| 基于模糊推理的物流车辆故障诊断专家系统 |
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| 引用本文： | 辛海奎,李蜀瑜. 基于模糊推理的物流车辆故障诊断专家系统[J]. 计算机系统应用, 2015, 24(8): 59-64 |
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| 作者姓名： | 辛海奎 李蜀瑜 |
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| 作者单位： | 陕西师范大学 计算机科学学院, 西安 710062;陕西师范大学 计算机科学学院, 西安 710062 |
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| 基金项目： | 国家自然科学基金(41271387) |
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| 摘 要： | 物流车辆故障诊断专家系统可以对物流车辆的故障进行诊断和排除. 为了提高该系统快速、准确诊断的能力, 在分析物流车辆的故障模式和故障机理的基础上, 建立故障树, 采用改进的CLIPS可以进行正向、反向两种模糊推理机制, 同时建立知识库管理系统对模糊规则和事实进行管理. 研究结果表明: 改进的CLIPS与VC++的结合, 使物流车辆故障诊断专家系统拥有模糊诊断故障的能力, 提高了物流车辆故障诊断的智能化水平.
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| 关 键 词： | 物流车辆 故障诊断专家系统 CLIPS 模糊诊断 |
| 收稿时间： | 2014-12-22 |
| 修稿时间： | 2015-02-09 |
Logistics Vehicle Fault Diagnosis Expert System Based on Fuzzy Reasoning |
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| XIN Hai-Kui and LI Shu-Yu. Logistics Vehicle Fault Diagnosis Expert System Based on Fuzzy Reasoning[J]. Computer Systems& Applications, 2015, 24(8): 59-64 |
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| Authors: | XIN Hai-Kui and LI Shu-Yu |
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| Affiliation: | College of Computer Science, Shaanxi Normal University, Xi'an 710062, China;College of Computer Science, Shaanxi Normal University, Xi'an 710062, China |
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| Abstract: | The fault diagnosis expert system for logistics vehicle could diagnose and troubleshoot logistics vehicle. In order to improve the performance of the system, the fault tree had been built based on the failure mode and failure mechanism of logistics vehicle. Then, the improved CLIPS which could carry out forward and backward reasoning was used, and the knowledge base management system was established to manage the fuzzy rules and facts. The results showed that the improved CLIPS coupled with VC++ was able to enhance the capability of the fault diagnosis expert system for diagnosing fault from the logistics vehicle fuzzily (i.e. fuzzy diagnosis) and improve the intelligence level of the system. |
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| Keywords: | logistics vehicle fault diagnosis expert system CLIPS fuzzy diagnosis |
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