| Intelligent Force-Measurement System Use in Shock Tunnel | |
Wang YP(汪运鹏) ; Jiang ZL(姜宗林)
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| Source Publication | SENSORS
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| 2020-11-01 | |
| Volume | 20Issue:21Pages:6179 |
| ISSN | 1424-8220 |
| Abstract | The inertial vibration of the force measurement system (FMS) has a large influence on the force measuring result of aircraft, especially on some tests carried out in high-enthalpy impulse facilities, such as in a shock tunnel. When force tests are conducted in a shock tunnel, the low-frequency vibrations of the FMS and its motion cannot be addressed through digital filtering because of the inertial forces, which are caused by the impact flow during the starting process of the shock tunnel. Therefore, this paper focuses on the dynamic characteristics of the performance of the FMS. A new method-i.e., deep-learning-based single-vector dynamic self-calibration (DL-based SV-DSC) of an impulse FMS, is proposed to increase the accuracy of aerodynamic force measurements in a shock tunnel. A deep-learning technique is used to train the dynamic model of the FMS in this study. Convolutional neural networks with a simple structure are applied to describe the dynamic modeling so that the low-frequency vibration signals are eliminated from the test results of the shock tunnel. By validation of the force test results measured in a shock tunnel, the current trained model can realize intelligent processing of the balance signals of the FMS. Based on this new method of dynamic calibration, the reliability and accuracy of force data processing are well verified. |
| Keyword | artificial intelligence BALANCE SYSTEM deep learning DESIGN dynamic calibration FLOWS force-measurement system strain-gauge balance |
| DOI | 10.3390/s20216179 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000589316100001 |
| WOS Research Area | Chemistry ; Engineering ; Instruments & Instrumentation |
| WOS Subject | Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
| Funding Organization | NATIONAL NATURAL SCIENCE FOUNDATION OF CHINANational Natural Science Foundation of China (NSFC) [11672357} |
| Classification | 二类/Q1 |
| Ranking | 1 |
| Contributor | Wang, YP |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/85433 |
| Collection | 高温气体动力学国家重点实验室 |
| Affiliation | 1.{Wang Yunpeng, Jiang Zonglin} Chinese Acad Sci Inst Mech State Key Lab High Temp Gas Dynam Beijing 100190 Peoples R China 2.{Jiang Zonglin} Univ Chinese Acad Sci Sch Engn Sci Beijing 100049 Peoples R China |
| Recommended Citation GB/T 7714 | Wang YP,Jiang ZL. Intelligent Force-Measurement System Use in Shock Tunnel[J]. SENSORS,2020,20,21,:6179.Rp_Au:Wang, YP |
| APA | 汪运鹏,&姜宗林.(2020).Intelligent Force-Measurement System Use in Shock Tunnel.SENSORS,20(21),6179. |
| MLA | 汪运鹏,et al."Intelligent Force-Measurement System Use in Shock Tunnel".SENSORS 20.21(2020):6179. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| Jp2020392.pdf（2149KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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