涡轮压缩机的先进诊断技术:预防性维护的光谱分析方法

Tarek Kebabsa, Mohamed Khemissi Babouri, A. Djebala, N. Ouelaa
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引用次数: 0

摘要

本文介绍了一种创新的频谱分析控制方法,旨在监测和诊断机器故障,防止潜在故障的发生。研究是在一家大型工业企业的一台关键机器上进行的。所提出的方法涉及使用一种名为 "总体水平"(OL)的新指标,该指标可在任何操作之前评估机器的状况。这项研究展示了从基于时间的维护过渡到预测性策略的实用方法,为机器状况提供了可操作的洞察力。这在优化维护实践和提高资产生产率方面为行业带来了实实在在的好处。此外,还采用了各种方法,包括振动分析、性能监测和数据分析,以确定问题的原因并提出解决方案,从而提高涡轮压缩机的可靠性。分析结果可清晰显示机器的振动状态,以便进行诊断。这一值得注意的干预措施强调了将 OL 指标的测量值和计算值纳入三个特定频率段的潜力。为实现这一目标,采用平均值作为指标,有助于提高关键工业机械的可靠性和使用寿命。在这种情况下,研究结果的新颖之处在于涡轮压缩机的先进诊断能力,从而提高了 BP 103 J 涡轮机基于状态的预防性维护的效率。最终目标是通过电子维护系统的支持,延长设备的使用寿命,提高旋转机械的效率,降低维护成本,并提高可用性和可靠性等参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced diagnostic techniques for turbo compressors: A spectral analysis approach for preventive maintenance
This paper introduces an innovative spectral analysis control approach aimed at monitoring and diagnosing machine malfunctions to prevent potential failures. The research was conducted on a critical machine in a major industrial enterprise. The proposed method involves the use of a new indicator, called Overall Level (OL), that evaluates the machine’s condition before any operation. This study showcases practical methodologies for transitioning from time-based maintenance to predictive strategies, furnishing actionable insights into machine condition. This yields tangible advantages for the industry in terms of optimizing maintenance practices and enhancing asset productivity. Additionally, various methods, including vibration analysis, performance monitoring, and data analysis, are employed to identify the causes of issues and recommend solutions to enhance the reliability of the turbo compressor. The results provide a clear representation of the machine’s vibration state for diagnostic purposes. This noteworthy intervention underscores the potential of incorporating the measured and calculated values of the OL indicator across three specifically chosen frequency bands. To achieve this objective, the average value is employed as an indicator, contributing to the enhancement of reliability and longevity of critical industrial machinery. In this context, the novelty of the findings resides in the advanced diagnostic capabilities of the turbocompressor, thereby augmenting the efficacy of condition-based preventive maintenance for the BP 103 J turbine. The ultimate goal is to extend the equipment’s lifespan, improve the efficiency of the rotating machinery fleet, reduce maintenance costs, and enhance parameters such as availability and reliability through the support of an electronic maintenance system.
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