A CFD assessment of classifications for hypersonic inlet start/unstart phenomena
A CFD assessment of classifications for hypersonic inlet start/unstart phenomena
复制标题
高超声速入口启动/未启动现象分类的 CFD 评估
DOI：
10.1017/s0001924000002931
复制
发表时间：
2009-04-01
影响因子：
1.4
通讯作者：
Fan, Y.
中科院分区：
文献类型：
--
作者：
Chang, J.;Yu, D.;Fan, Y.
进气道启动/不启动检测是高超声速进气道研究的重要内容之一，也是超燃冲压发动机保护控制的基础。在地面和飞行试验中，不可避免地会给测量系统引入传感器噪声。如何克服或减弱传感器噪声和外界干扰的影响是发动机控制系统的一个重要问题。针对这一问题，对不同自由度和背压条件下的高超声速进气道二维定常内流场进行了数值模拟，分析了两种不同的进气道不起动现象。采用概率输出支持向量机获得了高超声速进气道起动/不起动的隶属度函数，并介绍了多分类器融合算法。分别讨论了分类精度随传感器噪声强度和分类器个数的变化。因此，引入支持向量机和多分类器融合算法可以有效地克服或减弱传感器噪声对高超声速进气道起动/非起动分类精度的影响。实用的融合分类器的数量需要在融合分类精度和分类系统的复杂度之间进行权衡。
Inlet start/unstart detection is one of the most important issues of hypersonic inlets and is also the foundation of protection controls of scramjets. In ground and flight tests, it is inevitably to introduce the sensor noises to the measurement system. How to overcome or weaken the influence of the sensor noises and the outer disturbances is an important issue to the control system of the engine. To solve this problem, the 2D inner steady flow of hypersonic inlets was numerically simulated in different freestream conditions and backpressures, and two different inlet unstart phenomena were analysed. The membership function for hypersonic inlet start/unstart can be obtained by using probabilistic output support vector machine, and the algorithm of multiple classifiers fusion is introduced. The variations of the classification accuracy with the intensity of the sensor noises and the number of the classifier were discussed respectively. In conclusion, it is useful to introduce the algorithm of support vector machine and multiple classifiers fusion to overcome or weaken the influence of the sensor noises on the classification accuracy of hypersonic inlet start/unstart. The number of the practical fusion classifiers needs a tradeoff between the fusion classification accuracy and the complexity of the classification system.