Application of Deep Learning and Symmetrized Dot Pattern to Detect Surge Arrester Status

Surge arresters primarily restrain lightning and switch surges in the power system to avoid damaging power equipment. When a surge arrester fails, it leads to huge damage to the power equipment. Therefore, this study proposed the application of a convolutional neural network (CNN) combined with a symmetrized dot pattern (SDP) to detect the state of the surge arrester. First, four typical fault types were constructed for the 18 kV surge arrester, including its normal state, aging of the internal valve, internal humidity, and salt damage to the insulation. Then, the partial discharge signal was measured and extracted using a high-speed data acquisition (DAQ) card, while a snowflake map was established by SDP for the features of each fault type. Finally, CNN was used to detect the status of the surge arrester. This study also used a histogram of oriented gradient (HOG) with support vendor machine (SVM), backpropagation neural network (BPNN), and k-nearest neighbors (KNN) for image feature extraction and identification. The result shows that the proposed method had the highest accuracy at 97.9%, followed by 95% for HOG + SVM, 94.6% for HOG + BPNN, and 91.2% for HOG + KNN. Therefore, the proposed method can effectively detect the fault status of surge arresters.

Development of methodology and measures to ensure the reliability of energy systems equipment

THE PURPOSE: The article presents the results of the development of a methodology for the design calculation of reliability and changes in the level of reliability of energy systems, taking into account the influence of control actions based on statistical methods of collection, analysis and models of experimental data processing.METHODS: The system analysis and generalization of experimental data on technological failures of the main equipment of thermal power plants were used in the calculation assessment.RESULTS: The objective function of controlling the reliability parameters of the thermal power plant power equipment is proposed. The approbation of the presented objective control function was performed, which showed the adequacy of the results obtained to assess the reliability of the main nodes and elements of the TPP power equipment.CONCLUSION: The results of the conducted studies show that when determining reliability indicators, it is necessary to take into account the actual technical condition of individual elements and resource-determining functional units of thermal power plant power equipment. The results obtained can be used to develop a methodology for evaluating control actions for calculating the output control parameters and a mathematical model for changing the output characteristics of TPP steam turbines in terms of heat and electric energy generation, as well as at the stage of developing design documentation for the creation of structural elements and practical recommendations in order to extend the service life of power equipment generating systems based on digital technologies.

Dielectric Properties of Electrical Insulating Liquids for High Voltage Electric Devices in a Time-Varying Electric Field

The motivation to improve components in electric power equipment brings new proposals from world-renowned scientists to strengthen them in operation. An essential part of every electric power equipment is its insulation system, which must have the best possible parameters. The current problem with mineral oil replacement is investigating and testing other alternative electrical insulating liquids. In this paper, we present a comparison of mineral and hydrocarbon oil (liquefied gas) in terms of conductivity and relaxation mechanisms in the complex plane of the Cole-Cole diagram and dielectric losses. We perform the comparison using the method of dielectric relaxation spectroscopy in the frequency domain at different intensities of the time-varying electric field 0.5 kV/m, 5 kV/m, and 50 kV/m. With the increasing intensity of the time-varying electric field, there is a better approximation of the Debye behavior in all captured polarization processes of the investigated oils. By comparing the distribution of relaxation times, mineral oil shows closer characteristics to Debye relaxation. From the point of view of dielectric losses at the main frequency, hydrocarbon oil achieves better dielectric properties at all applied intensities of the time-varying electric field, which is very important for practical use.

MSIS: Multispectral Instance Segmentation Method for Power Equipment

Infrared image of power equipment is widely used in power equipment fault detection, and segmentation of infrared images is an important step in power equipment thermal fault detection. Nevertheless, since the overlap of the equipment, the complex background, and the low contrast of the infrared image, the current method still cannot complete the detection and segmentation of the power equipment well. To better segment the power equipment in the infrared image, in this paper, a multispectral instance segmentation (MSIS) based on SOLOv2 is designed, which is an end-to-end and single-stage network. First, we provide a novel structure of multispectral feature extraction, which can simultaneously obtain rich features in visible images and infrared images. Secondly, a module of feature fusion (MARFN) has been constructed to fully obtain fusion features. Finally, the combination of multispectral feature extraction, the module of feature fusion (MARFN), and instance segmentation (SOLOv2) realize multispectral instance segmentation of power equipment. The experimental results show that the proposed MSIS model has an excellent performance in the instance segmentation of power equipment. The MSIS based on ResNet-50 has 40.06% AP.

