栏目

基于BP神经网络和NSGA-Ⅱ的离心压气机机匣处理槽参数优化

  • 陈金萍 ,
  • 叶顺宏 ,
  • 李颂
展开
  • (1.大连海洋大学应用技术学院,辽宁 大连 116300;2.辽宁工程技术大学机械工程学院,辽宁 阜新 123000;3.大同北方天力增压技术有限公司,山西 大同 037036)

Parameters Optimization of Centrifugal Compressor Casing Slot Based on BP Neural Network and NSGA-Ⅱ

  • CHEN Jinping ,
  • YE Shunhong ,
  • LI Song
Expand
  • (1.School of Applied Technology,Dalian Ocean University,Dalian 116300,China;2.School of Mechanical Engineering,Liaoning Technical University,Fuxin 123000,China;3.Datong North Tianli Supercharging Technology Co.,Ltd.,Datong 037036,China)

摘要

为获取离心压气机机匣处理槽的最优结构参数,针对某型离心压气机机匣处理的槽参数展开了优化工作,通过已有模拟数据建立BP神经网络预测模型,利用遗传算法(NSGA-Ⅱ)对槽的结构参数进行了多目标寻优工作。结果表明:优化后的结构参数为开槽宽度4 mm,槽中心位置为靠近叶轮前缘距离导风轮中段1.5 mm处。经过模拟分析,优化值对应的槽处理结构位置相对靠近叶轮前缘,使低速区域相对前移,改善了主通道内的流动情况,喘振边界在高转速下明显向小流量偏移,进一步拓宽了压气机稳定工作范围。

本文引用格式

陈金萍 , 叶顺宏 , 李颂 . 基于BP神经网络和NSGA-Ⅱ的离心压气机机匣处理槽参数优化[J]. 车用发动机, 2023 , 0(1) : 62 -68 . DOI: 10.3969/j.issn.1001-2222.2023.01.010

Abstract

In order to obtain the optimal structural parameters of a centrifugal compressor casing treatment slot, the optimization of centrifugal compressor casing slot parameter was carried out. A BP neural network prediction model was established based on the existing simulation data, and a multi-objective optimization of the slot structural parameters was carried out by using the genetic algorithm (NSGA-Ⅱ). The results show that the optimized structural parameters are the slot width of 4 mm and the slot center position of 1.5 mm from the middle section of air guide wheel near the leading edge of impeller. According to the simulation analysis, the slot treatment structure corresponding to the optimized value is relatively close to the leading edge of impeller, which makes the low-speed region relatively forward and improves the flow situation of main channel so as to shift the surge boundary obviously to the small flow rate at high speed, the stable working range of compressor widens.
Options
文章导航

/