As the time goes by, the seal of the bearing oil tank cover of the hydropower station is gradually worn, the gap between dynamic and static increases, and the oil mist escapes seriously. In order to explore the influence of wear clearance and unit speed on oil mist leakage in oil tank seal, a geometric model of thrust bearing oil tank seal of generator was established. Using SST κ-ω turbulence model, steady state numerical simulation was carried out for oil mist leakage at different clearances (0.2 mm-2 mm) and rotating speeds (100 r/min-500 r/min). It is found that the influence of clearance value on oil mist leakage is much higher than that of rotational speed. With the increase of clearance, the throttling effect of sealing teeth is weakened, the sealing inlet pressure is reduced, and the oil mist leakage at the top of the tank cover is aggravated. The inlet and outlet velocity increases with the increase of wear clearance value. When the clearance value increases from 0.2 mm to 2 mm, the inlet velocity increases from 20 m/s to 113 m/s, the outlet speed increases from 76 m/s to 144 m/s, the leakage volume increases from 0.034 4 kg/s to 0.053 8 kg/s. The research can provide a theoretical basis for the optimization of sealing structure, the formulation of power station operation strategy, and the judgment of sealing performance.

In previous researches on intelligent fault diagnosis methods of the hydroelectric generating unit, the subjectivity of the artificial selection of the fault classification characteristics and the limitations of small sample data have important impacts on the accuracy of fault diagnosis results. To solve this problem, a CNN-SVM method for the fault diagnosis of the hydroelectric generating unit was proposed by combining with the feature extraction advantages of convolutional neural network (CNN) and the excellent ability of support vector machine (SVM) in processing small sample. In this method, the time-domain diagram of the vibration signal of the hydroelectric generating unit was used as the model input, and the CNN method was employed to extract the signal features. Then, the extracted feature vector was input to the SVM method to realize the final fault diagnosis of the unit. Finally, the advantages of the diagnosis method proposed in this paper were verified through a specific example analysis.

At present, most of the domestic parallel pump groups adopt a single-objective control model, and only pay attention to the energy efficiency optimization of operating conditions and operating costs in the process of use, and cannot adjust the operation strategy under the real-time working conditions of the pump group according to the comprehensive energy efficiency state of the pump group in the whole life cycle. A multi-objective pump group energy efficiency optimization control model can be independently adjusted according to the energy efficiency state of the current pump set in the whole life cycle. The weight coefficients of three objective functions can be autonomously adjusted, which improves the energy efficiency of the pump set throughout its life cycle and extends the life of the pump set. The objective function was determined by the ideal point value and distance deviation method. The multi-objective ideal point model was solved by LINGO. The optimal solution with the highest total system efficiency, the lowest pump group specific energy consumption and the highest system reliability was obtained. Experimental results show that the improved multi-objective ideal point model can adjust the target weight combination according to the real-time state of the pump group, so as to adjust the real-time control strategy of the pump group.

Accurate load forecasting is of great significance for improving the level of grid planning and accurately guiding investment. In view of the shortcoming of over-fitting in the combined forecasting model of empirical risk minimization, a combined forecasting model based on social learning multi-objective particle swarm optimization algorithm was proposed in term of partial least squares regression model, support vector regression model and grey prediction GM (1, 1) model. The uncertainty function information entropy of weight was introduced to represent the expected risk, and the empirical risk and expected risk were comprehensively considered in the model. The simulation results show that the proposed method has higher prediction accuracy than the single forecasting model and the other two combined forecasting models, and the social learning multi-objective particle swarm optimization algorithm has stronger global search ability and optimization performance.

Taking Dawen River Basin in Shandong Province as an example, Mann-Kendall method was used to analyze the consistency of the 6 h, 12 h, 24 h and 3 d annual extreme rainfall data. The regional linear moment method was used to infer the design value of the site rainstorm, and the regional design value was compared with the single-station linear moment method. The spatial distribution map of the design value of the 50-year rainstorm in Dawen River Basin was drawn. The results show that the Dawen River Basin can be divided into 3 hydrometeorological homogeneous regions, and the optimal distribution frequency linetype is dominated by the generalized extreme-value distribution (GEV). The difference (mean absolute relative error) between the results of single-station L-moment frequency analysis method and regional L-moments frequency analysis method decreases with the increase of the length of the sample series, and the larger the return period is, the greater the gap is; The spatial distribution of the designed rainstorm values in Dawen River Basin is not uniform, but the distribution trend of each period is basically similar.

