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Microsensors, arrays and automatic diagnosis of sensor faults

机译:微型传感器,阵列和传感器故障的自动诊断

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摘要

As man-made dynamical systems become increasingly complex, there is an ever-present need to ensure their safe and reliable operatibn. These requirements extend beyond the normally accepted safety-critical systems (e.g. nuclear reactors, chemical plants, and aircraft) to new systems such as autonomous vehicles and rapid transport systems. Early detection of faults and/or malfunctions in industrial processes and systems can help reduce downtimes and the incidence of catastrophic events. Sensors are essential components of any process or system which makes use of automatic control. It follows that an important aspect of any process/system fault diagnosis strategy is to attempt to determine their state of functionality. The paper opens a discussion on the appropriateness of local sensor health monitoring, fault diagnosis and measurement confidence indices. It looks at the techniques currently used for process fault detection, both centralised and hierarchical, and explores further the possibilities of transposing some of the design concepts from macrosystem level to microsystems, in respect to fault diagnosis. The use of Artificial Intelligence techniques is suggested for implementing on-chip sensor diagnosis. Micromachined accelerometers are considered as a case study.
机译:随着人造动力系统变得越来越复杂,一直存在确保其安全可靠运行的需求。这些要求已从通常公认的安全关键系统(例如核反应堆,化工厂和飞机)扩展到新系统,例如自动驾驶汽车和快速运输系统。尽早发现工业过程和系统中的故障和/或故障可以帮助减少停机时间和灾难性事件的发生。传感器是利用自动控制的任何过程或系统的重要组成部分。因此,任何过程/系统故障诊断策略的一个重要方面是试图确定其功能状态。本文就本地传感器健康状况监控,故障诊断和测量置信度指标的适用性展开讨论。它着眼于当前用于过程故障检测的技术(集中式和分层式),并进一步探讨了将有关故障诊断的一些设计概念从宏观系统级转换为微型系统的可能性。建议使用人工智能技术来实现片上传感器诊断。微机械加速度计被认为是一个案例研究。

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