Department of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun City, China.
Department of Electrical Information Engineering, Jilin University of Architecture and Technology, Changchun City, China.
PLoS One. 2021 Jul 6;16(7):e0253246. doi: 10.1371/journal.pone.0253246. eCollection 2021.
Under the background of modern industrial processing and production, the sintering furnace's temperature control system is researched to achieve intelligent smelting and reduce energy consumption. First, the specific application and implementation of edge computing in industrial processing and production are analyzed. The industrial processing and production intelligent equipment based on edge computing includes the equipment layer, the edge layer, and the cloud platform layer. This architecture improves the operating efficiency of the intelligent control system. Then, the sintering furnace in the metallurgical industry is taken as an example. The sintering furnace connects powder material particles at high temperatures; thus, the core temperature control system is investigated. Under the actual sintering furnace engineering design, the Distributed Control System (DCS) is used as the basis of sintering furnace temperature control, and the Programmable Logic Controller (PLC) is adopted to reduce the electrical wiring and switch contacts. The hardware circuit of DCS is designed; on this basis, an embedded operating system with excellent performance is transplanted according to functional requirements. The final DCS-based temperature control system is applied to actual monitoring. The real-time temperature of the upper, middle, and lower currents of 1# sintering furnace at a particular point is measured to be 56.95°C, 56.58°C, and 57.2°C, respectively. The real-time temperature of the upper, middle, and lower currents of 2# sintering furnaces at a particular point is measured to be 144.7°C, 143.8°C, and 144.0°C, respectively. Overall, the temperature control deviation of the three currents of the two sintering furnaces stays in the controllable range. An expert system based on fuzzy logic in the fault diagnosis system can comprehensively predict the situation of the sintering furnaces. The prediction results of the sintering furnace's faults are closer to the actual situation compared with the fault diagnosis method based on the Backpropagation (BP) neural network. The designed system makes up for the shortcomings of the sintering furnace's traditional temperature control systems and can control the temperature of the sintering furnace intelligently and scientifically. Besides, it can diagnose equipment faults timely and efficiently, thereby improving the sintering efficiency.
在现代工业加工和生产的背景下，研究了烧结炉的温度控制系统，以实现智能熔炼和降低能耗。首先，分析了边缘计算在工业加工和生产中的具体应用和实现。基于边缘计算的工业加工智能设备包括设备层、边缘层和云平台层。这种架构提高了智能控制系统的运行效率。然后，以冶金行业的烧结炉为例，烧结炉将粉末材料颗粒在高温下连接起来；因此，研究了核心温度控制系统。在实际的烧结炉工程设计中，采用分布式控制系统（DCS）作为烧结炉温度控制的基础，采用可编程逻辑控制器（PLC）减少电气布线和开关触点。设计了 DCS 的硬件电路；在此基础上，根据功能要求移植了具有优异性能的嵌入式操作系统。最终将基于 DCS 的温度控制系统应用于实际监测。测量到 1#烧结炉特定点的上、中、下电流的实时温度分别为 56.95°C、56.58°C 和 57.2°C。测量到 2#烧结炉特定点的上、中、下电流的实时温度分别为 144.7°C、143.8°C 和 144.0°C。总体而言，两台烧结炉的三个电流的温度控制偏差均在可控范围内。故障诊断系统中基于模糊逻辑的专家系统可以全面预测烧结炉的情况。与基于反向传播（BP）神经网络的故障诊断方法相比，烧结炉故障的预测结果更接近实际情况。设计的系统弥补了传统烧结炉温度控制系统的不足，可以智能、科学地控制烧结炉的温度。此外，它可以及时有效地诊断设备故障，从而提高烧结效率。
