基于BILSTM的河堤泄漏的智能报警系统
Zhiyu Shao1, Xin Mei2, Meiling Xue2
1School of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou, 225009, Jiangsu, China. zhiyushao@yzu.edu.cn.
Scientific reports
|October 11, 2024
概括
现有的堤泄漏监测系统缺乏先进的警报. 这项研究引入了一个智能报警系统,使用双向长期短期存储器 (BILSTM) 网络进行准确的泄漏预测和增强堤防安全.
科学领域:
- 地质技术工程 地质技术工程
- 人工智能的人工智能
- 水资源管理 水资源管理
背景情况:
- 目前的堤防泄漏监测系统在报警功能方面存在局限性,依赖于单个参数监测.
- 这种缺陷导致诸如错误报警,错过检测,设备故障和操作停机等问题,从而损害了整体堤防安全.
- 在堤防漏水监测方面,迫切需要更智能,更可靠的报警系统.
研究的目的:
- 设计和实施智能堤防泄漏报警系统,克服现有的单参数系统的局限性.
- 通过先进的预测能力,提高堤防安全监测的准确性和可靠性.
- 开发一个多层次的报警模块,其中包括汇率和相关报警,以改善早期预警.
主要方法:
- 数据清理和工程安全监测数据的预处理,以减轻异常值和重复值的影响.
- 使用相互信息 (MI) 理论进行相关性分析,以了解和解释堤平衡管水位和外部水体 (例如长江) 之间的关系.
- 应用双向长短记忆 (BILSTM) 网络模型,预测可能异常数据间隔的趋势和预测平衡管水位.
主要成果:
- 开发的系统有效预处理监控数据,减少噪音并提高报警精度.
- 相互信息分析成功地解决了压力计管水位变化的延迟,提高了相关性检测.
- 该BILSTM模型在预测平衡管水位方面表现出高准确度,从而实现及时和智能报警.
结论:
- 拟议的智能报警系统,利用BILSTM网络,大大提高了堤泄漏监测能力.
- 该系统提供准确的预测和可靠的多层次报警,有助于提高堤安全性和降低运营风险.
- 这种方法代表了关键基础设施 (如堤) 的智能监控的重大进步.
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