Selection of evaluation indicators for water supply network health status based on factor analysis

被引:0
|
作者
Ding X. [1 ]
Shi X. [2 ]
Ling M. [2 ]
Huang Z. [3 ]
An Q. [2 ]
Liu S. [1 ]
机构
[1] Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing
[2] School of Water Conservancy and Engineering, Zhengzhou University, Zhengzhou
[3] College of New Energy and Environment, Jilin University, Changchun
关键词
Contribution degree; Factor analysis; Health status evaluation indicator; Sensitivity; Water supply network;
D O I
10.3880/j.issn.1004-6933.2021.06.011
中图分类号
学科分类号
摘要
In order to select highly representative and sensitive indicators for water supply network health status evaluation, 11 water supply network health status evaluation indicators were analyzed by hierarchy process, and the contribution calculation and sensitivity analysis were carried out based on factor analysis method. The results of analytic hierarchy process show that the evaluation system includes external environment influencing factors on the static structure of the pipeline, internal static structure influencing factors of the pipeline, water quality influencing factors and hydraulic influencing factors. The results of contribution and sensitivity analysis show that the eight indicators of inner and outer lining, pipe diameter, ratio of node flow to total flow, residual chlorine, ratio of node pressure to minimum service pressure, soil cover thickness, pipe material and pipe age should be taken as the basic required indicators, and the data accuracy of inner and outer lining, pipe diameter, ratio of node flow to total flow, residual chlorine, soil cover thickness and pipe age should be improved as much as possible. © 2021, Editorial Board of Water Resources Protection. All rights reserved.
引用
收藏
页码:67 / 73
页数:6
相关论文
共 20 条
  • [1] LIU Bo, WANG Ziwei, WANG Wenpeng, Et al., Spatiotemporal characteristics analysis of major indicators of urban water use efficiencies over mainland China[J], Journal of Hohai University(Natural Sciences), 48, 6, pp. 534-541, (2020)
  • [2] PELLETIER G, MAILHOT A, VILLENEUVE J P., Modeling water pipe breaks:three case studies[J], Journal of Water Resources Planning and Management, 129, 2, pp. 115-123, (2003)
  • [3] ZHANG Xianguo, WANG Huizhen, WANG Junling, Et al., Screening and calculation examples of leakage evaluation indexes of water supply network[J], Water & Wastewater Engineering, 47, 1, pp. 158-161, (2011)
  • [4] WANG Xumian, HUANG Tinglin, LIU Yong, Et al., The three-step screening method of indexes for cluster analysis in water supply systems subregion[J], Journal of Xian University of Architecture & Technology(Natural Science Edition), 41, 5, pp. 708-714, (2009)
  • [5] SUN Naicong, Application of expert evaluation method in technical analysis[J], Journal of Xian University of Arts and Science(Natural Science Edition), 16, 1, pp. 125-128, (2013)
  • [6] DING Mingjiang, WU Changchun, Application of expert evaluation method in risk analysis of oil and gas pipelines[J], Oil-Gas Field Surface Engineering, 1, pp. 10-15, (2004)
  • [7] WANG Chenghui, JIANG Shengzhong, An indexes system of Chinese insurance industrys competitiveness and its application[J], Nankai Economic Studies, 5, pp. 116-131, (2006)
  • [8] XU Jiaojiao, CHEN Bo, GAO Qingning, Information analysis method-factor analysis[J], Pioneering with Science & Technology Monthly, 25, 4, pp. 21-22, (2012)
  • [9] Xinhua LIU, Necessity and software operation of positive management in factor analysis[J], Journal of Chongqing Institute of Technology(Natural Science Edition), 23, 9, pp. 152-155, (2009)
  • [10] YE Mingque, YANG Yajuan, Erroneous zone identification and improvement of synthesis evaluation based on principal component analysis[J], The Journal of Quantitative & Technical Economics, 33, 10, pp. 142-153, (2016)