| 基于特征的机械设备状态趋势预报 |
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| 引用本文： | 李录平,史铁林,黄树红,韩守木. 基于特征的机械设备状态趋势预报[J]. 华中科技大学学报(自然科学版), 1998, 0(10) |
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| 作者姓名： | 李录平 史铁林 黄树红 韩守木 |
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| 作者单位： | 华中理工大学机械科学与工程学院(李录平，史铁林)，华中理工大学能源科学与工程学院(黄树红，韩守木) |
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| 摘 要： | 提出了机械设备故障严重度的概念；给出了故障严重度的两种计算方法，一种是基于单一特征指标的计算方法，一种是基于多特征指标的计算方法．将故障严重度作为一个综合指标来预报机械故障的变化趋势．给出了基于特征的神经网络故障趋势预报模型和网络训练样本的构造方法，并用实例验证了该预报模型的准确性．
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| 关 键 词： | 特征 状态 趋势 预报 |
Forecasting of the Feature-Based Machine State |
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| Li Luping,College of Mech. Sci. , Eng.,HUST,Wuhan ,China. Shi Tielin,Huang Shuhong,Han Shoumu. Forecasting of the Feature-Based Machine State[J]. JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE, 1998, 0(10) |
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| Authors: | Li Luping College of Mech. Sci. & Eng. HUST Wuhan China. Shi Tielin Huang Shuhong Han Shoumu |
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| Affiliation: | Li Luping,College of Mech. Sci. & Eng.,HUST,Wuhan 430074,China. Shi Tielin,Huang Shuhong,Han Shoumu |
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| Abstract: | A concept of fault severity of machines is defined. Two methods of the fault severity calcu- lation are proposed with one based on single feature, and the other based on multi-feature. The fault severity is used as a synthetic index to forecast the tendency for machine fault. Feature-based neural network model is used to forecast the tendency, and the method for constructing training samples of the network is developed. The accuracy of this model is tested by an example. |
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| Keywords: | feature state tendency forcast |
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