期刊文献+

电冲击加速退化试验的雷达电路板故障趋势预测方法研究 被引量:1

Radar Circuit Board Fault Prediction Method Based on Electric Impact Accelerate Degradation Test
下载PDF
导出
摘要 以某型雷达18V20kHz信号板为研究对象,运用性能退化可靠性理论,对雷达电路板进行了可靠性分析;利用试验数据分析得到电冲击下雷达电路板性能退化规律;针对多性能退化参数故障顶测方法模型复杂求解困难的特点,将信号处理与性能退化理论相结合,提出了基于相像系数的多性能退化参数故障趋势预测方法;从信号特征提取角度出发,利用相像系数融合多个性能参数的退化特征解决了多性能参数特征提取的难点,然后利用Wiener过程描述相像系数的退化规律,进行建模,由于模型过于复杂,采用了MCMC方法进行参数估计;最后通过雷达电路板电冲击试验验证了该方法的有效性,同时也为多性能参数下雷达板级电路故障趋势预测提供了技术支撑。 Aiming at the insufficient of electric impact accelerate degradation test study, make a electric impact accelerate degradation test for 18 V20 KHz signal PCB of radar, and conclude the rule of performance degradation of radar circuit board in the environment of electric impact with the testing data. Aiming at the insufficient of multiple performance degradation parameters fault prediction method, combine sig- nal processing technology with performance degradation theory, present an new multiple performance degradation parameters fault prediction method based on resemblance coefficient. This article from the perspective of the signal feature extraction, integration of multiple perform- ance parameters degradation characteristics using resemblance coefficient, to solve the multi--feature extraction difficulties of multiple per- formance parameters. Then use the Wiener process to describe resemblance coefficient degradation for modeling, extrapolated life information of the product, and finally validity of this method was proved by the testing data, and provided technical support of the radar board--level cir- cuit fault prediction under multiple performance parameters.
出处 《计算机测量与控制》 北大核心 2014年第3期653-655,663,共4页 Computer Measurement &Control
基金 国家自然科学基金(61271153) 河北省重点基金(109635529)
关键词 电冲击试验 雷达电路板 故障预测 多性能参数 相像系数 退化建模 electric impact test radar circuit board fault prediction method multiple performance parameters resemblance coefficient degradation modeling
  • 相关文献

参考文献9

  • 1张庆志,鲍爱达,郭涛,孙韬.硅压力传感器振动可靠性试验与评估分析[J].计算机测量与控制,2012,20(5):1315-1317. 被引量:3
  • 2Meneghini M, Stocco A, Bertin Marco, et al. Time--dependent degradation of AIGaN/GaN high electron mobility transistors under reverse bias [J]. Applied Physics Letters, 2012, 100 (3): 033505 -033505 -3.
  • 3Tang L C, Chang D S. Reliability prediction using nondestructive accelerated degradation data: case study on power supplies [J]. IEEE Transactions on Reliability, 1995, 44 (4): 562- 566.
  • 4Lu S, Lu H, Kolarik W J. Multivariate performance reliability pre- diction in real--time E J3. Reliability Engineering and System Safe- ty, 2001, 72.. 39-45.
  • 5王玉明.基于性能退化数据的电子产品可靠性分析研究[D].石家庄:军械工程学院,2009.
  • 6Chen Z H, Zheng H R. Lifetime distribution based on degradation analysis [J]. IEEE Transactions on Reliability, 2005, 54 (1) : 3 - 10.
  • 7Jayaram J S R, Girish T. Reliability prediction through degradation data modeling using a quasi--likelihood approach [A]. Proceedings Annual Reliability and Maintainability Symposium [C], New York, 2005: 193-199.
  • 8Sarker, Bhaba R. Resemblance coefficient in group technology., a survey and comparative study of relational metrics [J]. Computers Industrial Engineering, 1996, 30 (1) 103 - 116.
  • 9屈直,黄高明,程远国,高敬.基于多特征参数的雷达信号调制方式识别方法[J].电光与控制,2012,19(11):31-34. 被引量:6

二级参考文献12

共引文献8

同被引文献12

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部