通过电力消耗水平检测自动化果园灌系统执行器的异常操作检测
Shahriar Ahmed1, Md Nasim Reza1,2, Md Rejaul Karim1
1Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea.
Sensors (Basel, Switzerland)
|January 25, 2025
概括
这项研究开发了一种信号处理技术,用于使用功耗数据检测自动化灌系统中的执行器故障. 该方法可靠地识别和门故障,提高灌效率和作物产量.
科学领域:
- 农业工程 农业工程
- 自动化和控制系统自动化和控制系统
- 传感器技术 传感器技术
背景情况:
- 自动灌系统依赖于信息和通信技术 (ICT) 组件,如精密灌的执行器.
- 这些系统中的执行器故障导致灌效率低下,对作物健康和生产率产生负面影响.
- 早期发现执行器故障对于保持最佳灌管理和作物产量至关重要.
研究的目的:
- 开发一种信号处理技术,用于检测自动化果园灌系统中的执行器故障.
- 为了利用功耗数据和执行器的运行状态来识别故障.
- 通过改进故障检测,提高自动化灌系统的可靠性和效率.
主要方法:
- 使用了果树的示范果园设置,采用Python编程的微控制器控制和两个电磁.
- 商用电流传感器测量了执行器功率消耗,使用值来区分正常和异常操作.
- 信号处理技术分析了功耗,控制命令和操作状态,以检测执行器故障.
主要成果:
- 拟议的方法准确地识别了和电磁的正常和异常操作.
- 对于第二个电磁,该模型在检测正常 (316/333) 和异常 (58/60) 实例时实现了高精度.
- 该系统的平均精度为1通道执行器的99.9%,2通道电磁的99.7%.
结论:
- 开发的信号处理方法可以有效地检测自动灌系统中的执行器故障.
- 这项技术有可能显著改善灌管理,提高作物生产率.
- 未来的工作包括整合机器学习以加强故障检测,并评估各种农业应用的系统可扩展性.
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