面向工业故障预测与健康管理的传感器网络可靠性研究
Dependability of Sensor Networks for Industrial Prognostics and Health Management
摘要：
维修是工业中的一项重要活动。它可以用来恢复机器/组件或防止其损坏。随着时间的推移，不同的策略不断发展，将维护带到了当前的状态：基于状态的维护和预测性维护。这种演变是由于工业对可靠性的需求不断增加。状态维修和预测维修的核心是工程资产的动态和健康管理，是预测工程资产剩余使用寿命的工具。如今，工厂需要在提供安全性和可靠性的同时避免停机。然而，计划维护活动需要关于系统/组件健康状态的准确信息。这些信息通常通过独立的传感器节点收集。在这项研究中，我们考虑的情况下，节点互连，形成一个无线传感器网络。据我们所知，还没有研究工作考虑过这样的一个案例。关于数据准确性的重要性，一个好的统计学需要可靠的信息来源。这就是为什么，在本文中，我们将首先讨论无线传感器网络的可靠性，然后提出一个国家的最先进的预测和健康管理活动。
英文摘要：
Maintenance is an important activity in industry. It is performed either to revive a machine/component or to prevent it from breaking down. Different strategies have evolved through time, bringing maintenance to its current state: condition-based and predictive maintenances. This evolution was due to the increasing demand of reliability in industry. The key process of condition-based and predictive maintenances is prognostics and health management, and it is a tool to predict the remaining useful life of engineering assets. Nowadays, plants are required to avoid shutdowns while offering safety and reliability. Nevertheless, planning a maintenance activity requires accurate information about the system/component health state. Such information is usually gathered by means of independent sensor nodes. In this study, we consider the case where the nodes are interconnected and form a wireless sensor network. As far as we know, no research work has considered such a case of study for prognostics. Regarding the importance of data accuracy, a good prognostics requires reliable sources of information. This is why, in this paper, we will first discuss the dependability of wireless sensor networks, and then present a state of the art in prognostic and health management activities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
