| 残差归一化的强跟踪滤波器及其应用 | |
| 刘铭 ; 周东华 ; LIU Ming ; ZHOU Dong-hua | |
| 2010-06-09 ; 2010-06-09 | |
| 关键词 | 电力电子 强跟踪滤波器 故障诊断 残差归一化 Power electronics Strong tracking filter (STF) Fault diagnosis Residuals normalization TN713 |
| 其他题名 | NORMALIZED RESIDUALS BASED STRONG TRACKING FILTER AND ITS APPLICATION |
| 中文摘要 | 强跟踪滤波器通过对残差的强制白化而具有自适应的校正估计偏差和迅速跟踪状态变化的能力。对一类多输出非线性系统的研究发现，当各输出在数值上存在较大差异时，会导致无故障情况下不同输出值对应残差间数值上的较大差异，从而造成滤波器对于各残差的信息不对称，影响故障诊断的速度和精度。针对这一问题，该文提出了一种残差归一化的强跟踪滤波器方法。该方法通过在次优渐消因子的计算过程中对残差的归一化处理，达到平衡各残差间信息的效果，从而提高了故障诊断的速度和精度。仿真结果验证了该方法的有效性。; The strong tracking filter (STF) can reduce adaptively estimate bias and thus has ability to track abrupt changes in nonlinear systems. When large difference exists among the system outputs in multi-output systems, the difference among residuals will also be large when no fault occurs. This difference lead to information asymmetry in the filter residuals, and the speed and precision will be damaged. In this paper a residuals-normalized STF method is presented. In this method the residuals are normalized when computing the suboptimal fading factors. So the information of the residuals is balanced. Simulation results show that the speed and precision of fault diagnosis can be improved by use of this improved filter.; 国家自然科学基金项目(60025307，60234010) 国家973计划项目(2002CB312200) |
| 语种 | 中文 ; 中文 |
| 内容类型 | 期刊论文 |
| 源URL | [http://hdl.handle.net/123456789/58025]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | 刘铭,周东华,LIU Ming,等. 残差归一化的强跟踪滤波器及其应用[J],2010, 2010. |
| APA | 刘铭,周东华,LIU Ming,&ZHOU Dong-hua.(2010).残差归一化的强跟踪滤波器及其应用.. |
| MLA | 刘铭,et al."残差归一化的强跟踪滤波器及其应用".(2010). |
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