| 基于RBF网络的信息融合在SAMS故障诊断中的应用 |
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| 引用本文： | 樊春玲,金志华,张静.基于RBF网络的信息融合在SAMS故障诊断中的应用[J].中国惯性技术学报,2003,11(5):55-59. |
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| 作者姓名： | 樊春玲 金志华 张静 |
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| 作者单位： | 上海交通大学信息检测技术与仪器系,上海,200030 |
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| 摘 要： | 针对卫星姿态测量系统(SAMS)，将径向基函数RBF(Radial Basis Function)网络和多传感器信息融合技术相结合，并将其应用在系统的故障检测与诊断中。研究结果表明，此方法是可行有效的，可以提高系统的测量精度和性能。
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| 关 键 词： | RBF网络 信息融合 SAMS 故障诊断 卫星姿态测量系统 径向基函数网络 |
| 文章编号： | 1005-6734(2003)05-0055-05 |
| 修稿时间： | 2003年6月28日 |
Application of Data Fusion Based on RBF Networks for Fault Diagnosis of SAMS |
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| FAN Chun-ling,JIN Zhi-hua,ZHANG Jin.Application of Data Fusion Based on RBF Networks for Fault Diagnosis of SAMS[J].Journal of Chinese Inertial Technology,2003,11(5):55-59. |
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| Authors: | FAN Chun-ling JIN Zhi-hua ZHANG Jin |
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| Abstract: | In this paper, the Radial Basis Function (RBF) neural networks and multisensor data fusion technology are combined and used in the fault detection and diagnosis of sensors hardware faults in the Satellite Attitude Measurement System (SAMS). The fusion method of the RBF neural networks is adopted. By using the combination method, the outputs of the system are more accurate and reliable than each individual sensor. Research results show that this method is feasible and more effective, and can improve its performance-price-ratio. |
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| Keywords: | RBF networks multisensor information fusion satellite attitude measurement system fault diagnosis |
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