基于软计算计算的静态负载估计,用于头部起重机
Tom Kusznir1, Jaroslaw Smoczek1
1Department of Manufacturing Systems, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
这项研究估计了用轴承应变和车位置来估计起重机的有效载荷重量,避免了传统的负载单元. 像遗传编程这样的软计算方法为工业自动化提供了准确,高效的替代方案.
科学领域:
- 工程 工程师 工程师 工程师
- 人工智能的人工智能
- 工业自动化 工业自动化
背景情况:
- 有效载荷重量检测对于起重机状态监测和自动化至关重要.
- 传统的载荷电池可能是昂贵的或不可能安装在吊装设备上.
- 使用现有传感器的间接方法为有效载荷估计提供了可行的替代方案.
研究的目的:
- 通过使用起重机轴承应变和车位置间接估计静态有效载荷重量.
- 应用软计算技术来推导非线性输入-输出关系.
- 为了比较不同数据驱动识别方法的性能.
主要方法:
- 利用语法指导的基因编程与稀疏的回归.
- 使用多基因遗传编程.
- 使用最小平方算法应用了减法模糊集群.
- 使用实验室空头起重机的实验数据.
主要成果:
- 多基因遗传编程和语法引导的遗传编程与稀疏的回归显示了类似的,高精度.
- 这两种遗传编程变体的表现都超过了减法模糊集群.
- 新的语法引导方法产生了更节的模型,执行时间更短.
结论:
- 软计算技术,特别是基因编程变体,可以间接有效估计起重机的有效载荷重量.
- 这些数据驱动的方法为传统的负载电池提供了准确和高效的替代方案.
- 开发的模型为起重机自动化和状态监控提供了实际的解决方案.
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