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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Aero-engine remaining useful life prediction based on multi-scale time-frequency fusion and composite attention mechanism

Li Gongxuna,b
Ye Qinga,b
a. School of Computer Science, b. Artificial Intelligence Research Platform, School of Computer Science, Yangtze University, Jingzhou Hubei 434023, China
DOI: 10.19734/j.issn.1001-3695.2025.07.0242

Abstract

To address issues such as the insufficient feature representation capability of traditional methods under complex operating conditions and the difficulty in modeling long-term and short-term temporal dependencies, this study proposes a novel aero-engine RUL prediction method based on Multi-scale Time-Frequency Fusion and Compound Attention Mechanism (MTFCA) . The method first converts time-domain sensor signals into frequency-domain representations via Fast Fourier Transform (FFT) , extracts features from the amplitude and phase spectra, and fuses them with the original time-domain signals to construct a multi-dimensional comprehensive feature representation. Subsequently, the approach introduces an efficient channel attention module to perform adaptive weight allocation on different feature channels, thereby enhancing key degradation features; the multi-scale residual temporal-aware unit adopts a dilated causal convolution structure to capture multi-scale temporal features; and the improved multi-head attention module incorporates a relative positional encoding mechanism to accurately model long-term and short-term dependencies in the sequence. Validation experiments on the C-MAPSS benchmark dataset show that the proposed method achieves excellent prediction performance on all four sub-datasets, with the average RMSE (Root Mean Square Error) and Score reduced by 13.50% and 24.87% respectively compared with 13 advanced prediction models. The research results demonstrate that this method can effectively capture multi-dimensional feature changes during the degradation process of aero-engines, providing a new technical approach for equipment health management under complex operating conditions.

Foundation Support

国家自然科学基金资助项目(62006028)
湖北省自然科学基金资助项目(2023AFB909)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.07.0242
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-10-27] Accepted Paper

Cite This Article

李龚珣, 叶青. 基于多尺度时频融合与复合注意力机制的航空发动机剩余使用寿命预测 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0242. (Li Gongxun, Ye Qing. Aero-engine remaining useful life prediction based on multi-scale time-frequency fusion and composite attention mechanism [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0242. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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