Artificial Neural Network-Based Fault Detection System with Residual Analysis Approach on Centrifugal Pump: A Case Study

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-04-07 DOI:10.15282/ijame.20.1.2023.10.0795

K. Indriawati, Gabriel Fransisco Yugoputra, Noviarizqoh Nurul Habibah, Risma Yudhanto

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Abstract

Centrifugal pump is an instrument that is widely used in industry and has become the main driving component. A detection system is often needed to prevent damage to these pumps because they can interfere with the overall system performance. Therefore, this study discussed the development of a fault detection system for two centrifugal pump units, namely the Medium Pressure Oil Pump (MPOP) and the Water Injection Pump (WIP). In detecting the operating conditions of the pump, it was used a residual feature extraction technique in the time domain with a statistical approach. Residual was generated by using three sub-systems of a pumping system. Each sub-system was modeled using an artificial neural network with feedforward-back propagation architecture. Based on the feature values, the classifier was designed to classify pump conditions. Then the proposed fault detection system was applied in a condition monitoring system scheme. The test results (using data from the field) show that the fault detection system has an accuracy of 91.67% for MPOP and 94.8% for WIP cases. Meanwhile, the fault detection system has an accuracy above 99% during online monitoring simulations.

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基于残余分析方法的人工神经网络离心泵故障检测系统研究

离心泵是工业上应用广泛的一种仪表，已成为主要的驱动部件。通常需要一个检测系统来防止这些泵的损坏，因为它们会干扰整个系统的性能。因此，本研究讨论了针对中压油泵(MPOP)和注水泵(WIP)两个离心泵单元的故障检测系统的开发。在检测泵的运行状态时，采用了时域残差特征提取技术和统计方法。余量是由一个泵送系统的三个子系统产生的。各子系统采用前馈-反馈传播结构的人工神经网络建模。根据特征值设计分类器对泵工况进行分类。然后将所提出的故障检测系统应用于状态监测系统方案中。现场测试结果表明，该系统对MPOP和WIP的检测准确率分别为91.67%和94.8%。同时，在在线监测仿真中，系统的故障检测准确率达到99%以上。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.