研究成果 / 2026 / 会议论文
A Transformer Approach for Remaining Useful Life Prediction and Fault Diagnosis of Mechanical Equipment
面向机械设备剩余寿命预测与故障诊断的 Transformer 方法
IOP Conference Series: Materials Science and Engineering · 012059 · 2026
摘要
原始英文摘要
Accurately estimating remaining useful life (RUL) and performing timely fault diagnosis are critical for ensuring the reliability and safety of industrial equipment. However, these tasks are often treated separately, reducing the effectiveness of maintenance decisions and limiting the use of sensor data. This study extends the Transformer architecture to simultaneously perform RUL prediction and multi-label fault classification within the same framework. Through a shared encoder using self-attention to capture temporal and cross-sensor dependencies, the model learns representations that capture machine health evolution and fault characteristics. Two output heads handle RUL regression and fault classification, while uncertainty-based loss weighting automatically balances the training of both tasks. The model is evaluated on the Microsoft Azure predictive maintenance dataset containing multi-sensor readings from 100 industrial machines. Results show that the proposed approach outperforms machine-learning and deep-learning baselines on both tasks, achieving high accuracy and strong robustness across test machines. By jointly predicting fault types and RUL within a single framework, the proposed method enhances maintenance planning, enables earlier and more reliable interventions, and provides a scalable solution for intelligent monitoring in smart manufacturing environments.
原始来源: Chalmers Research ↗
这项研究在做什么
设备剩余寿命预测与故障诊断通常分别建模。本文使用共享传感器数据编码器的 Transformer 联合完成两项任务，并在 100 台工业设备的数据上评估。
研究要点
- 通过共享自注意力编码器，连接剩余寿命回归与故障分类两个输出头。
- 使用基于不确定性的损失加权来平衡两项学习任务。
- 在 Microsoft Azure 预测性维护数据集上验证联合建模方法。
引用这项成果
Yuchen Liu, Siyuan Chen, Ebru Turanoglu Bekar (2026). A Transformer Approach for Remaining Useful Life Prediction and Fault Diagnosis of Mechanical Equipment. IOP Conference Series: Materials Science and Engineering, 1342(1), 012059. https://doi.org/10.1088/1757-899X/1342/1/012059
@inproceedings{Chen2026TransformerRulFault,
title = {{A Transformer Approach for Remaining Useful Life Prediction and Fault Diagnosis of Mechanical Equipment}},
author = {Liu, Yuchen and Chen, Siyuan and Turanoglu Bekar, Ebru},
year = {2026},
booktitle = {The 12th Swedish Production Symposium (SPS 2026)},
series = {IOP Conference Series: Materials Science and Engineering},
volume = {1342},
number = {1},
pages = {012059},
doi = {10.1088/1757-899X/1342/1/012059},
url = {https://research.chalmers.se/en/publication/553219}
}
英文摘要来自所链接的原始记录；研究解读和要点用于简要说明论文内容。