航空发动机砂尘吸入物静电监测仿真实验

孙见忠; 姜衡; 陈颖达

doi:10.13224/j.cnki.jasp.2018.12.011

航空发动机砂尘吸入物静电监测仿真实验

doi: 10.13224/j.cnki.jasp.2018.12.011

1.
南京航空航天大学民航学院民航飞机健康监测与智能维护重点实验室,南京 211106
2.
南京航空航天大学民航学院,南京 211106
3.
南京航空航天大学能源与动力学院,南京 210016

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出版历程
- 收稿日期: 2017-11-19
- 刊出日期: 2018-12-28

Aero engine sand dust ingestion electrostatic monitoring simulation experiment

摘要

摘要: 提出了航空发动机砂尘吸入物静电监测的仿真实验方法，实验以软件ANSYS电磁场分析模块建立有限元模型为基础，模拟不同粒径、荷质比、运动速度及质量浓度情况下砂尘吸入物的静电感应信号，并分别从时域与频域对感应电荷与电压信号进行分析，研究砂尘吸入物的粒径及其他宏观参数与静电监测信号之间的关系，建立用以表征砂尘颗粒粒径大小的特征指标。基于IDMS(进气监测系统)感应电压信号功率谱密度分布建立了特征向量，并以其曼哈顿距离与欧氏距离作为特征指标表征砂尘颗粒粒径大小。经仿真实验验证：特征指标与砂尘粒径呈正相关，且不受砂尘吸入物运动速度及荷质比变化的影响，但受砂尘吸入物质量浓度影响。进一步研究将利用质量浓度对特征指标进行修正，并开展验证实验。
- 航空发动机 /
- 砂尘环境 /
- 颗粒粒径 /
- 静电监测 /
- 有限元分析 /
- 时频域分析
Abstract: A simulation experiment method for electrostatic monitoring of aero engine dust ingestion was proposed. Based on ANSYS electromagnetic field analysis module, a finite element model was established, the electrostatic induction signals of sand dust ingestion under different particle sizes, charge-mass ratios, moving speeds and mass concentrations were simulated experimentally, and the induced charge and voltage signals were analyzed from the time domain and frequency domain, respectively. The relationship between particle size and other macroscopic parameters of sand ingestion and electrostatic monitoring signals was studied to establish a characteristic index used to characterize the particle size of sand dust particles. The eigenvectors were established based on the power spectral density distributions of the IDMS(ingested debris monitoring system) induced voltage signals. The Manhattan distance and the Euclidean distance were used as characteristic indicators to characterize the sand particle size. Simulation results showed that the characteristic index was positively correlated with sand dust particle size, and it was not affected by the movement velocity and charge-mass ratio of sand ingestion, but affected by the sand dust ingestion mass concentration. Further studies will use quality concentration to correct the characteristics of the indicators and carry out verification experiments.
- aero engine /
- sand dust environment /
- particle diameter /
- electrostatic monitoring /
- finite element analysis /
- time domain analysis and frequency domain analysis

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