The application of a cloud model based on a wavelet de-noising method in the determination of a dam safety-monitoring index of displacement

2013 ◽  
Author(s):  
Kai Zhu ◽  
Dong Qin ◽  
Chen Chen ◽  
Geng Feng ◽  
Fengshan Zhang
Keyword(s):  
Cloud Model ◽  
Safety Monitoring ◽  
Dam Safety ◽  
Model Based ◽  
Dam Safety Monitoring ◽  
Monitoring Index

Study on Determining Safety-Monitoring Index for Concrete Dam Based on Cloud Model

2012 ◽  
Vol 226-228 ◽  
pp. 1106-1110 ◽  
Author(s):  
Dong Qin ◽  
Xue Qin Zheng ◽  
Song Lin Wang
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Cloud Model ◽  
Safety Monitoring ◽  
Monitoring Data ◽  
Concrete Dam ◽  
Deterministic Function ◽  
Monitoring Index

The paper, based on analyzing original monitoring data, employs forward and backward cloud algorithm in studying determining safety-monitoring index for concrete dam ,which integrates randomness and fuzziness into of qualitative concept of digital features. By means of above monitoring data, its digital characteristics can be easily transformed to the “quantitative-qualitative- quantitative” change. The final generated quantitative value constitutes the cloud diagram where each droplet demonstrates the characterization of raw monitoring data. At the same time, it also shows the randomness and fuzziness of monitored value. we can study out the safety monitoring indexes according to different remarkable levels by using the probability density function and deterministic function which completed by cloud algorithm. In the end, it is obtained with practice that this method is more suitable and reliability.

scholarly journals Application of the Bayesian Belief Nets in dam safety monitoring

2012 ◽  
Vol 44 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Dorota Mirosław-Świątek ◽  
Mariusz Kembłowski ◽  
Władysław Jankowski
Keyword(s):  
Water Pressure ◽  
Safety Monitoring ◽  
Data Interpretation ◽  
Technical Condition ◽  
Monitoring Data ◽  
Earth Dam ◽  
Physical Parameters ◽  
Dam Safety ◽  
Dam Safety Monitoring ◽  
Bayesian Belief Nets

Application of the Bayesian Belief Nets in dam safety monitoring The systems for earth dam monitoring should enable measurements of basic physical parameters describing the behavior of the structure, including: soil water pressure, soil stress, displacements, leaks, and drainage discharges. In the case of earth dam safety assessment, the monitoring data are used to detect any anomalies in dam behavior. In this paper, the dam safety has been analyzed using the Bayesian Nets. Two types of information: water pressure measurements and drainage discharge measurements are used in analyses. The seepage anomalies in the Klimkówka Dam were considered in demonstrate the practical advantages of using the Bayesian Nets for monitoring data interpretation. Presented examples of the Bayesian Nets applications (forward and backward propagation) in analysis of seepage through earth dams show that this method can be an effective tool supporting an assessment of dams technical condition and monitoring of the dam safety.

Quantitative and Comprehensive Evaluation of Qualitative Indices in Dam Safety Monitoring

2011 ◽  
Vol 301-303 ◽  
pp. 924-931
Author(s):  
Bo Xu ◽  
Hui Xia ◽  
Yuan Yao
Keyword(s):  
Distance Function ◽  
Evaluation System ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Safety Monitoring ◽  
Dam Safety ◽  
Grey Theory ◽  
Comprehensive Evaluation Method ◽  
Dam Safety Monitoring ◽  
Qualitative Index

Since there are few methods to evaluate the qualitative index in dam safety monitoring and the evaluation system is imperfect, in this paper a new quantitative and comprehensive evaluation method for qualitative index is explored with the introduction of the method of interval marking, Set-Valued Statistics, grey theory and Jousselme distance function. Firstly, the interval marking method and Set-Valued Statistics are used to obtain the comprehensive quantitative value; then the evaluation class of the comprehensive quantitative value is quantified and the evidence vector is obtained through grey theory; next the weights of all qualitative indices are obtained through Jousselme distance function; finally the comprehensive influence of the qualitative indices on dam safety is determined by using the evidence vector and weights. The case study proves that this method is feasible which can reasonably determine the influence of qualitative index on dam safety.

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