Gas turbine health status assessment based on BP neural network

Dali Hou; Wen Liu

doi:10.1117/12.3004167

11 October 2023 Gas turbine health status assessment based on BP neural network

Dali Hou, Wen Liu

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128003W (2023) https://doi.org/10.1117/12.3004167
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Due to the harsh operating environment of gas turbines, their performance status will degrade with the growth of service life, which can even lead to unscheduled downtime in severe cases. The purpose of building the model is to provide guidance for the operation optimization and maintenance decision of the unit, and to improve the safety and reliability of equipment operation as much as possible. This paper uses BP neural network algorithm to establish a gas turbine health status assessment model, and verifies the accuracy of the model assessment through example analysis and research. The findings indicate that the model has demonstrated good evaluation performance and holds a certain level of practical significance in gas turbine health status assessment.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dali Hou and Wen Liu "Gas turbine health status assessment based on BP neural network", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128003W (11 October 2023); https://doi.org/10.1117/12.3004167

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available