In order to monitor the stability of industrial systems, engineers installed diversified sensors in systems, and used communication devices to transfer the sensed data to the cloud platform for real-time monitoring and event detection. Furthermore, as industry demand for power grows, the scale and quantity of power systems gradually increase, and the original network data transmission architecture cannot bear such large-scale communication, especially the communication bandwidth tolerance isn’t allowed for trusted industrial Internet of things. Therefore, this trusted transmission problem will be one of challenges of the industrial Internet of things. In the application of device load recognition, how to create power fingerprinting recognition sample data, reduce the cloud platform computation complexity and the transmission quantity of sensed data without losing detection accuracy are the subjects of this study. Therefore, this study proposes a resilient section selection mechanism of power fingerprinting applied to device load recognition, in order to determine the transmission time and select the power fingerprinting section to be resiliently transferred, and replace the cycle-fixed full power fingerprinting data transfer for trusted industrial Internet of things. According to the experimental results, in the case of multi-load, the power fingerprinting of the first 25% section have the maximum recognition of 87.5%.

中文翻译：

---

可信工业物联网设备负载识别的弹性功率指纹选择机制

为了监视工业系统的稳定性，工程师在系统中安装了多种传感器，并使用通信设备将感测到的数据传输到云平台，以进行实时监视和事件检测。此外，随着工业对电力需求的增长，电力系统的规模和数量逐渐增加，原始的网络数据传输体系结构无法承受如此大规模的通信，尤其是对于可信的工业物联网而言，通信带宽的容忍度是不允许的。因此，这种可信的传输问题将成为工业物联网的挑战之一。在设备负载识别的应用中，如何创建电源指纹识别样本数据，降低云平台的计算复杂度和感测数据的传输量而又不降低检测精度是本研究的主题。因此，本研究提出了一种用于设备负载识别的功率指纹的弹性段选择机制，以便确定传输时间并选择要弹性传输的功率指纹段，并取代周期固定的全功率指纹数据传输，以实现可信的传输。工业物联网。根据实验结果，在多负载情况下，前25％部分的功率指纹最大识别率为87.5％。这项研究提出了一种用于设备负载识别的功率指纹的弹性段选择机制，以便确定传输时间并选择要弹性传输的功率指纹段，并取代周期固定的全功率指纹数据传输，以实现可信的工业互联网。东西的。根据实验结果，在多负载情况下，前25％部分的功率指纹最大识别率为87.5％。这项研究提出了一种用于设备负载识别的功率指纹的弹性段选择机制，以便确定传输时间并选择要弹性传输的功率指纹段，并取代周期固定的全功率指纹数据传输，以实现可信的工业互联网。东西的。根据实验结果，在多负载情况下，前25％部分的功率指纹最大识别率为87.5％。