| 基于专家系统的汽车衡故障传感器判别 |
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| 引用本文： | 杨静,李丽宏.基于专家系统的汽车衡故障传感器判别[J].传感器与微系统,2014,33(11):34-36. |
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| 作者姓名： | 杨静 李丽宏 |
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| 作者单位： | 太原理工大学信息工程学院,山西太原,030024 |
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| 摘 要： | 传感器是自动化设备的核心部件,传感器故障检测显得尤为重要。针对目前汽车衡维护、检修的困难,为有效准确判断故障传感器,提出了以径向基函数神经网络（RBFNN）预估值的初始化数据库专家系统判别方法。经现场测试准确率达到96%以上,从而有效简单地判定传感器好坏和识别故障传感器的位置。
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| 关 键 词： | 汽车衡 故障传感器判定 径向基函数神经网络 专家系统 |
Detection of truck scale fault sensor based on expert system |
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| YANG Jing,LI Li-hong.Detection of truck scale fault sensor based on expert system[J].Transducer and Microsystem Technology,2014,33(11):34-36. |
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| Authors: | YANG Jing LI Li-hong |
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| Affiliation: | (College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, China) |
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| Abstract: | Detection of sensor fauh is particularly important,because sensor is the core component of automation equipment. Aiming at difficulties in maintenance and inspection of present truck, an initialized database expert system based on radial basic neural network estimated value is proposed for judging the fault sensor effectively and accurately. The results of field testing accuracy can reach 96 %, thus determine quality of sensor effectively and simply and it also can identify location of the fault sensor. |
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| Keywords: | truck scale detection of fault sensor RBFNN expert system (ES) |
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