Reliability Of Electrical Equipment Research Articles

KENDALI BERBASIS WEB PADA ANOMALI NEUTRAL GROUND RESISTOR (NGR)

A real-time monitoring and control system for Neutral Grounding Resistor (NGR) has been developed utilizing Internet of Things (IoT) technology. The system employs the PZEM-004T sensor for measuring current and voltage, and the NodeMCU ESP8266 for data processing and communication. Measurement data is displayed in real-time on an LCD screen and a website, with early warning alerts provided through a buzzer/alarm if abnormal conditions are detected. This system addresses the limitations of traditional monitoring methods, which are typically visual and periodic, by enabling continuous monitoring. Integration with a circuit breaker adds an additional layer of protection by disconnecting the power supply when necessary. Testing results demonstrate the effectiveness of the device in measuring voltages ranging from 5V to 220V and current, with a reliance on internet connectivity to ensure measurement accuracy. This system offers an efficient and proactive solution for maintaining the safety and reliability of electrical equipment at substations

Reliability and economic evaluation of energy storage as backup and load regulation power supply in data centers

AbstractThe battery energy storage system (BESS) combines backup and load regulation functions, making it a potential alternative to the diesel generator (DG) as the backup power source for data centers. Some studies have been conducted on the reliability and cost–benefit of equipping data centers with BESS, but the impact of the reliability of external utility power and the expected outage losses have not been considered. Therefore, this study established a power supply reliability model that included the external utility power reliability and the electrical equipment reliability, and a cost–benefit model that took into account the BESS construction and replacement cost, the outage loss reduction, and the load regulation benefits. A case study was conducted on a data center in Beijing. The results indicate that: (a) the reliability and cost–benefit of BESS significantly vary with the reliability of the external utility power; (b) based on the 2022 utility power reliability data from various regions in China, in over 48% of the regions, the objective function value of BESS, the annual net income considering power outage losses, and the investment payback period are all superior to those of DG; and in over 27% of regions, the BESS–DG parallel system can serve as a suboptimal alternative to DG; (c) in regions with reliable utility power, BESS exhibits the potential as a feasible substitute for DG in providing backup and load regulation power to data centers.

Optimization of monitoring systems power cable lines

RELEVANCE. The length and complexity of the geography of medium voltage cable lines is at a high level. Such lines extend underground, on supports in the air. In order to constantly maintain the reliability of city power supply at a high level, any interruptions and accidents should be promptly corrected.TARGET. The main goal of the work is to develop the theory of medium voltage CL research, to practically and theoretically substantiate the search for the most convenient and effective installation for CL diagnostics, to study and develop possible modifications of CL diagnostic installations.METHODS. A variant of CL diagnostics based on the CPDA-60 installation is proposed, which makes it possible to find and localize the places where defects occur in the insulation based on the measurement and analysis of partial discharges (PD). Suitable for insulation monitoring in all types of high voltage cables. The CPDA installation can be used when testing new cable lines being put into operation, and to analyze the condition of old cables in operation.RESULTS. Cable lines require an integrated approach to diagnostics and monitoring, since the reliability of modern authentication systems for the generation and distribution of electricity is largely determined by the electrical reliability of electrical equipment. Technical diagnostics of equipment is a key link, the quality of which determines the efficiency of the processes of organizing production activities, strategic planning and renovation of electric grid assets.CONCLUSION. The study and analysis of the presented data and research allows us to form a conclusion regarding the method of measuring and localizing partial discharges (PD) in power cable lines (CL) using the Online Wire Testing System (OWTS) diagnostic system. The OWTS system allows real-time measurements without interrupting cable lines, making it especially valuable to the energy industry. Thanks to the introduction of advanced technologies and signal processing algorithms, the method has high accuracy and sensitivity to minimal manifestations of private discharges, which allows not only to detect, but also to accurately localize the location of defects in the insulation. The use of this method can significantly increase the service life of power cables, reduce the likelihood of sudden accidents and, as a result, reduce the cost of repair and maintenance of electrical power equipment. Ultimately, improvements in diagnostic and monitoring techniques, including the method of measuring and localizing PD in power lines using OWTS, represent a significant step towards improving the reliability and safety of electrical power systems. This will not only reduce operating costs, but also ensure uninterrupted and high-quality power supply to consumers.

