| 何怡刚,白月皎,鲁 力.基于 DE-QPSO 算法的 MKRVM 对电容式RF-MEMS 开关的寿命预测方法[J].电子测量与仪器学报,2020,34(12):66-75 |
| 基于 DE-QPSO 算法的 MKRVM 对电容式RF-MEMS 开关的寿命预测方法 |
| MKRVM prediction of capacitive RF-MEMS switching life based on DE-QPSO algorithm |
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| DOI： |
| 中文关键词: 电容式 RF-MEMS 开关 BREMD MKRVM DE-QPSO 寿命预测 |
| 英文关键词:capacitive RF-MEMS switch BREMD MKRVM DE-QPSO life prediction |
| 基金项目:国家自然科学基金( 51577046)、国家自然科学基金重点项目( 51637004)、国家重点研发计划“ 重大科学仪器设备开发” 项目(2016YFF0102200)、装备预先研究重点项目(41402040301)资助 |
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| 中文摘要: |
| 为进一步研究电容式 RF-MEMS 开关在实际应用中存在的可靠性问题,提出一种基于差分进化的量子粒子群算法(DEQPSO)的多核相关向量机(MKRVM)方法对开关寿命进行预测。 首先采用了限制带宽经验模态分解(BREMD)来对实验过程
中获得的寿命数据进行去噪处理,提高数据的可靠性;其次采用 DE-QPSO 获取 MKRVM 的最优稀疏权重,并利用 MKRVM 算法
对此类开关进行寿命预测;最后利用实验获取的实际数据对所用方法的准确性进行测试。 实验结果表明,MKRVM 能在 0. 21 s
的时间内得到预测结果,所得数据的均方根为 3. 104 3×10
6
s,最接近原始数据的 3. 065 7×10
6
s;DE-QPSO 能在 0. 45 s 内得到优
化结果,方差为 7×10
-5
。 同时得到弹性系数在 4~ 16 N/ m 的范围内取值时开关寿命最长的结论。 |
| 英文摘要: |
| To further study the reliability problems of capacitive RF-MEMS switches in practical applications, a multi-core relevance
vector machine ( MKRVM) method based on differential evolution quantum particle swarm optimization (DE-QPSO) is proposed to
predict the switch lifetime. First of all, bandwidth restricted empirical mode decomposition (BREMD) is used to denoise the life data
obtained during the experiment to improve the data reliability; secondly, DE-QPSO is used to obtain the optimal sparse weight of
MKRVM, and the MKRVM algorithm is used to predict the life of such switches; finally, the actual data obtained by experiment is used
to test the accuracy of the methods. The experimental results show that MKRVM can obtain the prediction results within 0. 21 s. The root
mean square of the data is 3. 104 3×10
6
s, which is the closest to the original data of 3. 065 7×10
6
s; DE-QPSO can be optimized within
0. 45 s, the variance is 7×10
-5
. At the same time, it is concluded that the switch life is the longest when the elastic coefficient is in the
range of 4~ 16 N/ m. |
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