Fault diagnosis of aero-engine endoscopic image processing based on BP neural network

Xiaomin Xie; Fan Zhang; Yong Zeng; Changkai Li

doi:10.1117/12.2503051

9 August 2018 Fault diagnosis of aero-engine endoscopic image processing based on BP neural network

Xiaomin Xie, Fan Zhang, Yong Zeng, Changkai Li

Author Affiliations +

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108065K (2018) https://doi.org/10.1117/12.2503051
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

Aiming at the shortcomings of endoscopic image processing and detection technology in aero-engine fault diagnosis and maintenance, this paper proposes an endoscopic image processing and diagnosis method based on BP neural network learning algorithm. In this method, the feature extraction technology of endoscopic image in aero-engine fault diagnosis is studied, and the effective feature parameters are extracted from the internal damage region of aero-engine. The BP neural network model is established to improve the endoscopic image processing effect and improve the level of fault diagnosis. Finally, the BP neural network endoscopic image processing and diagnosis mechanism is simulated and experimentally studied for a Boeing 787 engine, and the expected diagnosis effect is achieved.

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Xiaomin Xie, Fan Zhang, Yong Zeng, and Changkai Li "Fault diagnosis of aero-engine endoscopic image processing based on BP neural network", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108065K (9 August 2018); https://doi.org/10.1117/12.2503051

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KEYWORDS

Endoscopy

Neural networks

Image segmentation

Image processing

Image enhancement

Edge detection

Feature extraction

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