Prediction of APU Turbine Remaining Life Based on BAS_RVM
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College of Civil Aviation， Nanjing University of Aeronautics & Astronautics， Nanjing 211106， China
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摘要:
提出一种优化相关向量机的寿命预测方法，并用于对辅助动力系统（Auxiliary power unit， APU）涡轮的剩余寿命预测。首先，提出了改进的核函数，兼顾效率和精度，用天牛须搜索（Beetle antennae search， BAS）算法对相关向量机的核参数进行优化，建立寿命预测模型；然后，对历史数据进行分析，提取排气温度（Exhaust gas temperature，EGT）并进行修正、降噪，用多项式回归建立了EGT的涡轮性能退化模式库；最后，实例验证表明，文中算法在APU涡轮剩余寿命预测上与传统相关向量机相比效率提高40%，精度提高20%，通过敏感性分析确定了最佳的初始步长和输入维度。
Abstract:
An optimized relevance vector machine（RVM） life prediction method is proposed for the remaining life of auxiliary power unit （APU）. Firstly， an improved kernel function is proposed by taking into account both efficiency and accuracy. Furthermore， the beetle antennae search （BAS） algorithm is applied to optimize the kernel parameters of RVM. Secondly， through analyzing the historical A13 message and maintenance record data of an airline's APU， the exhaust gas temperature （EGT） parameters are extracted， corrected， and noise reduced， and the turbine performance degradation pattern library of EGT is established with polynomial regression. Finally， it is proved that compared with the traditional RVM， the efficiency and accuracy of the proposed algorithm in the APU turbine life prediction are improved by 40%， 20%， respectively. In addition， the optimal initial step size and input dimension in the model are determined based on sensitivity analysis.