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Detection and modelling of incipient failures in internal combustion engine driven generators using Electrical Signature Analysis

机译：使用电子特征分析对内燃机驱动发电机的早期故障进行检测和建模

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Condition based maintenance of electric generators have been gaining increasing importance due to the electricity demand and the criticality that this equipment represents to electrical power systems. In this context, this paper proposes a methodology and a system for detectionand modeling of incipient failures in the components of internal combustion engine driven generators based on Electrical Signature Analysis (ESA). The proposed methodology enables the detection of incipient faults both in the prime mover and in the Coupled synchronous generator, only relying on measurements of the generator stator voltages and currents. The proposed ESA failure patterns are based on defined frequencies and the structural features of the machine, so they can be reproduced in a wide range of engine generators sets. The main advantages of the proposed system are its low intrusiveness, feasible installation and cost efficiency. A scale model laboratory has been designed to simulate faults in a small diesel generator and apply the ESA methodology to detect these faults and obtain the failure patterns. Experimental results are presented to prove the effectiveness of the proposed methodology. The main results include the findings that exciter generator unbalance induces electrical unbalance components, exciter diode short circuit induces even harmonics, intake valve failure and piston ring failure induce multiples of rotation frequency components, and mechanical misalignment of the engine generator set induces multiples of half order speed frequency components on ESA. Moreover, the proposed prototype is installed at two large in-service internal combustion engine driven generators and examples of signal analysis are provided. (C) 2017 Elsevier B.V. All rights reserved.
机译：由于电力需求以及该设备对电力系统的重要性，发电机状态维护一直变得越来越重要。在此背景下，本文提出了一种基于电气特征分析（ESA）的内燃机驱动发电机部件早期故障检测和建模的方法和系统。所提出的方法仅依靠对发电机定子电压和电流的测量就能够检测原动机和耦合同步发电机中的早期故障。提议的ESA故障模式基于定义的频率和机器的结构特征，因此可以在各种发动机发电机组中复制。该系统的主要优点是它的低侵入性，可行的安装和成本效益。已经设计了一个比例模型实验室来模拟小型柴油发电机中的故障，并应用ESA方法来检测这些故障并获得故障模式。实验结果表明，该方法是有效的。主要结果包括以下发现：励磁发电机不平衡会引起电气不平衡分量；励磁二极管短路会产生均匀的谐波；进气门故障和活塞环故障会引起旋转频率分量的倍数；发动机发电机组的机械失准会导致半倍数的倍数。加速ESA上的频率分量。此外，将拟议的原型安装在两台大型运行中的内燃发动机驱动的发电机上，并提供信号分析的示例。 （C）2017 Elsevier B.V.保留所有权利。

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