Overview of Mainstream Turbine Fault Detection Technologies and Development Prospects

Wenzheng Liu

doi:10.54097/hy0zyc64

Authors

Wenzheng Liu

DOI:

https://doi.org/10.54097/hy0zyc64

Keywords:

Turbine faults, Detection techniques, Mainstream technologies, Emerging trends

Abstract

The turbine is the ‘heart’ of the ship, and its fault detection technology is of great significance. The technology has gone through the transformation from artificial experience detection to modern intelligent detection. The current mainstream technology is based on vibration analysis, oil analysis, infrared thermal imaging and expert systems, each with its own principles, application scenarios, advantages and disadvantages. However, they face challenges such as complex detection environment, data accuracy and technology applicability. Emerging trends such as big data, artificial intelligence and fault detection fusion and multi-technology fusion, to solve the challenge of providing new ideas, various types of technology needs to be optimised towards multi-technology fusion, intelligent direction to adapt to the industry's development needs.

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References

[1] Aditi Baral, et al. "Fault Detection in Turbines Using Machine Learning: A study of the capabilities of Various Classification Algorithms." IOP Conference Series: Materials Science and Engineering 1314. 1 (2024), 2.

[2] Zhen Wu,and Tianzhen Wang. "An EGLOF method for tidal stream turbine blade impact fault detection." Journal of Physics: Conference Series 2823. 1 (2024), 32.

[3] Naga Venkata Rama Subbarao Tadepalli,and Ramji Koona. "Gas turbine aero engine fault detection using Geo-TLSVM and digital twin with multimodal data analysis." Engineering Research Express 6. 1 (2024), 56-58.

[4] Nadir Fenghour,Messaoud Bouakkaz,and Elias Hadjadj. "Utilizing Principal Component Analysis for the Identification of Gas Turbine Defects." Journal of Failure Analysis and Prevention 24. 1 (2023), 67-80.

[5] Xie Tao, et al. "Impact fault detection for marine current turbines blade via MEGK-means and PCA under variable marine conditions." Measurement Science and Technology 34. 9 (2023), 6.

[6] Hadroug Nadji, et al. "Implementation of Vibrations Faults Monitoring and Detection on Gas Turbine System Based on the Support Vector Machine Approach." Journal of Vibration Engineering & Technologies 12. 3 (2023), 87-88.

[7] Liu Jiao, et al. "Early fault detection of gas turbine hot components under different ambient and operating conditions." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 235. 13 (2021), 58.