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Diagnostics for piezoelectric transducers under cyclic loads deployed for structural health monitoring applications

机译:用于结构健康监测应用的周期性载荷下压电换能器的诊断

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Accurate sensor self-diagnostics are a key component of successful structural health monitoring (SHM) systems. Transducer failure can be a significant source of failure in SHM systems, and neglecting to incorporate an adequate sensor diagnostics capability can lead to false positives in damage detection. Any permanently installed SHM system will thus require the ability to accurately monitor the health of the sensors themselves, so that when deviations in baseline measurements are observed, one can clearly distinguish between structural changes and sensor malfunction. This paper presents an overview of sensor diagnostics for active-sensing SHM systems employing piezoelectric transducers, and it reviews the sensor diagnostics results from an experimental case study in which a 9 m wind turbine rotor blade was dynamically loaded in a fatigue test until reaching catastrophic failure. The fatigue test for this rotor blade was unexpectedly long, requiring more than 8 million fatigue cycles before failure. Based on previous experiments, it was expected that the rotor blade would reach failure near 2 million fatigue cycles. Several sensors failed in the course of this much longer than expected test, although 48 out of 49 installed piezoelectric transducers survived beyond the anticipated 2 million fatigue cycles. Of the transducers that did fail in the course of the test, the sensor diagnostics methods presented here were effective in identifying them for replacement and/or data cleansing. Finally, while most sensor diagnostics studies have been performed in a controlled, static environment, some data in this study were collected as the rotor blade underwent cyclic loading, resulting in nonstationary structural impedance. This loading condition motivated the implementation of a new, additional data normalization step for sensor diagnostics with piezoelectric transducers in operational environments.
机译:准确的传感器自我诊断是成功的结构健康监测(SHM)系统的关键组成部分。换能器故障可能是SHM系统中的重要故障源,而忽略合并足够的传感器诊断功能可能会导致损坏检测中出现误报。因此,任何永久安装的SHM系统都需要能够准确监视传感器本身的健康状况,以便在观察到基线测量值出现偏差时,可以清楚地区分结构变化和传感器故障。本文概述了采用压电换能器的主动感应SHM系统的传感器诊断,并回顾了一个实验案例研究的传感器诊断结果,在该案例中,一个9 m的风力涡轮机转子叶片在疲劳测试中动态加载,直到发生灾难性故障。该转子叶片的疲劳测试出乎意料地长,在失效之前需要进行超过800万次疲劳循环。根据先前的实验,预计转子叶片将在200万疲劳周期附近达到故障。尽管在安装的49个压电换能器中有48个的寿命超过了预期的200万疲劳周期,但仍有数个传感器在比预期的更长的测试过程中失败。在测试过程中确实发生故障的换能器中,此处介绍的传感器诊断方法可以有效地识别出它们以进行更换和/或清洗数据。最后,虽然大多数传感器诊断研究都是在受控的静态环境中进行的,但由于转子叶片承受周期性载荷,因此收集了该研究中的一些数据,从而导致结构不稳定。这种加载条件促使实施新的,附加的数据标准化步骤,以在操作环境中使用压电换能器进行传感器诊断。

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