Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking s...Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.展开更多
Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then p...Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.展开更多
The 130m high Punt dal Gall dam is located at the Swiss-Italian border in the South-eastern part of Switzerland and was completed in 1969.The dam is founded on highly folded and partially crushed dolomite and limeston...The 130m high Punt dal Gall dam is located at the Swiss-Italian border in the South-eastern part of Switzerland and was completed in 1969.The dam is founded on highly folded and partially crushed dolomite and limestone formations.A grout curtain with an area of 120,000m^(2) was provided for controlling seepage.For the monitoring of the dam deformations five inverted pendulums were installed in the dam and three in the rock foundation of the right abutment outside of the dam.For a seasonal water level fluctuation in the reservoir of about 60 m the maximum amplitude of the radial displacement is 25 mm,which includes both the effects of the water load and temperature effects.Furthermore a comprehensive geodetic network was established,57 joint meters were installed and cracks in the crest gallery are monitored by crack meters.There are also thermometers,piczometers and rocmeters.Springs at the left and fight banks of the dam are monitored and chemical analyses of the seepage water and springs are performed regularly.The dam is equipped with strong motion instruments and several near-field earthquakes have been recorded in the past.The paper describes the long-term safety monitoring of this 42 years old arch dam.A short description of the Swiss practice in dam safety monitoring and emergency planning is also given.展开更多
文摘Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51079046, 50909041, 50809025, and 50879024)the National Science and Technology Support Plan (Grant Nos. 2008BAB29B03and 2008BAB29B06)+6 种基金the Special Fund of State Key Laboratory of China (Grant Nos. 2009586012, 2009586912, and 2010585212)the Fundamental Research Funds for the Central Universities (Grant Nos. 2009B08514, 2010B20414, 2010B01414, and 2010B14114)the China Hydropower Engineering Consulting Group Co. Science and Technology Support Pro-ject (Grant No. CHC-KJ-2007-02)Jiangsu Province "333 High-Level Personnel Training Project" (Grant No. 2017-B08037)Graduate Innovation Program of Universities in Jiangsu Province (Grant No. CX09B_ 163Z)Dominant Discipline Construction Program Funded Projects of University in Jiangsu ProvineScience Foundation for the Excellent Youth Scholars of Ministry of Education of China (Grant No. 20070294023)
文摘Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.
文摘The 130m high Punt dal Gall dam is located at the Swiss-Italian border in the South-eastern part of Switzerland and was completed in 1969.The dam is founded on highly folded and partially crushed dolomite and limestone formations.A grout curtain with an area of 120,000m^(2) was provided for controlling seepage.For the monitoring of the dam deformations five inverted pendulums were installed in the dam and three in the rock foundation of the right abutment outside of the dam.For a seasonal water level fluctuation in the reservoir of about 60 m the maximum amplitude of the radial displacement is 25 mm,which includes both the effects of the water load and temperature effects.Furthermore a comprehensive geodetic network was established,57 joint meters were installed and cracks in the crest gallery are monitored by crack meters.There are also thermometers,piczometers and rocmeters.Springs at the left and fight banks of the dam are monitored and chemical analyses of the seepage water and springs are performed regularly.The dam is equipped with strong motion instruments and several near-field earthquakes have been recorded in the past.The paper describes the long-term safety monitoring of this 42 years old arch dam.A short description of the Swiss practice in dam safety monitoring and emergency planning is also given.