| 廖力力,杨书仪,胥小强,凌启辉,陈哲吾,戴巨川,何兴云.PSO-IWLF 算法优化的履带车辆振动测试传感布置[J].电子测量与仪器学报,2021,35(6):191-198 |
| PSO-IWLF 算法优化的履带车辆振动测试传感布置 |
| Sensor layout for vibration test of trackedvehicles optimized by PSO-IWLF |
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| DOI： |
| 中文关键词: PSO-IWLF 履带车辆半车 振动测试 传感器布置优化 MAC |
| 英文关键词:PSO-IWLF tracked semi-vehicles vibration test optimal sensor placement MAC |
| 基金项目:国防基础科研计划项目、湖南省自然科学基金面上项目（2020JJ4026）、湖南省研究生科研创新项目（CX2018B668）资助 |
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| 中文摘要: |
| 针对大型结构振动测试中传感布置优化问题,采用改进的粒子群优化算法,实现履带车辆半车振动响应测试中加速度
传感器的布置优化。 首先,提出一种惯性权值协同学习因子非线性动态调整的粒子群(PSO-IWLF)算法,并将其作为后续传感
器布置优化算法;其次通过履带车辆半车的有限元模态分析,获取节点不同阶模态振型值;最后依据模态置信准则(MAC)进行
履带车辆半车振动测试加速度传感器的布置优化计算,并通过振动响应实测分析验证了优化结果的有效性。 优化及实验结果
表明,PSO-IWLF 与标准 PSO 算法相比,寻优精度提高了 17. 5%,在初选 10 个测点中选择 2、3、4、5、9、10 等 6 个测点布置较
为合理。 |
| 英文摘要: |
| Aiming at optimal sensor placement in vibration testing of large structures, an improved particle swarm optimization was
adopted to optimize placement of acceleration sensors in the vibration responses test of tracked semi-vehicles. First, a particle swarm
optimization with nonlinear dynamic adjustment of inertial weight collaborative learning factor ( PSO-IWLF) was proposed,and it was
used as a subsequent optimal sensor placement algorithm. Then, the finite element modal analysis was performed on tracked semivehicles to obtain different orders’ mode shape of the node. Finally, according to the modal assurance criterion ( MAC), optimal
calculation of acceleration sensor placement in the vibration test of tracked semi-vehicles was carried out, and the validity of the
optimization results was verified through the vibration response test and analysis. The optimization and experimental results show that
compared with the standard PSO, the optimization accuracy of PSO-IWLF is improved by 17. 5%, and the selection of 2, 3, 4, 5, 9 and
10 among the 10 measuring points in the primary selection is more reasonable. |
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