Blade fault localization with the use of vibration signals through artificial neural network: a data-driven approach

• Main Authors: Keng, Ngui Wai, Mohd Salman, Leong, Mohd Ibrahim, Shapiai, Hee, Lim Meng
• Format: Article
• Language: English
• Published: UPM Press 2023
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery; TL Motor vehicles. Aeronautics. Astronautics
• Online Access: http://umpir.ump.edu.my/id/eprint/38233/1/Blade%20fault%20localization%20with%20the%20use%20of%20vibration%20signals%20through%20artificial%20neural%20network_.pdf; http://umpir.ump.edu.my/id/eprint/38233/; https://doi.org/10.47836/pjst.31.1.04; https://doi.org/10.47836/pjst.31.1.04
• Institution: Universiti Malaysia Pahang

Turbines are significant for extracting energy for petrochemical plants, power generation, and aerospace industries. However, it has been reported that turbine-blade failures are the most common causes of machinery breakdown. Therefore, numerous analyses have been performed to formulate techniques f...