In order to evaluate the matching degree between water conservancy project for tobacco and tobacco drought in Guizhou Province, the daily rainfall data from 17 meteorological stations, tobacco production and water supply data of water conservancy project for tobacco during 2006-2017 was used to construct a matching degree evaluation model, and grade standard of matching degree was proposed. The results show that the water conservancy project for tobacco alleviated tobacco drought to a certain extent. However, the matching relationship between water conservancy project for tobacco and tobacco drought still needs to be improved. The matching degrees of Qianxinan, Qiannan, Anshun, Liupanshui, and Guiyang were 55.4%, 52.1%, 46.2%, 45.9%, 44.7%, and 34.4%, respectively, which were in the fourth grade with a poor matching degree. The matching degrees of Bijie, Qiandongnan, Tongren, and Zunyi were 31.7%, 28.6%, and 26.8%, respectively, which were in the fifth grade with a worse matching degree. In different growth stages, water shortage in root extension period mainly occurred in 90% and 95% effective rainfall frequency, and water shortage in prosperous and mature periods mainly occurred in each effective rainfall frequency. Additionally, the lowest matching degree occurred at the mature period. It is suggested that in the future, the layout of the water conservancy project for tobacco should focus on strengthening the construction in Zunyi, Tongren and Qiandongnan, and improve the rationality of the layout of water conservancy project for tobacco, as well as enhance the guarantee ability of drought resistance of tobacco.

In order to efficiently utilize water resources in the upper reaches of the Minjiang River Basin, based on hydro-meteorological data of the basin from 1960 to 2018, a variety of statistical theories were used to analyze the trend, cycle and abrupt point of runoff. The elastic coefficient method based on Budyko theory (Choudhury-Yang formula) and the comparative method of cumulated slope change rate (SCRCQ method) were used to analyze the attribution of runoff changes. The results show that the runoff decreases significantly at a rate of 12.5 mm/10a, and a sudden change occurred in 1993. There are 3 years, 8 years, 12 years and 18 years main cycles of runoff change, and the annual distribution is uneven, mainly concentrated in summer and autumn, accounting for 73.6%. Rainfall is the most sensitive to runoff, followed by underlying surface parameters, and potential evapotranspiration is the least sensitive. Choudhury-Yang formula and SCRCQ method calculated that the contribution rate of climate change to runoff reduction was 58.13% and 63.29%, respectively. Climate change was the main factor of runoff reduction in the study area, and the contribution rate of human activities to runoff reduction should not be underestimated, reaching 41.87% and 36.71%, respectively.

In order to investigate the non-stationary characteristics of runoff series in changing environments and to better predict the occurrence of flood events, taking Hutuo River in the Haihe River Basin as the research object, GAMLSS model was used to conduct a non-coherent frequency analysis of the runoff series during 1970 and 2012 by taking time, reservoir indicators and climate indicators as covariates. The results show that the runoff series of Hutuo River has obvious non-stationary characteristics with trend and abrupt changes. The GAMLSS model can better simulate the runoff series in changing environments and describe the flood regimes under the influence of climate change, thus outperforming the traditional model. Changes of the large-scale climate indicators NINO1+2 and NAO significantly affect the flood events in the Hutuo River, with increasing values of these two climate indicators indicating low flood risk and decreasing values indicating high flood risk.

In order to illustrate the influence mechanism of flow distribution on slope of urban asphalt road, two-dimensional shallow water equations were applied to simulate runoff characteristics on asphalt slope. Comprehensive sensitivity analysis was performed on multiple factors (cross slope, longitudinal slope, slope width, slope length, rainfall intensity and roughness coefficient) which caused different degrees of ponding on asphalt slope. The maximum flow depth was taken as the sensitivity analysis index. Both range and variance analysis were performed, through which the sensitivity ranking of the influencing factors were obtained and the significance level can be clarified as well. The results show that under overflow drainage condition, cross slope, pavement width and rainfall intensity have significant effects on flow depth; Slope length has no significant effect on flow depth. Flow depth is negatively correlated with cross slope, and positively correlated with rainfall intensity, pavement width and slope length, and negatively correlated first and then positively correlated with the roughness coefficient. The research results can provide reference for engineering practice.

Focusing on the influence of the project of water diversion from Yangtze River to Taihu Lake on the hydrodynamic characteristics of Gonghu Bay, the physical model of the wind-driven currents in Taihu Lake was used to analyze the influence on the hydrodynamic characteristics and the vertical flow velocity and planar circulation distribution in Gonghu Bay under the different wind speeds and different diversion flow of Wangyu River in the typical wind field in summer. The results indicate that the variation of Wangyu River diversion flow affects the hydrodynamic characteristics of Gonghu Bay mainly in the near and middle regions, but has little impact on Taihu Lake; The implementation of the water diversion project from Yangtze River to Taihu Lake significantly changes the vertical velocity distribution characteristics on the outlet axis of Wangyu River in the near and middle regions, but has no effect on the vertical velocity distribution characteristics at the junction section; The characteristics of the planar circulation in Gonghu Bay are affected by both wind speed and diversion flow, the changes of wind speed and diversion flow have a significant impact on the area, location and shape of the plane circulation. The research results can provide hydrodynamic theoretical support for evaluating the impact of the water diversion project from Yangtze River to Taihu Lake on the water environment of Gonghu Bay.