低成本振动传感器在工业物联网应用中的性能评估

A. Iqbal, N. S. Mian, A. Longstaff, S. Fletcher
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引用次数: 0

摘要

最近在工业物联网(IIoT)革命的推动下,低成本加速度计的发展为其在精密制造中的应用提供了机会。在任何精密加工过程中,传感器数据通常是最重要的考虑因素。在工业制造中,传统上采用高成本振动传感器进行振动测量,但影响低成本振动传感器精度的测量不确定度尚未得到探讨,需要进行性能评估。本研究的重点是低成本三轴微机电系统(MEMS)加速度计的测量特性,以确定测量数据中引起不确定性的参数。根据ISO 16063系列和IEEE-STD-1293-2018标准,在校准试验台上使用一系列频率进行静态和动态校准,并建立可追溯性。此外,通过将传感器安装在机床上进行比较试验,以评估记录数据的数字传输的可靠性。这两项测试都进一步确定了传感器产生的基线误差与它们对机床动态性能剖面中获得的数据的影响之间的关系。这项研究的结果将预见这种低成本传感器在计量应用中的可行性,从而实现工业4.0。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of Low-Cost Vibration Sensors in Industrial IoT Applications
The recent development of low-cost accelerometers, driven by the Industrial Internet of Things (IIoT) revolution, provides an opportunity for their application in precision manufacturing. Sensor data is often of the highest consideration in any precision machining process. While high-cost vibration sensors have traditionally been employed for vibration measurements in industrial manufacturing, the measurement uncertainty affecting the accuracy of low-cost vibration sensors has not been explored and requires performance evaluation. This research focuses on the characterization of measurements from low-cost tri-axial micro electro-mechanical systems (MEMS) accelerometers in terms of identifying the parameters that induce uncertainties in measured data. Static and dynamic calibration was conducted on a calibration test bench using a range of frequencies while establishing traceability according to the ISO 16063 series and the IEEE-STD-1293-2018 standards. Moreover, comparison tests were performed by installing the sensors on machine tools for reliability evaluation in terms of digital transmission of recorded data. Both tests further established the relationship between the baseline errors originating from the sensors and their influence on the data obtained during the dynamic performance profile of the machine tools. The outcomes of this research will foresee the viability offered by such low-cost sensors in metrological applications enabling Industry 4.0.
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