| 基于改进LS-SVM的航空发动机传感器故障诊断与自适应重构控制 |
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| 引用本文： | 蔡开龙,谢寿生,杨伟,吴勇.基于改进LS-SVM的航空发动机传感器故障诊断与自适应重构控制[J].航空动力学报,2008,23(6):1118-1126. |
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| 作者姓名： | 蔡开龙 谢寿生 杨伟 吴勇 |
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| 作者单位： | 1. 空军工程大学,工程学院,西安 710038;空军第一航空学院,信阳 464000
2. 空军工程大学,工程学院,西安 710038 |
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| 基金项目： | 军队科研项目
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空军工程大学院优秀博士论文创新基金 |
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| 摘 要： | 提出了一种基于改进LS-SVM的航空发动机传感器故障诊断与自适应重构控制方法.该方法通过给误差变量赋予不同权值因子提高LS-SVM的鲁棒性,采用修剪算法提高LS-SVM的稀疏性;该方法从某涡扇发动机输入输出空间中建立其正常模型,采用阈值判别法对传感器故障进行实时监视与诊断,并用模型输出值代替故障传感器测量值反馈回闭环控制系统,实现对发动机的自适应重构控制.仿真结果表明,该方法能及时准确地定位故障,并进行有效的自适应重构控制.
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| 关 键 词： | 航空、航天推进系统 航空发动机 改进最小二乘支持向量机(LS-SVM) 传感器 故障诊断 自适应重构控制 |
| 收稿时间： | 2007/5/25 0:00:00 |
| 修稿时间： | 2007/9/17 0:00:00 |
Fault diagnosis and adaptive reconfiguration control for sensors in aeroengine based on improved least squares support vector |
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| CAI Kai-long,XIE Shou-sheng,YANG Wei and WU Yong.Fault diagnosis and adaptive reconfiguration control for sensors in aeroengine based on improved least squares support vector[J].Journal of Aerospace Power,2008,23(6):1118-1126. |
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| Authors: | CAI Kai-long XIE Shou-sheng YANG Wei and WU Yong |
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| Affiliation: | The Engineering Institute, Air Force Engineering University, Xi'an 710038, China;The First Aeronautic Institute of the Air Force, Xinyang 464000, China;The Engineering Institute, Air Force Engineering University, Xi'an 710038, China;The Engineering Institute, Air Force Engineering University, Xi'an 710038, China;The Engineering Institute, Air Force Engineering University, Xi'an 710038, China |
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| Abstract: | A method of fault diagnosis and adaptive reconfiguration control based on improved least squares support vector machine(LS-SVM) was presented for sensors in aeroengine control system.LS-SVM robustness was improved by adding weighed values to errors,and its sparseness was improved by clipping algorithm.Some turbofan engine normal models were set up with improved LS-SVM.The threshold discriminance was used to real-timely watch and diagnose sensors fault.Adaptive reconfiguration control for aeroengine was realized by model output which is fed back to closed loop control system in replacement of fault sensor measurements.The simulation results show that the proposed method can exactly diagnose sensor faults in time,and also effectively realize adaptive reconfiguration control. |
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| Keywords: | aerospace propulsion system aeroengine improved least squares support vector machine(LS-SVM) sensors fault diagnosis adaptive reconfiguration control |
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