Nonstationary incipient fault detection based on hybrid supervised trend-period variational autoencoder and its application in thermal power generation

IF 3.3 2区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Zhangming Lan , Yun Wang , Yuchen He , Lijuan Qian
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引用次数: 0

Abstract

Incipient fault detection has been considered as one of the most efficient approaches to reduce the risks of systematic failures. However, incipient fault signals are often obscured by nonstationary characteristics, such as trend features and periodic features. In this paper, a hybrid-supervised trend-period variational autoencoder (HSTPVAE) is proposed to achieve fault detection for incipient faults in nonstationary processes. The features of trend, period and residual are extracted from a novel trend-period variational autoencoder (TPVAE). Then, these features are optimized by a hybrid supervised strategy, which includes fault trend semi-supervised module and trend-period self-supervised module. The former enhances the distinctiveness between normal and fault trend features, while the latter prevents the overfitting issues. Finally, the effectiveness of the HSTPVAE is demonstrated on a numerical simulation process and real boiler combustion process of thermal power generation. The comparison with state-of-the-art (SOTA) methods proves that the proposed HSTPVAE method can fully utilize the trend and period features of nonstationary process and outperform other comparison methods in incipient fault detection.

Abstract Image

基于混合监督趋势周期变分自编码器的非平稳早期故障检测及其在火力发电中的应用
早期故障检测被认为是降低系统故障风险的最有效方法之一。然而,早期的故障信号往往被非平稳特征所掩盖,如趋势特征和周期特征。本文提出了一种混合监督趋势周期变分自编码器(HSTPVAE)来实现对非平稳过程中早期故障的故障检测。从一种新的趋势-周期变分自编码器(TPVAE)中提取趋势、周期和残差特征。然后,采用故障趋势半监督模块和趋势周期自监督模块的混合监督策略对这些特征进行优化。前者增强了正、断层趋势特征的显著性,后者防止了过拟合问题。最后,通过数值模拟过程和实际火电锅炉燃烧过程验证了该方法的有效性。与SOTA方法的比较表明,该方法能充分利用非平稳过程的趋势特征和周期特征,在早期故障检测方面优于其他比较方法。
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来源期刊
Journal of Process Control
Journal of Process Control 工程技术-工程:化工
CiteScore
7.00
自引率
11.90%
发文量
159
审稿时长
74 days
期刊介绍: This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others. Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques. Topics covered include: • Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.
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