Improvement of Operational Reliability of Units and Elements of Dump Trucks Taking into Account the Least Reliable Elements of the System

The present work is devoted to the analysis of the most important reliability indicators of components of electrical devices of mining dump trucks, and analytical methods of their evaluation are proposed. A mathematical model for calculating the reliability of electrical devices integrated into the electrical systems of quarry dump trucks is presented. The model takes into account various loads arising in the process of operation and their influence on reliability reduction. Optimisation of maintenance and repair schedules of electrical equipment has revealed problems for research. One of them is the classification of electrical equipment by similar residual life, which allows the formation of effective repair and maintenance cycles. The analysis of statistical data on damages revealed the regularities of their occurrence, which is an important factor in assessing the reliability of electrical equipment in mining production. For quantitative assessment of reliability, it is proposed to use the parameter of the average expected operating time per failure. This parameter characterises the relative reliability of electrical equipment and is a determining factor of its reliability. The developed mathematical model of equipment failures with differentiation of maintained equipment by repeated service life allows flexible schedules of maintenance and repair to be created. The realisation of such cycles makes it possible to move from planned repairs to the system of repair according to the actual resource of the equipment.

AC ripple on DC voltage: Experimental and theoretical investigation of the impact on accelerated ageing in electrical insulation

AbstractWith the increasing penetration of DC systems into the high voltage and medium voltage power industry, DC voltage is becoming common for distribution/transmission and to supply different typologies of loads. The allowable extent of AC ripple superimposed to DC, and its effect on insulation ageing, is a long‐term discussed topic. The most harmful phenomenon causing extrinsic ageing acceleration and insulation system premature failure is partial discharges (PD); thus, the risk of incepting PD due to AC ripple could become a primary issue for electrical asset equipment reliability. In this work, the impact of AC sinusoidal ripple on insulation system life and reliability is dealt with, considering both intrinsic and extrinsic ageing but focusing on the latter, that is, the PD aspect. Experiments are performed to assess how the jump voltage (due to AC ripple) and the DC component impact on PD activity in terms of amplitude and repetition rate. For the first time, the correlation between the magnitude of jump voltage associated with ripple and PD inception is established, shedding a light on the allowable ripple extent which does not impact significantly on ageing and premature insulation failure. This approach can provide straightforward tools for design specification and ageing inference of insulation systems.

Прогнозирование состояния плоскостных контактных соединений шин с применением моделей машинного обучения

The article considers the problem of predicting the technical condition of planar contact connections of tires in electrical installations. Modeling methods, including polynomial regression and autoregression, have been studied to assess and predict the state of contacts. The analysis of the results of the models was carried out and their effectiveness was evaluated on various data sets. A program for predicting the condition of contacts has been developed and integrated into the software for monitoring tire contacts. The results of the work show the prospects of creating monitoring systems using forecasting models to ensure the reliability and efficiency of electrical equipment. Keywords: MONITORING, CONTROL, TECHNICAL CONDITION, ELECTRICAL INSTALLATION, CONTACT CONNECTIONS

Development of a Mathematical Model of Operation Reliability of Mine Hoisting Plants

The work analyzes the performance assurance of mine hoisting machines, including the problem of the quality of performance of the functions. The quality of functioning allows evaluation of a set of properties of the process of lifting loads, designed to meet the given requirements in accordance with the purpose and evaluated performance indicators. In this case, the quality of the function depends not only on the elements that worked properly or failed during system functioning but also on the moments involving certain changes in the states of the system. The considered system of power supply of mine hoisting installations is rather complex with respect to reliability. The proposed approach allows this rather complex system to lead in terms of the form of a serial connection of elements, allowing for determining the influence of the functioning of its subsystems and electrical equipment on the technological process of cargo lifting in a coal mine. The presented mathematical concept of increasing the reliability and failure-free operation of mine hoisting plants with the help of the developed mathematical model of the mine hoisting plant allowed studying the reliability indicators of the hoisting plant operation and reserving the equipment most effectively to increase reliability. The determination of coupling coefficients in this study made it possible to analyze the impact of the reliability of electrical equipment and power supply systems on the operation of technological machines to improve the reliability of mining equipment and the efficiency of technical systems of mining equipment.

