油气设备状态维修研究进展

T. Abbasi, K. Lim, Toufique Ahmed Soomro, I. Ismail, Ahmed Ali
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引用次数: 2

摘要

油气行业需要资本密集型投资,特别是在旋转机械设备的购置和安装方面。旋转机械设备,如感应电机、压缩机和泵,是工业过程中必不可少的部件。最近的原油价格下跌引起了整个油气行业对有效维护管理的关注。基于状态的维护(CBM)是石油工业中最具成本效益的维护技术,可以防止设备停机,提高生产力。本文综述了旋转设备CBM技术的最新进展,分为三类:基于特征提取的方法在时域和频域上预测机械参数;基于模型的方法在数学模型上分析机械行为;基于知识的方法利用数据驱动算法学习系统过去的信号以预测未来。重点介绍了每种类型的优势、局限性和实际意义,以供油气行业建议和选择。
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Condition Based Maintenance of Oil and Gas Equipment: A Review
Oil and gas industry requires capital-intensive investment especially in rotating mechanical equipment acquisition and installation. Rotating mechanical equipment such as induction motor, compressors and pumps, are essential components in industrial processes. The recent crude oil price drop raises the concern of effective maintenance management across oil and gas industry. Condition-based maintenance (CBM) is the most cost-effective maintenance technique to prevent the downtime of equipment and increases the productivity in petroleum industry. In this paper, recent reviews on CBM techniques for rotating equipment are presented under three categories, i.e. (1) Signature extraction-based method predicts machinery parameter in time and frequency domain, (2) Modelbased approach analyses machinery behavior in mathematical model and (3) Knowledge-based approach uses data-driven algorithm to learn system signal in the past for future prediction. The advantages, limitations and practical implication of each category are highlighted for suggestions and selection in the oil and gas industry.
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