Contrastive Learning-Based Dual Autoencoder for Anomaly Detection in Loader Gearboxes

IF 4.9 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Ruonan Lu;Da Zheng;Chengyuan Zhu;Weiwei Cao;Qinmin Yang
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Abstract

Anomaly detection (AD) of gearboxes is essential for ensuring the operational safety and reliability of the loader. However, identifying anomalies in non-stationary signals remains challenging as anomalies often emerge within the normal fluctuation, especially when normal and abnormal samples exhibit high similarity. This brief proposes a contrastive learning-based dual autoencoder (AE) AD method for loader gearboxes. Specifically, the continuous wavelet transform is employed to capture dynamic characteristics of non-stationary signals. A compound scaling network is then designed into the unified encoder to extract complex features while maintaining a lightweight architecture. Subsequently, a sparse representation channel is integrated into the second AE framework, complementing the basis for contrastive mechanisms and promoting the learning of consistency across normal samples with the reconstruction channel. By minimizing the contrastive loss between two samples from different channels, the model learns the inherent consistency of normal samples. Finally, the contrastive loss of the second AE and the reconstruction error of the first AE serve as indicators for detecting abnormalities. Experimental results on real-world loader gearbox data demonstrate that the proposed method achieves a high fault detection rate, a low false alarm rate, and robust reliability, validating its effectiveness.
基于对比学习的双自编码器在装载机变速箱异常检测中的应用
齿轮箱异常检测是保证装载机安全可靠运行的重要手段。然而,识别非平稳信号中的异常仍然具有挑战性,因为异常通常出现在正常波动中,特别是当正常和异常样本表现出高度相似时。提出了一种基于对比学习的装载机齿轮箱双自编码器(AE) AD方法。具体而言,采用连续小波变换捕捉非平稳信号的动态特性。然后在统一编码器中设计复合缩放网络,在保持轻量级架构的同时提取复杂特征。随后,将稀疏表示通道集成到第二个AE框架中,补充了对比机制的基础,并通过重构通道促进了正常样本间一致性的学习。通过最小化来自不同通道的两个样本之间的对比损失,该模型学习了正态样本的固有一致性。最后,第二声发射的对比损失和第一声发射的重建误差作为检测异常的指标。在装载机变速箱实际数据上的实验结果表明,该方法具有较高的故障检出率、较低的虚警率和较强的可靠性,验证了该方法的有效性。
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来源期刊
IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE Transactions on Circuits and Systems II: Express Briefs 工程技术-工程:电子与电气
CiteScore
7.90
自引率
20.50%
发文量
883
审稿时长
3.0 months
期刊介绍: TCAS II publishes brief papers in the field specified by the theory, analysis, design, and practical implementations of circuits, and the application of circuit techniques to systems and to signal processing. Included is the whole spectrum from basic scientific theory to industrial applications. The field of interest covered includes: Circuits: Analog, Digital and Mixed Signal Circuits and Systems Nonlinear Circuits and Systems, Integrated Sensors, MEMS and Systems on Chip, Nanoscale Circuits and Systems, Optoelectronic Circuits and Systems, Power Electronics and Systems Software for Analog-and-Logic Circuits and Systems Control aspects of Circuits and Systems.
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