Magnetic and Thermal Behavior of a Planar Toroidal Transformer

This paper presents a study on the magnetic and thermal behaviors of a planar toroidal transformer, comprising two planar toroidal coils. In our configuration, the primary coil consists of twenty turns, while the secondary coil consists of ten turns. This design combines the advantages of both toroidal and planar transformers: it employs flat coils, akin to those utilized in planar transformers, while retaining a toroidal shape for its magnetic core. This combination enables leveraging the distinctive characteristics of both transformer types. This study delves into electromagnetic and thermal behaviors. Electromagnetic behavior is elucidated through Maxwell’s equations, offering insights into the distribution of magnetic fields, potentials, and electric current densities. Fluid flow is modeled via the Navier–Stokes equations. By coupling these equation sets, a more comprehensive and accurate portrayal of the thermal phenomena surrounding electrical equipment is attained. Such research is invaluable in the design and optimization of electrical systems, empowering engineers to forecast and manage thermal effects more efficiently. Consequently, this aids in enhancing the reliability, durability, and performance optimization of electrical equipment. The mathematical model was solved using the finite element method integrated into the COMSOL Multiphysics software v. 6.0. The COMSOL Multiphysics simulation showed correct behavior of potential, electric field, current density, and uniformly distributed temperature. In addition, this planar toroidal coil transformer model offers many advantages, such as small dimensions, high resonance frequency, and high operating reliability. This study made it possible to identify the range of its optimal functioning.

A hybrid network of NARX and DS-attention applied for the state estimation of lithium-ion batteries

Monitoring the state of the battery, including the state of charge (SOC) and state of health (SOH), is crucial for ensuring the safety and reliability of electrical equipment. The paper presents a novel hybrid network that combines nonlinear autoregressive model with exogenous inputs (NARX) and DS-attention. The proposed DS-attention method establishes a robust mapping relationship between inputs and outputs, it is a specialized method of the recurrent neural network that enhances the estimation performance by incorporating division function and self-adaptive function into the attention mechanism. The division function is designed to efficiently differentiate between exogenous inputs and state outputs, thereby minimizing the potential for cross-interference between them, and the self-adaptive function optimizes the query features within the attention mechanism. The results demonstrate that the hybrid method of NARX and DS-attention achieves higher prediction accuracy for SOH and SOC estimation of lithium-ion batteries. Specifically, compared with the best-performing similar methods, the proposed hybrid method enhanced the prediction accuracy by 22.9%, 60.7%, and 51.2% across three different SOH datasets, respectively. In terms of long sequence SOC forecasting, the improvements in prediction accuracy under two different working conditions are 82.5% and 60.5%, respectively. The proposed algorithm optimizes the attention mechanism based on the characteristics of the NARX, resulting in higher estimation accuracy for predicting the state of lithium batteries.

Automated methods for analyzing and predicting self-oscillations in agricultural systems

The article presents the study of automated methods used for analysis and prediction of auto oscillations in agricultural systems. Auto oscillations arising in control systems and electronics have a negative impact on the reliability of electrical equipment, effective control of the operation of units and systems. The influence of optimization of parameters: frequency and amplitude of auto oscillations, which allow to use effectively technological resources, increase the service life of equipment, reduce the cost of repair and replacement, is shown. The obtained value of the amplitude of auto oscillations can be used to monitor the level of the control signal, also the estimation of amplitude shows the degree of impact on the environment or other components of the system. As a result of research, the automated method for analysis and forecasting of auto oscillations in electric drives is offered, principles and technologies of occurrence of unstable modes are studied, the practical example of application of the method of forecasting of auto oscillations in the technological systems having in structure the electric drive. Methods based on data processing, mathematical modeling and machine learning are used. Particular attention is paid to harmonic linearization for revealing the conditions of occurrence and control of auto oscillations. The proposed methods are based on modern data processing algorithms, artificial intelligence, machine learning and a deep understanding of technological processes. The proposed models and methods ensure the creation of stable and reliable solutions, along with the identification of general regularities, minimizing the influence of random factors, which emphasizes the importance of using the proposed techniques. Automated methods of analysis and forecasting of auto oscillations increase the efficiency of resource use, allow to optimize production processes, and make technological systems of agriculture more resistant to changes in external conditions.

NEURAL NETWORK PROCESSING OF ELECTROMAGNETIC ACOUSTIC SIGNALS TO IDENTIFY THE STRESS-STRAIN STATE AND DAMAGE OF POWER EQUIPMENT

The purpose of the study is to develop and train an artificial neural network to identify the stress-strain state and damage to the metal of power equipment based on the values of the parameters of the harmonic components of the electromagnetic-acoustic transducer signal.
 
 Materials and methods. Experimental study of the relationship between the parameters of the harmonic components of the signal of an electromagnetic-acoustic transducer with the stress-strain state and damage to the structure of standard metal samples, development of an artificial neural network and methods for its training to identify the stress-strain state and damage to the structure of the metal according to the loading diagram.
 
