@inproceedings{dc7573aa9c8c427fb7c1e9750b11d7bc,
title = "A Condition-Based Calibration Method for Flight Test Measuring Equipment",
abstract = "The degradation rate of the specification for the flight test measuring equipment varies with the actual working environment. The determination of the proper calibration time becomes a challenging job as the current method of calibrating test equipment in a fixed period is no longer suitable for the increasingly onerous flight test tasks. This paper proposes a method combining the degradation model and the extended Kalman particle filter algorithm to realize the state detection of the test instrument. Condition-based calibration can be achieved by this method, thereby avoiding flight test risks caused by insufficient calibration and economic waste caused by over-calibration. Finally, the equipment calibration cycle is optimized and the calibration efficiency is improved.",
keywords = "EKPF, condition-based calibration, degradation model, flight test measuring equipment, metrological characteristic",
author = "Renjian Feng and Ruoyan Xing and Yinfeng Wu and Ning Yu",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 1st International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 ; Conference date: 15-10-2020 Through 17-10-2020",
year = "2020",
month = oct,
day = "15",
doi = "10.1109/ICSMD50554.2020.9261747",
language = "英语",
series = "International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "69--73",
booktitle = "International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings",
address = "美国",
}