Incipient faults in interface converters can potentially lead to catastrophic failures. Detection of incipient faults contributes to proactive fault management and predictive maintenance, which effectively improves system reliability. In this paper, a detection method in correlation space is proposed to address this problem, which is based on the inherent feature of correlation changes when a fault occurs. First, a convolution process is used to weaken noise and highlight the correlation feature. Second, the current signals are transmitted to correlation space by using the Pearson correlation coefficient. Third, an accumulation and a reference compensation method are designed for enhancing the features and equalizing influence of reference adjustment. Finally, a fault detection rule is designed based on correlation features and fault excitation. Experiments on a hardware‐in‐loop(HIL) semi‐physical platform indicate that the proposed method outperforms three commonly used correlation analysis algorithms. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

中文翻译：

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通过信号相关分析增强接口转换器传感器的早期故障检测

接口转换器中的初期故障可能会导致灾难性故障。早期故障的检测有助于主动故障管理和预测性维护，有效提高系统可靠性。针对这一问题，本文根据故障发生时相关性变化的固有特征，提出了一种相关性空间检测方法。首先，使用卷积过程来削弱噪声并突出相关特征。其次，利用皮尔逊相关系数将当前信号传输到相关空间。第三，设计了累加和参考补偿方法，以增强参考调整的特征并均衡影响。最后，基于相关特征和故障激励设计故障检测规则。硬件在环（HIL）半物理平台上的实验表明，所提出的方法优于三种常用的相关分析算法。© 2024 日本电气工程师协会和 Wiley periodicals LLC。