FADS系统故障诊断方法研究

Qianlei Jia; Weiguo Zhang; Jingping Shi; Guangwen Li; Xiaoxiong Liu

doi:10.1051/jnwpu/20203861210

FADS系统故障诊断方法研究

Translated title of the contribution: Research on Fault Detection Method of FADS System

Qianlei Jia, Weiguo Zhang, Jingping Shi, Guangwen Li, Xiaoxiong Liu

School of Automation

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ² distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.

Translated title of the contribution	Research on Fault Detection Method of FADS System
Original language	Chinese (Traditional)
Pages (from-to)	1210-1217
Number of pages	8
Journal	Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume	38
Issue number	6
DOIs	https://doi.org/10.1051/jnwpu/20203861210
State	Published - Dec 2020

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title = "FADS系统故障诊断方法研究",

abstract = "In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.",

keywords = "Chi-square χ distribution, Fault detection, Flush air data sensing(FADS), Parity equation, Simulation",

author = "Qianlei Jia and Weiguo Zhang and Jingping Shi and Guangwen Li and Xiaoxiong Liu",

note = "Publisher Copyright: {\textcopyright} 2020 Journal of Northwestern Polytechnical University.",

year = "2020",

month = dec,

doi = "10.1051/jnwpu/20203861210",

language = "繁体中文",

volume = "38",

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TY - JOUR

T1 - FADS系统故障诊断方法研究

AU - Jia, Qianlei

AU - Zhang, Weiguo

AU - Shi, Jingping

AU - Li, Guangwen

AU - Liu, Xiaoxiong

PY - 2020/12

Y1 - 2020/12

N2 - In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.

AB - In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.

KW - Chi-square χ distribution

KW - Fault detection

KW - Flush air data sensing(FADS)

KW - Parity equation

KW - Simulation

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U2 - 10.1051/jnwpu/20203861210

DO - 10.1051/jnwpu/20203861210

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SN - 1000-2758

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JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University

JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University

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ER -

FADS系统故障诊断方法研究

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