研究一种基于改进的SSD的工业液体水平检测方法
1College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, 300300, China.
Scientific reports
|November 23, 2025
概括
本研究介绍了一种轻量级的SSD算法,用于在边缘设备上高效的工业液体水平检测. 改进的模型提高了准确性,降低了计算负载,使实时监控和早期异常警告成为可能.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 工业自动化 工业自动化
背景情况:
- 工业液位检测需要平衡计算效率和准确性.
- 现有的模型经常在边缘设备上的实时处理中扎.
- 由于缺乏足够的液体水平监测,生产事故可能会出现.
研究的目的:
- 为边缘设备开发一个轻量级的单射击探测器 (SSD) 算法.
- 在工业环境中实现实时液体水平监测和异常早期预警.
- 通过改进检测来减轻生产事故的风险.
主要方法:
- 开发了一个基于MobileNetV2的轻量级特征提取网络.
- 建议采用多尺度扩展倒置残余块 (MS-DIRB),以减少信息丢失.
- 一个三重注意力机制被整合用于增强特征学习.
主要成果:
- 拟议的算法实现了96.65%的mAP,比基线SSD有3.57%的改进.
- 模型参数减少了81.58%,提高了计算效率.
- 该算法证明了其适用于工业边缘设备的实时检测.
结论:
- 轻量级的SSD算法有效地平衡了工业液位检测的效率和准确性.
- 集成MS-DIRB和三重注意力显著提高模型性能.
- 拟议的模型非常适合实时工业边缘计算应用.
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