 Results. Analysis of changes in the microstructure and frequency models of standard steel samples used in power engineering confirmed the possibility of identifying the stress-strain state and damage to the structure of metals based on the values of the parameters of the harmonic components of the electromagnetic-acoustic transducer signal. To solve this problem, an artificial neural network has been developed and trained. After training, the effectiveness of the network in identifying the stress-strain state and damage to the structure of metals reached 92.16%, which is acceptable for the tasks of recognizing the technical condition of metal structural elements of electrical installation equipment.
 
 Conclusions. The use of an artificial neural network to identify the stress-strain state and damage to metal structures based on the harmonic parameters of the electromagnetic-acoustic transducer signal enables to identify areas of concentration of mechanical stress and damage to the metal structure at the early stage of development, thereby increasing reliability and safety operation of electrical equipment.

Results of a statistical study of types of single-phase faults in low-voltage ship electrical networks

The increase in the power supply of ships is manifested in growth of ship power plants' capacity, the total length of cable lines, and the number of electrified mechanisms. With the development of marine technology, the severity of the consequences of damage to ship electrical equipment and the costs of its maintenance and repair increase. The search for ways to improve the reliability and safety of electrical equipment should be based on design and technological solutions at the stages of its development and production, as well as an analysis of various factors that may appear during the operation of marine equipment and affect the condition of ship electrical systems. During studying these factors, it has been revealed that one of the common types of damage to electrical equipment of marine equipment is single-phase short circuits, the causes of which are varied. Preventing short circuits is labour intensive and in some cases impracticable. However, understanding the characteristics of this type of damage to low-voltage equipment is necessary to improve the reliability and safety of ship electrical systems. The conducted research is based on a survey of ship electrical mechanics. The results of the surveys have made it possible to analyze the frequency of occurrence of single-phase insulation faults, the duration of their existence, to identify the most likely places of occurrence of short circuits and equipment that is more susceptible to such damage compared to other elements of the electrical power system.

Methods for assessing the reliability of in-shop power supply

Research activities in the field of development of electrical power and electrical equipment include the development of new approaches to assessing the reliability indicators of electrical equipment elements and in-house power supply systems in general. The study has examined methods for assessing the reliability of electrical equipment in intra-shop power supply systems using the example of a workshop network section, including its main elements: power transformer, low-voltage cable lines, distribution points, circuit breakers, magnetic starters, contactors, switches. The reliability parameters of the circuit are calculated relative to the distribution cabinet of the power (DCp) and the distribution point of the power (DPp); regarding each connection of DCp and DPp. The methods under consideration are recommended to be used to clarify the frequency and timing of maintenance and repairs of electrical equipment of the in-shop power supply system, as well as to analyze the reliability of operation and identify the least reliable sections of network diagrams. The presented calculation using the logical-probabilistic method by constructing a fault tree is advisable to use to estimate the frequency of power loss of DCp and DPp, as well as individual connections. For the studied circuits, graphical dependences of the probability of failure-free operation of electrical equipment and the occurrence of a failure over time have been constructed.

Lithium Battery State-of-Health Estimation Based on Sample Data Generation and Temporal Convolutional Neural Network

Accurate estimation of battery health is an effective means of improving the safety and reliability of electrical equipment. However, developing data-driven models to estimate battery state of health (SOH) is challenging when the amount of data is restricted. In this regard, this study proposes a method for estimating the SOH of lithium batteries based on sample data generation and a temporal convolutional neural network. First, we analyzed the charge/discharge curves of the batteries, from which we extracted features that were highly correlated with the SOH decay. Then, we used a Variational Auto-Encoder (VAE) to learn the features and distributions of the sample data to generate highly similar data and enrich the number of samples. Finally, a temporal convolutional neural network (TCN) was built to mine the nonlinear relationship between features and SOH by combining the source and extended domain data to realize SOH estimation. The experimental results show that the proposed method in this study has less than 2% error in SOH estimation, which improves the accuracy by 64.9% based on its baseline model. The feasibility of using data-driven models for battery health management in data-constrained application scenarios is demonstrated.

