基于实测信息的海堤PHM系统框架及关键技术研究

蓝祝光; 黄铭

doi:10.13961/j.cnki.stbctb.2017.03.053

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基于实测信息的海堤PHM系统框架及关键技术研究

实验研究

- 基于实测信息的海堤PHM系统框架及关键技术研究
- Framework and Key Technologies of Seawall Prognostic and Health Management System Based on Measured Information
- 水土保持通报 2017年37卷第3期页码：307-313
- 作者机构：
  
  1. 合肥工业大学土木与水利工程学院,安徽,合肥,230009
  2. 三峡大学三峡库区地质灾害教育部重点实验室,湖北,宜昌,443000
- 作者简介：
- 基金信息：
  
  水利部公益性行业专项“皖江城市带长江河势变化与洲滩综合利用研究”（201401063-02）;三峡库区地质灾害教育部重点实验室开放研究基金“库区边坡安全监测PHM系统关键技术研究”（2015KDZ03）;安徽省科技攻关计划项目（1604a0802106）
- DOI：10.13961/j.cnki.stbctb.2017.03.053
  中图分类号：
- 纸质出版：2017
- 稿件说明：
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蓝祝光, 黄铭. 基于实测信息的海堤PHM系统框架及关键技术研究[J]. 水土保持通报, 2017,37(3):307-313.

LAN Zhuguang, HUANG Ming. Framework and Key Technologies of Seawall Prognostic and Health Management System Based on Measured Information[J]. Bulletin of Soiland Water Conservation, 2017, 37(3): 307-313.
蓝祝光, 黄铭. 基于实测信息的海堤PHM系统框架及关键技术研究[J]. 水土保持通报, 2017,37(3):307-313. DOI： 10.13961/j.cnki.stbctb.2017.03.053.

LAN Zhuguang, HUANG Ming. Framework and Key Technologies of Seawall Prognostic and Health Management System Based on Measured Information[J]. Bulletin of Soiland Water Conservation, 2017, 37(3): 307-313. DOI： 10.13961/j.cnki.stbctb.2017.03.053.

摘要

[目的] 解决海堤传统维修方式存在维修保障能力差、易造成重大损失的问题，建立科学的海堤健康管理系统。[方法] 将先进的故障预测与健康管理（prognostic and health management， PHM）技术应用于海堤工程中，研究建立海堤PHM系统，并深入探讨海堤PHM系统的预测和健康评估方法。结合海堤特点及海量、高频的实测信息，提出将具有强大寻优能力的水循环算法与神经网络相结合，形成海堤状态预测模型；并综合考量海堤健康影响因素，基于模糊数学建立系统健康评估模型。[结果] 实例分析表明，所建立的海堤PHM系统预测模型和健康评估模型可有效预测海堤状态，并对海堤现阶段和未来一定时段的健康状况进行准确的实时评估和预评估。[结论] 形成了适应海堤工程特点的海堤PHM系统框架，所建立的预测模型和健康评估模型科学有效。

Abstract

[Objective] To solve the problems of maintenance support inability and easily causing significant loss in the traditional maintenance mode of seawall

in order to establish a scientific health management system of seawall.[Methods] The advanced prognostic and health management(PHM) technology was applied to the seawall project. The PHM system of seawall was set up

and the prediction model and health assessment model of seawall PHM system were studied. Combining with the characteristics of seawall and the massive high frequency-measured information

the prediction model of seawall state was put forward based on the water cycle algorithm with strong searching ability combined with the neural network. On the premise of the seawall health factors were considered comprehensively

the system health assessment model was set up based on fuzzy mathematics.[Results] The example analysis showed that the prediction model could predict seawall condition effectively and the health assessment model could assess seawall health in real-time and can pre-estimate seawall health accurately for present and future.[Conclusion] The seawall PHM system framework established meet the characteristics of seawall project. The prediction model and health assessment model are scientific and effective.

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