基于微服务架构与达梦数据库的大坝安全评价系统

Dam Safety Evaluation System Based on a Micro-Service Architecture and the Dameng Database

摘要: 针对传统大坝安全评价中存在的评价规范性与信息化水平不足等问题，本文基于《水库大坝安全评价导则》(SL258-2017)，研发了基于微服务架构与达梦数据库的大坝安全评价系统。系统技术架构包括数据层、服务层、接入层、表现层与四大体系，以多源监测数据为核心、模型协同融合为支撑构建了由监控对象、监控部位、监控项目及监控测点组成的大坝安全评价体系，结合机器学习算法对监测数据的异常、趋势与风险等级进行自动识别，将不同模型输出的评价结果进行加权融合，实现大坝安全智能评价。本文主要介绍大坝渗流安全评价、结构安全评价及抗震安全评价三大模块，以湖北省黄陂区7座中小型水库为例的工程应用表明，该系统能够实现工程安全状态评判，显著提升了安全评价的规范化、准确性与智能化水平，为大坝运行管理提供科学决策支撑。

Abstract: To address the insufficient standardization and low level of informatization in traditional dam safety evaluations, this study, based on the Guidelines for Safety Evaluation of Reservoir Dams (SL258-2017), develops a dam safety evaluation system based on a micro-service architecture and the Dameng Database. The technical architecture comprises four layers—data, service, access, and presentation—along with four core subsystems. Centered on multi-source monitoring data and supported by model collaboration and integration, a hierarchical dam safety evaluation framework is constructed, consisting of monitoring objects, monitoring parts, monitoring items, and monitoring points. By incorporating machine learning algorithms, the system automatically identifies anomalies, trends, and risk levels within monitoring data, and performs weighted fusion of evaluation results from different models to achieve intelligent dam safety assessment. The study focuses on three major modules: seepage safety evaluation, structural safety evaluation, and seismic safety evaluation. An engineering application involving seven medium- and small-sized reservoirs in Huangpi District, Hubei Province, demonstrates that the system can effectively determine the safety status of dam projects, significantly improving the standardization, accuracy, and intelligence of safety evaluations. The proposed system provides robust scientific support for decision-making in dam operation and management.