外涵静子叶片是大涵道比涡扇发动机气路的核心部件之一,外涵静子脱出是一种较为严重的故障模式,此故障可能会导致飞机或其他发动机部件损伤,进而造成灾难性事故。对外涵静子叶片脱出故障的预警是一项重要的工作。但因其早期特征不明显,...外涵静子叶片是大涵道比涡扇发动机气路的核心部件之一,外涵静子脱出是一种较为严重的故障模式,此故障可能会导致飞机或其他发动机部件损伤,进而造成灾难性事故。对外涵静子叶片脱出故障的预警是一项重要的工作。但因其早期特征不明显,现有的方法较难对此类故障进行有效的预警。因此,针对该问题,基于监控数据提出一种深度特征提取的支持向量数据域描述(Support vector data description,SVDD)的故障预警方法,以实现对外涵静子叶片脱出故障的早期预警。首先,采用基于发动机气路性能辨识的建模方法,建立发动机特定性能参数的观测模型对气路参数进行深度特征提取,以真实状态量与模型观测量的差值作为航空发动机是否发生故障的特征;然后利用SVDD算法建立决策边界,实现故障数据的自动划分,决策边界生成的阈值可在故障发生之前的一定时间之内给出告警;最后,经过多次计算,结果表明,在故障早期直至故障发生的区间内,表征其健康状态的性能参数都与观测量有较大的偏移,表明了所选特征的有效性。使用数据增强方法生成故障仿真数据与真实数据进行对比验证,预警时间比故障真实发生时间预警模型平均提前3.14 h。展开更多
The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimatio...The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimation accuracy of soft sensor models. Wiener model effectively describes dynamic and static characteristics of a system with the structure of dynamic and static submodels in cascade. We propose a soft sensor model derived from Wiener model structure, which is an extension of Wiener model. Dynamic and static relationships between secondary and primary variables are built respectively to describe the dynamic and static characteristics of system. The feasibility of this model is verified. Then the expression of discrete model is derived for soft sensor system. Conjugate gradient algorithm is applied to identify the dynamic and static model parameters alternately. Corresponding update method for soft sensor system is also given. Case studies confirm the effectiveness of the proposed model, alternate identification algorithm, and update method.展开更多
The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equa...The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.展开更多
文摘外涵静子叶片是大涵道比涡扇发动机气路的核心部件之一,外涵静子脱出是一种较为严重的故障模式,此故障可能会导致飞机或其他发动机部件损伤,进而造成灾难性事故。对外涵静子叶片脱出故障的预警是一项重要的工作。但因其早期特征不明显,现有的方法较难对此类故障进行有效的预警。因此,针对该问题,基于监控数据提出一种深度特征提取的支持向量数据域描述(Support vector data description,SVDD)的故障预警方法,以实现对外涵静子叶片脱出故障的早期预警。首先,采用基于发动机气路性能辨识的建模方法,建立发动机特定性能参数的观测模型对气路参数进行深度特征提取,以真实状态量与模型观测量的差值作为航空发动机是否发生故障的特征;然后利用SVDD算法建立决策边界,实现故障数据的自动划分,决策边界生成的阈值可在故障发生之前的一定时间之内给出告警;最后,经过多次计算,结果表明,在故障早期直至故障发生的区间内,表征其健康状态的性能参数都与观测量有较大的偏移,表明了所选特征的有效性。使用数据增强方法生成故障仿真数据与真实数据进行对比验证,预警时间比故障真实发生时间预警模型平均提前3.14 h。
基金Supported by the National Natural Science Foundation of China(61104218,21006127)the National Basic Research Program of China(2012CB720500)the Science Foundation of China University of Petroleum(YJRC-2013-12)
文摘The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimation accuracy of soft sensor models. Wiener model effectively describes dynamic and static characteristics of a system with the structure of dynamic and static submodels in cascade. We propose a soft sensor model derived from Wiener model structure, which is an extension of Wiener model. Dynamic and static relationships between secondary and primary variables are built respectively to describe the dynamic and static characteristics of system. The feasibility of this model is verified. Then the expression of discrete model is derived for soft sensor system. Conjugate gradient algorithm is applied to identify the dynamic and static model parameters alternately. Corresponding update method for soft sensor system is also given. Case studies confirm the effectiveness of the proposed model, alternate identification algorithm, and update method.
基金Supported by the Navy Equipment Department Foundation under Grant No. 2009(189)
文摘The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.
