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模拟电路故障诊断的仿真研究
资料介绍
研究模拟电路故障诊断优化问题,模拟电路故障特征和故障诊断器之间密切相关,然而传统算法忽略两者之间的联系,无法获取最优故障诊断器,导致故障诊断正确率低。为了提高了模拟电路故障诊断正确率,提出一种特征和故障诊断器联合优化的模拟电路故障诊断算法。首先利用故障特征选择和分类器参数间的相互联系,建立故障诊断数学模型,然后采用遗传算法对模型进行求解,最后对具体电路故障进行仿真测试。测试结果表明,联合优化算法有效提高了模拟电路故障诊断正确率,为模拟电路故障诊断提供了一种新的工具。
In order to improve the analog circuit fault diagnosis accuracy rate,the paper put forward a feature and classifier combination optimization algorithm for fault diagnosis of analog circuits.First,fault feature selection and classifier parameter relationship were used to establish the fault diagnosis mathematical model.Then,the genetic algorithm was used to solve the model.Finally,the specific circuit fault simulation test was carried out.The test results show that,compared with the traditional algorithm,the optimization algorithm of analog circuit fault diagnosis can improve the correct rate of fault diagnosis in analog circuits.
部分文件列表
| 文件名 | 大小 |
| 模拟电路故障诊断的仿真研究.pdf | 269K |
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