| 基于径向基函数神经网络的柴油机故障诊断 |
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| 引用本文： | 肖健梅. 基于径向基函数神经网络的柴油机故障诊断[J]. 仪器仪表学报, 2005, 26(4): 355-358 |
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| 作者姓名： | 肖健梅 |
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| 作者单位： | 上海海事大学电气自动化系,上海,200135 |
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| 基金项目： | 上海市教委自然科学基金项目 (0 3IK0 9) |
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| 摘 要： | 提出一种应用径向基函数(RBF)神经网络解决故障诊断问题的方法,并将其应用于柴油机故障诊断与识别。在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数,从而使神经网络结构得到优化。实例仿真结果表明,RBF神经网络学习收敛较快,对故障识别性能好。
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| 关 键 词： | 柴油机 RBF神经网络 故障诊断 |
| 修稿时间： | 2003-06-01 |
Fault Diagnosis for Diesel Engines Based on RBFNN |
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| Xiao Jianmei. Fault Diagnosis for Diesel Engines Based on RBFNN[J]. Chinese Journal of Scientific Instrument, 2005, 26(4): 355-358 |
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| Authors: | Xiao Jianmei |
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| Abstract: | The application of radial basis function neural network (RBFNN) to fault diagnosis is presented and is applied successfully to fault diagnosis of diesel engines. A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure. The simulation results show that the method has better learning and diagnostic properties to complex faults. |
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| Keywords: | Diesel engine RBFNN Fault diagnosis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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