| 基于Labview的伺服系统故障定位技术研究与实现 |
| |
| 引用本文： | 李文俊.基于Labview的伺服系统故障定位技术研究与实现[J].大众科技,2014(10):18-21. |
| |
| 作者姓名： | 李文俊 |
| |
| 作者单位： | 中国船舶重工集团公司第七一〇研究所,湖北 宜昌,443003 |
| |
| 摘 要： | 现代伺服系统规模庞大,结构复杂,且通常工作环境恶劣,故障发生率高,故障诊断费时费力。为了提高伺服系统故障诊断定位效率,基于故障树分析和虚拟仪器技术相结合在LabView软件平台上开发了伺服故障诊断定位系统。设计了一种基于最小割集表示的等价故障树的,结合模拟退火粒子群算法对神经网络的训练进行优化,使其故障诊断定位响应时间和准确度都显著提高。最后实验证明所设计系统采用的分析算法能够快速准确的进行故障诊断定位,对故障诊断定位技术的发展具有一定的参考和实际意义。
|
| 关 键 词： | Labview 故障树 模拟退火粒子群 伺服系统 故障定位 |
Research and implementation of a fault-location technology for servo system based on labview |
| |
| Abstract: | Modern servo system is large-scale and complex. It often has harsh working-conditions, so it has a high failure-rate. The fault diagnosis is time-consuming. In order to improve the efficiency of the servo system fault diagnosis and fault location, fault diagnosis and fault location system has be designed and implemented based on the technology of fault tree analysis that combined with virtual instrument in the Labview software platform. Designed a algorithm that combines the algorithm which uses minimum cut set to represent the equivalent fault tree with the algorithm which is Particle Swarm Optimization with simulated annealing to optimize the training of the neural network. The method makes the better response-time and the better accuracy. Finally, the experiment proves that the algorithm make fault diagnosis and fault location better, the method has some reference and practical significance for the development of the technology of fault diagnosis and fault location. |
| |
| Keywords: | Labview fault tree particle swarm optimization with simulated annealing servo system fault location |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
