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A review on machinery diagnostics and prognostics implementing condition-based maintenance

机译:实施基于状态的维护的机械诊断和预测的回顾

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Condition-based maintenance (CBM) is a maintenance program that recommends maintenance decisions based on the information collected through condition monitoring. It consists of three main steps: data acquisition, data processing and maintenance decision-making. Diagnostics and prognostics are two important aspects of a CBM program. Research in the CBM area grows rapidly. Hundreds of papers in this area, including theory and practical applications, appear every year in academic journals, conference proceedings and technical reports. This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making. Realising the increasing trend of using multiple sensors in condition monitoring, the authors also discuss different techniques for multiple sensor data fusion. The paper concludes with a brief discussion on current practices and possible future trends of CBM.
机译:基于状态的维护(CBM)是一项维护程序,可根据通过状态监视收集的信息来建议维护决策。它包括三个主要步骤:数据获取,数据处理和维护决策。诊断和预测是CBM程序的两个重要方面。煤层气领域的研究发展迅速。每年在该领域的数百篇论文,包括理论和实际应用,都会出现在学术期刊,会议论文集和技术报告中。本文试图总结和回顾在实施CBM的机械系统的诊断和预后方面的最新研究和发展,重点是用于数据处理和维护决策的模型,算法和技术。意识到在状态监测中使用多个传感器的趋势日益增加,作者还讨论了用于多个传感器数据融合的不同技术。本文最后对煤层气的当前做法和未来可能的趋势进行了简短讨论。

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