基于PLC技术控制的太阳能电池板智能生产线产品故障检测研究  

Research on product fault detection of solar panel intelligent production line based on PLC technology control

作　　者：白玉田 BAI Yutian(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China)

机构地区：[1]西安航空职业技术学院,西安710089

出　　处：《自动化与仪器仪表》2025年第3期71-75,80,共6页Automation & Instrumentation

基　　金：2023年度西安航空职业技术学院科研计划项目《大型无人机专用光伏组件生产关键技术研发》(23XHZK-03)。

摘　　要：针对传统太阳能电池板产品故障检测准确率低和检测效率不高的问题,提出设计一个基于PLC技术控制的太阳能电池板智能生产线产品故障检测系统。首先,采用相机对太阳能电池板智能生产线产品进行拍摄;然后对采集图像进行高斯滤波处理;最后采用改进的YOLOv7-tiny网络对产品图像进行故障检测。实验结果表明,本算法的mAP指标为99.41%,相较于传统的YOLOv5故障检测算法和SSD检测算法的mAP指标分别高出了14.58%和20.06%。相同实验数据集下,本算法的故障检测时长仅为156.6 ms,对比于另外两种算法分别低了176.5 ms和113.2 ms。由此分析可知,本算法可提高太阳能电池板的故障检测精度和速度,检测效率显著提升,满足太阳能电池板智能生产线产品的生产需求,具备实时性和有效性。In view of the problems of low fault detection accuracy and low detection efficiency of traditional solar panel products,a fault detection system of solar panel intelligent production line based on PLC technology control is proposed.First,the camera is used to film the smart production line;then the Gaussian filter;finally,the improved YOLOv7-network network.The experimental results show that the mAP index of this algorithm is 99.41%,which is 14.58% and 20.06% higher than the traditional YOLOv5 fault detection algorithm and SSD detection algorithm,respectively.In the same experimental data set,the fault detection time of this algorithm is only 156.6 ms,which is lower than 176.5 ms and 113.2 ms compared with the other two algorithms.According to this analysis,this algorithm can improve the accuracy and speed of fault detection of solar panels,significantly improve the detection efficiency,meet the production needs of intelligent production line of solar panels,and have real-time and effectiveness.

关 键 词：太阳能电池板 PLC技术 故障检测 YOLOv7-tiny算法 智能生产线 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]