVM的损坏检测系统更加健壮,可靠且易于实施。

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