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Large gas turbine control system fail during operation inevitably. Due to the various failure causes and failure modes, the troubleshooting process is relatively complicated. Combining the current situation of gas turbine control system fault diagnosis, the fault examples of the gas turbine control system are sorted out and summarized into five types of faults. Using distributed database, micro-service framework Spring Cloud, front-end framework Vue.js, following the principle of separation of front-end and back-end , carry out the design and development of the fault diagnosis system for GT control system based on B/S architecture, so that power plant staff can use the system to analyze and diagnose faults, and improve the accuracy and efficiency of fault diagnosis of the GT control system.

Liquid leakage in power plant pipelines not only wastes resources, but also affects the safe and stable production requirements of power plants. In order to detect the liquid leakage area of power plant pipelines timely and accurately, and meet the requirements of practical application, this paper proposes a method of power plant pipeline liquid leakage detection based on improved ViBe algorithm. According to the characteristics of power plant pipeline liquid leakage, and the traditional ViBe algorithm cannot adapt to dynamic background changes and quickly eliminate ghosting problems in the detection results, this paper chooses to expand the sampling neighborhood of the background model and adopts an adaptive radius threshold determined by the dispersion coefficient. To improve the accuracy of leak detection, and re-determine the leaking and non-leaking areas through Otsu threshold calculation, quickly and effectively suppress the appearance of ghost areas, so as to make the segmented power plant pipeline liquid leakage area more complete.

To solve defects of the traditional Z-source topology, an enhanced three-level neutral-point-clamped quasi-Z-source inverter (3L NPC QZSI) topology is proposed in the paper. New topology combines the advantages of three-level neutral-point-clamped inverter with the advantages of quasi-z-source network. Compared with traditional topology, new topology can effectively enhance inverter boost capability, reduce the capacitor voltage stress and suppress start-up shock current. All the conclusion mentioned above have been confirmed by simulations and experiment.

To improve the electric vehicle charging infrastructure and accelerate the development of electric vehicles, the optimization of electric vehicle charging stations’ location and size are studied in this paper. The annual comprehensive cost of society, including user cost and charging station cost, is regarded as the objective function. Weight coefficients are added to the function for increasing the proportion of user cost. An optimized mathematical model for electric vehicle charging stations based on users’ benefit is established. The improved Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is adopted to solve this mathematical mode, and result which contain the optimal location and size of electric vehicle charging stations is obtained. Finally, an actual area is taken as the case study to optimize the location and size of electric vehicle charging stations by solving the mathematical model proposed in this paper with the improved QPSO algorithm. Rationality and validity of the model are well improved by the scientific reasonable result.

Differential evolution algorithm is a heuristic global search technology based on population, which has received extensive attention from the academic community. Evolution algorithm is applied to the identification and optimization of double-tank system in this article. Firstly, the paper introduces the basic principle of the system identification and differential evolution algorithm. Secondly, design the identification scheme of double-tank system based on differential evolution algorithm. Identify the system according to the data measured in the experiment. Based on the commonly used three models and combined with DE/rand/1/bin, the model structure which best complies with the original experimental data is selected, and the improved form of the difference algorithm is further studied on the basis of the model structure. A large number of experiments have been carried out, the algorithm in other references may only improve one of CR or F, and the two will be all compared in this paper. The results of comparative analysis show that the improved differential evolution algorithm is, to some extent, superior to the basic differential evolution algorithm on identification accuracy of double-tank.

Power system short-term load forecasting have a significant role in the power system planning and reliable operation. This paper compared the result of two prediction models BP neural network and wavelet neural network (WNN). According to comparison results, WNN model in the case of the same number of nodes have better predictive accuracy. In order to achieve the balance of the least input neurons and prediction precision, the regionality human body amenity indicator is used as the input of meteorological factors. Meanwhile, in order to take full advantage of the historical load data, improve the prediction precision, the concept of innovation is introduced and the load data of forecast base day is included in the input range. The model is verified by using the actual data, the results show that the prediction results is accurate and the model in practical and effective.

Power system short-term load forecasting have a significant role in the power system planning and reliable operation. According to the deficiency of time variation and easy to fall into the local least value in feed forward neural networks, a forecasting Model is provided by using Elman feedback neural network. Hourly weather factors can improve the prediction precision. In order to achieve the balance of the least input neurons and prediction precision, the regionality human body amenity indicator is used as the input of meteorological factors. Meanwhile, in order to take full advantage of the historical load data, improve the prediction precision, the concept of innovation is introduced and the load data of forecast base day is included in the input range. The model is verified by using the actual data, the results show that the prediction results is accurate and the model in practical and effective.

In order to enhance the accuracy rate of the fault diagnosis of condenser, a fault diagnosis method based on consensus information fusion is presented. The decision-making distance is calculated and the closest supporting group is found. By integrating the results of the closest supporting group, the best decision-making value of fault diagnosis is obtained. This method is applied in the simulation experiment of condenser fault diagnosis in this paper. The experimental results show that the consensus information fusion method is able to improve the reliability of the fault diagnosis and reduce erratic elements evidently.

The high quality of the information source can improve the accuracy of target recognition when data is fused via multi-information sources. In this paper, it proposes a new method to determine the reliability coefficient of the information source by information criterion. With calculating the reliabilities of information sources, the more reliable source would be used in the combination process to improve the recognition rate. The experiment results prove that the better results will be obtained with the reliability coefficient to choose the source in information fusion.

In the application of particle holography analysis, the diameter measurement is basic and important. A novel approach of segmentation is proposed. For improving the accuracy of measurement, the method of bi-threshold is used firstly and then the edge linking method is adopted to get the more accuracy segmented particle image. The experiment tests showed the less relative error is in the diameter measurement with the algorithm, compared with the bi-threshold algorithm. The study has further meanings on the processing of particles field holography.