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Self-Detection and Self-Diagnosis Methods for Sensors in Intelligent Integrated Sensing System

机译：智能集成传感系统中传感器的自我检测和自诊断方法

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摘要

Intelligent integrated sensing systems possess capabilities such as perceiving external information, data processing. It has a wide range of applications in Internet of Things (IOT), smart manufacturing, and other fields. However, if the information is acquired incorrectly, it will definitely affect the correctness of data processing. Though there have been many researches about sensor data processing, only a few focused on how to self-detect and self-diagnosis the working status of the sensors themselves. Based on the above, this paper proposes to evaluate the accuracy and reliability of sensor output by predicting the sensor's real-time output with multi-sensor fusion. The proposed system can perform self-diagnosis to find out the cause or type of the error when failure occurs. Furthermore, this system can also perform real-time fault-tolerant conveniently. Experimental results show that this method has high recognition accuracy with small amount of calculation complexity. The intelligent integrated sensing system can be more reliable with the proposed self-diagnosis technologies for the smart sensors.
机译：智能集成传感系统具有诸如感知外部信息，数据处理等功能。它在物联网（物联网），智能制造和其他领域拥有广泛的应用。但是，如果获取错误的信息，则肯定会影响数据处理的正确性。虽然传感器数据处理已经有很多研究，但只有一些专注于如何自我检测和自我诊断传感器本身的工作状态。基于上文，本文提出通过通过多传感器融合预测传感器的实时输出来评估传感器输出的准确性和可靠性。所提出的系统可以进行自我诊断，以找出发生故障时错误的原因或类型。此外，该系统还可以方便地执行实时容错。实验结果表明，该方法具有高识别准确性，计算复杂量少。智能集成传感系统可以更可靠，智能传感器的建议自诊断技术更可靠。

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