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AI-BASED DIAGNOSTICS FOR FAULT DETECTION AND ISOLATION IN PROCESS EQUIPMENT SERVICE

机译:基于AI的过程设备服务中的故障检测和隔离诊断

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摘要

Recent industry requires efficient fault discovering and isolation solutions in process equipment service. This problem is a real-world problem of typically ill-defined systems, hard to model, with large-scale solution spaces. Design of precise models is impractical, too expensive, or often non-existent. Support service of equipment requires generating models that can analyze the equipment data, interpreting the past behavior and predicting the future one. These problems pose a challenge to traditional modeling techniques and represent a great opportunity for the application of AI-based methodologies, which enable us to deal with imprecise, uncertain data and incomplete domain knowledge typically encountered in real-world applications. In this paper the state of the art, theoretical background of conventional and Al-based techniques in support of service tasks and illustration of some applications to process equipment service on bio-ethanol production process are shortly described.
机译:最近的行业要求在过程设备服务中提供有效的故障发现和隔离解决方案。这个问题是一个典型的,定义不明确的系统的现实世界问题,很难使用大型解决方案空间进行建模。精确模型的设计不切实际,过于昂贵或经常不存在。设备的支持服务需要生成可以分析设备数据,解释过去的行为并预测未来的模型。这些问题对传统的建模技术提出了挑战,并为基于AI的方法学的应用提供了巨大的机会,这使我们能够处理通常在实际应用中遇到的不精确,不确定的数据和不完整的领域知识。在本文中,简要介绍了支持服务任务的常规技术和基于Al的技术的理论背景,并简要介绍了生物乙醇生产过程中处理设备服务的一些应用。

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