School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.
School of Electrical Engineering, Tianjin University of Technology, Tianjin 300384, China.
Sensors (Basel). 2022 Jul 25;22(15):5559. doi: 10.3390/s22155559.
The board channel is a connection between a data acquisition system and the sensors of a plant. A flawed channel will bring poor-quality data or faulty data that may cause an incorrect strategy. In this paper, a data-driven approach is proposed to detect the status of the enclosed board channel based on an error time series obtained from multiple excitation signals and internal register values. The critical faulty data, contrary to the known healthy data, are constructed by using a null matrix with maximum projection and are labelled as training examples together with healthy data. Finally, the status of the enclosed board channel is validated by a well-trained probabilistic neural network. The experimental results demonstrate the effectiveness of the proposed method.
板通道是数据采集系统与工厂传感器之间的连接。有缺陷的通道会带来质量差或错误的数据，可能导致错误的策略。在本文中，提出了一种基于从多个激励信号和内部寄存器值获得的误差时间序列来检测封闭板通道状态的基于数据的方法。与已知的健康数据相反，使用具有最大投影的零矩阵构造关键错误数据，并将其与健康数据一起标记为训练示例。最后，通过训练良好的概率神经网络验证封闭板通道的状态。实验结果证明了所提出方法的有效性。
