Remote condition monitoring using open-system wireless technologies
Remote condition monitoring using open-system wireless technologies
复制标题
DOI：
--
复制
发表时间：
2006
影响因子：
0.6
通讯作者：
J. Rybak;Oceana Sensor
中科院分区：
文献类型：
--
作者：
J. Rybak;Oceana Sensor
状态监测包括使用传感器和数据采集设备，通过确定其组件的健康状况来评估给定过程的质量。机械状态监测，它提供了实施基于状态的维护（而不是基于时间的维护或运行到故障）的能力，评估关键机械部件的健康状况，以减少灾难性的过程停机时间并延长机械的使用寿命。强大、开放系统、扩频无线电技术的出现，通过网络和计算机接口远程、经济地持续监测关键机械和过程的状况，从而减少了计划外维护的能力。本文探讨了通过远程数据访问进行连续状态监测的价值，以及在不损害其完整性的情况下，以低成本高效地无线传输数据的方法。它提供了有关可用无线系统技术的信息，解决了各种应用的适用性，并简要描述了目前商用的产品解决方案。旋转机械几乎是每一个制造过程的重要组成部分。电机、齿轮箱、泵、压缩机等都依赖于高效运行，以保持最大产量的稳定生产。这种对关键操作中使用的机械的依赖促使了机械健康监测的发展。每一件机器的寿命都受到其运行速度、所受载荷、部件、装配和安装的质量、环境和维护水平的限制。虽然所有这些因素都非常重要，但对后者的关注将决定机器的效率。它结合了智能维护实践，可以预测关键机械部件（如轴承）即将发生的故障，从而防止昂贵的停机时间，由于库存和昂贵的资本支出而导致的过多开销。
Condition monitoring involves the use of sensors and data acquisition equipment to assess the quality of a given process by determining the health of its components. Machinery condition monitoring, which affords one the ability to implement condition-based maintenance (as opposed to time-based maintenance or run to failure) assesses the health of critical machinery components to reduce catastrophic process downtime and extend the useful life of machinery. The advent of robust, open-system, spread-spectrum radio technology has brought about the ability to reduce unplanned maintenance by continuously monitoring the condition of critical machinery and processes remotely and affordably via network and computer interfaces. This article looks at the value of continuous condition monitoring through remote data access and the means in which that data can be cost effectively transmitted wirelessly without compromising its integrity. It provides information on available wireless system technologies, addresses the suitability of various applications, and briefly describes product solutions commercially available today. Rotating machinery is a vital part of virtually every manufacturing process. Motors, gearboxes, pumps, compressors, etc. are relied upon to operate efficiently to maintain a steady stream of production at maximum throughput. This dependency on machinery used in critical operations has prompted the evolution of machinery health monitoring. The lifespan of every piece of machinery is limited by the speed at which it is operating, the load to which it is subjected, the quality of its components, assembly and installation, its environment and the level of maintenance. While all of these factors are extremely important, it’s the attention that’s placed on the latter that will dictate how efficiently the machinery performs. It’s the incorporation of intelligent maintenance practices, which predict impending failure of critical machinery components like bearings that prevent costly downtime, excessive overhead due to inventory and costly capital expenditures.