航天推进技术研究院主办
[1]王 珺,吕海鑫,陈景龙,等.液体火箭发动机健康状态智能检测方法[J].火箭推进,2021,47(04):52-58.
WANG Jun,LV Haixin,CHEN Jinglong,et al.Intelligent detection method of liquid rocket engine health state[J].Journal of Rocket Propulsion,2021,47(04):52-58.
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WANG Jun,LV Haixin,CHEN Jinglong,et al.Intelligent detection method of liquid rocket engine health state[J].Journal of Rocket Propulsion,2021,47(04):52-58.
液体火箭发动机健康状态智能检测方法
《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V]
卷:
47
期数:
2021年04期
页码:
52-58
栏目:
研究与设计
出版日期:
2021-08-31
- Title:
- Intelligent detection method of liquid rocket engine health state
- 文章编号:
- 1672-9374(2021)04-0052-07
- 分类号:
- V434,TP391
- 文献标志码:
- A
- 摘要:
- 液体火箭发动机健康检测技术是提高火箭安全性和可靠性的重要技术之一,对其进行研究具有重要的学术和工程应用价值。目前的健康检测方法大多基于特征提取和专家经验,智能检测技术水平急需提高。提出了一种基于卷积自编码器的液体火箭发动机健康状态智能检测方法,对发动机多传感器监测数据进行无监督的特征提取和重构,完成对训练集的学习,并基于隐含层特征和重构误差确定健康状态的中心和监测阈值,然后对测试集各机组状态进行识别,通过对各部件的损失计算可以进一步确定各部件的健康状态。提出方法通过热试车实验数据进行了验证,该方法在测试集上取得了88.9%的准确率,并能够监测整机及各部件的健康状态和退化趋势,结果表明提出方法的有效性和应用潜力。
- Abstract:
- The health state detection technology of liquid rocket engine is very important to improve the safety and reliability of rockets,which has important academic research and application value.The current research methods are mostly based on feature extraction and expert experience,while the research on intelligent detection technology needs to be improved.In this paper,Multi-component Two-stage Fusion Convolutional Denoising Auto-Encoder(MTAE)for intelligent detection of liquid rocket engine health state was proposed.First,unsupervised feature extraction and reconstruction of multi-sensor monitoring data were performed.After completing the learning of training set with the MTAE,the center of health and the monitoring threshold were determined based on the hidden layer features and reconstruction errors.Then,the state of each group of the testing set would be identified.In addition,the health state of each component could be further determined by calculating the loss of each component.Finally,the proposed method was verified by the data collected from the static firing test process.The method achieves an accuracy of 88.9% on the test set and could monitor the health and degradation trends of the whole engine and each component.The results show the effectiveness and application potential of the proposed method.
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备注/Memo
收稿日期:2021-03-05
作者简介:王珺(1980—),男,博士,研究员,研究领域为液体火箭发动机力学与环境。
更新日期/Last Update:
1900-01-01