流量时间序列分解以确定饮用水分配系统中的非收入水组成部分:以数据为导向的方法
Maria Almeida Silva1, Conceição Amado2, Dália Loureiro3
1Lusófona University, Portugal; Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI), Portugal; CEMAT, Instituto Superior Técnico, University of Lisbon, Portugal.
Water research
|March 18, 2025
概括
水利公司可以通过分析非收入水模式来减少水损失. 单元光谱分析有效地分解时间序列数据,揭示了更好的水资源管理策略的隐藏组件.
科学领域:
- 环境工程 环境工程
- 水资源管理 水资源管理
- 数据科学数据科学数据科学
背景情况:
- 非收入水 (NRW) 对水利设施构成重大挑战,包括泄漏,爆破和消费错误.
- 现有的方法经常单独处理NRW组件,缺乏全面的方法.
- 智能水表已经改进了计费消费数据,但需要与网络数据集成才能获得NRW的完整图像.
研究的目的:
- 应用时间序列分解技术对非收入水进行全面分析.
- 识别NRW数据中的隐藏模式,以告知减少水损失的战略.
- 为了评估NRW分析的不同分解方法的有效性.
主要方法:
- 使用智能水表数据和网络流量时间序列.
- 应用各种时间序列分解技术来分割NRW数据.
- 比较不同分解方法的性能,包括单一光谱分析.
主要成果:
- 时间序列分解成功地揭示了非收入水中不同的组件.
- 单一频谱分析在分区NRW时间序列方面表现出卓越的可靠性.
- 综合方法提供了NRW随时间推移的动态的全面视图.
结论:
- 时间序列分解,特别是单点光谱分析,是理解NRW的一个强大的工具.
- 水利公司可以通过分析这些分解的组件来制定有针对性的战略来减少水损失.
- 这种方法可以实现更全面,更有效地管理水资源.
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