Research on hazard installations identification method of power equipment in ship

Hazard installation identification was the key and difficult point for ship power equipment safety management. According to the characteristics of ship power equipments, this article analyzed the characteristic of hazard installations, given the range and classification of hazard installation identification. Combining hazard installation checklist and routing inspection, the method and process of hazards installation identification was proposed for ship power equipment, which laid a foundation for its risk assessment and control.

Partial Renewal is a Tool for an Increase in the Environmental Efficiency of the Worn-out Power Facilities

The mankind created the global production that has an increasingly harmful effect on the natural environment. The present-day condition of natural environment causes much concern. A global environmental problem has inevitably emerged and now it requires a decrease in the intensity of the harmful action of available productive facilities. The purpose of the research done was to substantiate and find a potential opportunity for the use of a new approach to an increase in the level of ecological compatibility due to a partial renewal of the worn-out equipment. A substantial portion of the domestic energy equipment has a low level of the process-related functioning efficiency (including ecological efficiency). A global practice shows that the problems of the improvement of technological parameters can be solved in a different way to provide failure –free functioning of power facilities. The analysis of the circumstances existing nowadays in the field of the interaction of domestic power engineering and natural environment gives us an opportunity to adhere to the opinion that the use of the method of partial renewal is objectively affordable and it is a highly efficient tool for the reduction of the degree of harmful action on the part of power equipment. The purpose of this research paper was to show technological opportunities of the method of a partial renewal of worn-out engineering facilities (first of all power equipment and especially boiler plants) as an affordable tool for a decrease of the degree of their harmful action on the environment. Among the branches of the domestic industry, the power engineering branch needs badly a partial renewal and in the first turn these are boiler plants. This type of renewal is of vital importance for Ukraine that possesses a huge fleet of completely worn-out boiler plants. It is advisable to perform an integrated partial renewal. The partial renewal can involve all or individual parts of the entire chain of process elements. A successful fulfillment of the program of partial renewal is defined by a high quality control of the system of scientific and organizational-&-engineering problems relating to the renewal arrangement and realization. An issue relating to an index of the estimation of the extent of renewal of engineering facilities is of great importance. The capital inputs into the partial renewal are always justified for all intents and purposes. As for the conception of the renewal of the worn-out equipment the partial renewal can become an important launching low-cost step that will simplify the expected realization of the program of complete renewal.

Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis

The application of data mining technology in power field mainly focuses on the application of power defect text and dispatching text. However, the power operation and maintenance data contains a lot of information about power equipment suppliers. Taking the operation and maintenance text involving power equipment suppliers as an example, this paper summarizes the theme of operation and maintenance text and studies the evaluation model of power equipment suppliers. The next sentence prediction analysis model of single round dialogue text based on transformer bidirectional encoder prediction and cosine similarity weighting is proposed, which can effectively divide the topic of dialogue text. Aiming at the semantic richness and complexity of power operation and maintenance text, a supplier evaluation model based on text emotion analysis is proposed. Based on the expansion of the entries and attributes of the existing power ontology dictionary, the dialogue emotion analysis rules are established to realize the normal evaluation of power equipment suppliers.

Power Equipment Defects Prediction Based on the Joint Solution of Classification and Regression Problems Using Machine Learning Methods

Our paper proposes a method for constructing a system for predicting defects and failures of power equipment and the time of their occurrence based on the joint solution of regression and classification problems using machine learning methods. A distinctive feature of this method is the use of the equipment’s technical condition index as an informative parameter. The results of calculating and visualizing the technical condition index in relation to the electro-hydraulic automatic control system of hydropower turbine when predicting the defect “clogging of drainage channels” showed that its determination both for an equipment and for a group of its functional units allows one to quickly and with the required accuracy assess the arising technological disturbances in the operation of power equipment. In order to predict the behavior of the technical condition index of the automatic control system of the turbine, the optimal tuning of the LSTM model of the recurrent neural network was developed and carried out. The result of the application of the model was the forecast of the technical condition index achievement and the limiting characteristic according to the current time data on its values. The developed model accurately predicted the behavior of the technical condition index at time intervals of 3 and 10 h, which made it possible to draw a conclusion about its applicability for early identification of the investigated defect in the automatic control system of the turbine. Thus, we can conclude that the joint solution of regression and classification problems using an information parameter in the form of a technical condition index allows one to develop systems for predicting defects, one significant advantage of which is the ability to early determine the development of degradation phenomena in power equipment.