Fault diagnosis of flying control system servo actuator based on Elman neural network

Guopeng Zhang; Bo Wang

doi:10.1109/ICEMI.2011.6037944

Fault diagnosis of flying control system servo actuator based on Elman neural network

Guopeng Zhang^*, Bo Wang

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Servo actuator is one most important section of flying control system, and faults also often happen to it. The fault detection and diagnosis technology is seriously important to improve the reliability of servo actuator. The paper proposes a method of fault diagnosis based on Elman neural network, using its non-linear distributed processing and dynamic feature reflecting ability to detect servo actuator fault. Then, neural network algorithm is applied to simulation. The result indicated that the method could accurately identify the servo actuator fault. Meanwhile, compared with BP neural network, the advantage of Elman neural network in fault diagnosis is confirmed.

Original language	English
Title of host publication	Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011
Pages	46-49
Number of pages	4
DOIs	https://doi.org/10.1109/ICEMI.2011.6037944
Publication status	Published - 2011
Event	IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011 - Chengdu, China Duration: 16 Aug 2011 → 18 Aug 2011

Publication series

Name	Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011
Volume	4

Conference

Conference	IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011
Country/Territory	China
City	Chengdu
Period	16/08/11 → 18/08/11

Keywords

BP neural network
elman neural network
fault diagnosis
servo actuator

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10.1109/ICEMI.2011.6037944

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Zhang, G., & Wang, B. (2011). Fault diagnosis of flying control system servo actuator based on Elman neural network. In Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011 (pp. 46-49). Article 6037944 (Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011; Vol. 4). https://doi.org/10.1109/ICEMI.2011.6037944

@inproceedings{60eaa51d9ac545cf9fc1d862d27bdb2a,

title = "Fault diagnosis of flying control system servo actuator based on Elman neural network",

abstract = "Servo actuator is one most important section of flying control system, and faults also often happen to it. The fault detection and diagnosis technology is seriously important to improve the reliability of servo actuator. The paper proposes a method of fault diagnosis based on Elman neural network, using its non-linear distributed processing and dynamic feature reflecting ability to detect servo actuator fault. Then, neural network algorithm is applied to simulation. The result indicated that the method could accurately identify the servo actuator fault. Meanwhile, compared with BP neural network, the advantage of Elman neural network in fault diagnosis is confirmed.",

keywords = "BP neural network, elman neural network, fault diagnosis, servo actuator",

author = "Guopeng Zhang and Bo Wang",

year = "2011",

doi = "10.1109/ICEMI.2011.6037944",

language = "English",

isbn = "9781424481590",

series = "Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011",

pages = "46--49",

booktitle = "Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011",

note = "IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011 ; Conference date: 16-08-2011 Through 18-08-2011",

}

Zhang, G & Wang, B 2011, Fault diagnosis of flying control system servo actuator based on Elman neural network. in Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011., 6037944, Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011, vol. 4, pp. 46-49, IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011, Chengdu, China, 16/08/11. https://doi.org/10.1109/ICEMI.2011.6037944

Fault diagnosis of flying control system servo actuator based on Elman neural network. / Zhang, Guopeng; Wang, Bo.
Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011. 2011. p. 46-49 6037944 (Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fault diagnosis of flying control system servo actuator based on Elman neural network

AU - Zhang, Guopeng

AU - Wang, Bo

PY - 2011

Y1 - 2011

N2 - Servo actuator is one most important section of flying control system, and faults also often happen to it. The fault detection and diagnosis technology is seriously important to improve the reliability of servo actuator. The paper proposes a method of fault diagnosis based on Elman neural network, using its non-linear distributed processing and dynamic feature reflecting ability to detect servo actuator fault. Then, neural network algorithm is applied to simulation. The result indicated that the method could accurately identify the servo actuator fault. Meanwhile, compared with BP neural network, the advantage of Elman neural network in fault diagnosis is confirmed.

AB - Servo actuator is one most important section of flying control system, and faults also often happen to it. The fault detection and diagnosis technology is seriously important to improve the reliability of servo actuator. The paper proposes a method of fault diagnosis based on Elman neural network, using its non-linear distributed processing and dynamic feature reflecting ability to detect servo actuator fault. Then, neural network algorithm is applied to simulation. The result indicated that the method could accurately identify the servo actuator fault. Meanwhile, compared with BP neural network, the advantage of Elman neural network in fault diagnosis is confirmed.

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KW - elman neural network

KW - fault diagnosis

KW - servo actuator

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M3 - Conference contribution

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SN - 9781424481590

T3 - Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011

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BT - Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011

T2 - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011

Y2 - 16 August 2011 through 18 August 2011

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Zhang G, Wang B. Fault diagnosis of flying control system servo actuator based on Elman neural network. In Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011. 2011. p. 46-49. 6037944. (Proceedings - IEEE 2011 10th International Conference on Electronic Measurement and Instruments, ICEMI 2011). doi: 10.1109/ICEMI.2011.6037944

Fault diagnosis of flying control system servo actuator based on Elman neural network

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