| 引用本文: | 黄敏超,张育林,陈启智.模糊方向神经网络及其在故障检测与分离中的应用[J].控制理论与应用,1997,14(3):370~375.[点击复制] |
| HUANG Minchao，ZHANG Yulin and CHEN Qizhi.Fuzzy Direction Neural Network and Its Application to Fault Detection and Isolation[J].Control Theory and Technology,1997,14(3):370~375.[点击复制] |
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| 模糊方向神经网络及其在故障检测与分离中的应用 |
| Fuzzy Direction Neural Network and Its Application to Fault Detection and Isolation |
| 摘要点击 958 全文点击 437 投稿时间：1995-11-20 修订日期：1996-06-24 |
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| DOI编号 |
| 1997,14(3):370-375 |
| 中文关键词 故障检测与分离 模糊集 神经网络 方向超体 |
| 英文关键词 failure detection and isolation neural network fuzzy set direction body |
| 基金项目 |
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| 中文摘要 |
| 提出了一种用于多工况对象系统故障检测与分离的模糊方向神经网络．神经网络用模糊集表示故障模式，模糊集是由模糊超体聚集形成的集合体，模糊超体是由单位方向、夹角和两个半径确定．模糊方向神经网络能在一次循环学习中形成非线性方向边界，并不断融合新样本信息和精炼已存在的故障模式．发动机故障检测与分离的仿真研究验证了模糊方向神经网络分类器的优越性能. |
| 英文摘要 |
| A supervised learning fuzzy direction neural network used for fault detection and isolation (FDI) of the multi-condition process of a typical plant is proposed in this
paper. Direction neural network utilizes fuzzy sets as fault classes of the plant. Each
fuzzy set is an aggregate of fuzzy direction bodies. A fuzzy direction body is described
by a direction vector，an included angle and two radii. The fuzzy direction neural network can learn nonlinear direction failure boundaries in a single pass through the training data and provides the ability to incorporate new and refine exisiting failure classes without retraining. The FDI simulation of the engine system demonstrates the strong qualities of the fuzzy direction neural network. |