Condition monitoring of critical mechanical elements through Graphical Representation of State Configurations and Chromogram of Bands of Frequency
Condition monitoring of critical mechanical elements through Graphical Representation of State Configurations and Chromogram of Bands of Frequency
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DOI：
10.1016/j.measurement.2018.11.029
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发表时间：
2019-03-01
期刊：
影响因子：
5.6
通讯作者：
Carlos Garcia-Prada, Juan
中科院分区：
文献类型：
--
作者：
Bustos, Alejandro;Rubio, Higinio;Carlos Garcia-Prada, Juan
故障检测是避免机械系统发生灾难性故障以及为公司节省资金的关键方面。目前，许多非破坏性测试，信号处理分析和人工智能技术被用于处理越来越大量的维护数据，无论是单独还是组合在所有行业领域。本文提出了一种基于振动分析的机械状态监测新方法。该方法是支持两种新的信号处理技术：图形表示的状态图（GRSC）和频带的频率（CBF）的色谱图。这两种新技术将机器劣化理论的基本概念应用于频谱。为了证明所提出的工作的成功，该方法进行了测试，对两个真实的例子：从凯斯西储大学（CWRU）轴承数据中心的振动信号，和振动信号从高速列车在正常运行。结果表明，这些新技术可以在不使用人工智能的情况下处理大量数据，充分识别被测系统的运行状况，并通过简单的图形和颜色给出有关该操作系统的精确信息。(C)2018爱思唯尔有限公司版权所有。
Fault detection is a crucial aspect to avoid catastrophic failures on mechanical systems, as well as to save money for companies. Currently, a number of non-destructing tests, signal processing analysis and artificial intelligence techniques are used for processing larger and larger amounts of maintenance data in all industry fields, either independently or combined. This manuscript presents a novel methodology for the condition monitoring of machinery, based on vibration analysis. The methodology is supported on two novel signal processing techniques: Graphical Representation of State Configurations (GRSC) and Chromogram of Bands of Frequency (CBF). These two new techniques apply basic concepts of the machine deterioration theory to the frequency spectrum. In order to prove the successful of the work presented, the methodology is tested against two real examples: vibration signals from the Case Western Reserve University (CWRU) Bearing Data Centre, and vibration signals from a high-speed train in normal operation. The results show that these new techniques can process large amounts of data without using artificial intelligence, identify adequately the operating condition of the tested systems and give precise information about that operating system by means of simple graphs and colours. (C) 2018 Elsevier Ltd. All rights reserved.