APPLICATION OF COLD-CURING SILICONE COATING ON ENERGY FACILITIES IN UKRAINE

The choice of preventive measures as one of the ways to ensure the reliability of electrical equipment in areas with a polluted atmosphere is based, first of all, on the experience gained in similar conditions. One of these measures is applying an RTV coating (a cold-curing silicone coating) to the insulation. The article analyzes the latest publications on developments in the direction of applying RTV coating. Summarized information on the use of RTV coating in Ukraine. Recommendations for improving the convenience and productivity of coating in "field conditions" (that is, at active energy facilities) are given, which have been tested on our own experience. Factors inhibiting the application of RTV coating on linear insulation are identified. The effectiveness of using RTV coating in areas with both highly soluble and cement-like contaminants has been proven.

Power Quality Improvement using Shunt Active Power Filter: An Industrial Zone Case Study

Power quality (PQ) improvement using active power filters (APF) is a topic of growing interest. APFs are effective in reducing harmonic distortion and improving power factor. They can be used in a variety of applications to improve the performance and reliability of electrical equipment. To address concerns with PQ improvement, this study offers an application of shunt APF in an industrial zone smart grid. the non-linear loads and unpredictable harmonics produced by on-grid PV inverters that represent the architecture of an industrial smart grid. Utilizing the MATLAB/SIMULINK software suite, a detailed design of the APF and associated hysteresis current control technique is provided. The findings demonstrate that APF is a useful tool for reducing total harmonic distortion (THD) and has a quick dynamic reaction to control grid voltage and power factor.

Dynamic Cross-Linked Polyethylene Networks with High Energy Storage and Electrical Damage Self-Healability.

Dielectric polymers that exhibit high energy density Ue, low dielectric loss, and thermal resistance are ideal materials for next-generation electrical equipment. The most widely utilized approach to improving Ue involves augmenting the polarization through increasing the dielectric constant εr or the breakdown strength Eb. However, as a conflicting parameter, the dielectric loss also increases inevitably at the same time. In addition, due to the long-term work under a strong electric field or high potential, dielectric materials often produce electrical damage (electrical tree), which is one of the main factors affecting the reliability and service life of electrical equipment. To address these problems, we herein develop dynamic cross-linked polyethylene materials (PE-MA-Epo) by polyethylene-graft-maleic anhydride (PE-MA) and polar epoxy monomers, which showed high εr (>7), low dielectric loss (<0.02), high Ue (5.16 J/cm3 at 425 MV/m), and outstanding discharge efficiency (97%). The performances of the materials are adequate to rival biaxially oriented polypropylene (BOPP) films. Moreover, the excellent self-healing capability of PE-MA-Epo enables the total recovery of εr and tan δ after electrical tree healing. After two cycles of electrical breakdown healing, Eb remained at 80%, which improves the durability and reliability of dielectric polymers. Therefore, PE-MA-Epo shows great potential for applications in advanced electronic power devices.

Analytical method of identifying the type of defect of oil-filled equipment according to the results of analysis of gases dissolved in oil

Purpose. Development of a method for recognizing the type of defect of oil-filled equipment based on the results of the analysis of gases dissolved in oil. Methodology. Analysis of gas ratio values in oil-filled equipment with various types of defects, synthesis of a method for recognizing the type of defects. Findings. A description of the analytical method for recognising the type of defects in oil-filled equipment based on the results of the dissolved gases analysis is given. To recognise the type of defect, the values of three ratios are used: CH4/H2, C2H4/C2H6, and C2H2/C2H4. Using these ratios, 40 different types of defects and their combinations can be recognised. These defects correspond to 25 different ranges of gas ratios obtained as a result of gas content studies for 3715 units of oil-filled equipment The type of defect is determined by analysing the obtained gas ratio values and classifying them according to the ranges of gas ratios for each fault. In the case when the obtained ratio values correspond to several types of faults in the same range, characteristic nomograms of defects and recommendations according to the key gas method are used to clarify the type of fault. A comparative analysis of the reliability of fault type recognition using the developed method and some well-known methods for interpreting the results of dissolved in oil gases analysis was performed. Originality. An analytical method for recognising the type of faults in oil-filled equipment of electrical networks based on the results of the dissolved gases analysis is proposed. This method differs from the existing ones in that, when using three known gas ratios, it allows recognising a larger number of defects of different types (40), including those for which the known methods do not allow establishing a diagnosis. This result is ensured by the use of 25 ranges of gas ratios obtained from the results of gas content studies for 3715 units of oil-filled equipment. Practical value. The use of the developed method for recognising the type of faults in oil-filled equipment of electrical networks allows increasing the reliability of defect recognition based on the results of dissolved gases analysis. This, in turn, makes it possible to increase the operational reliability of electric power equipment and extend the service life of this equipment.

DEVELOPMENT OF A COMPREHENSIVE APPROACH TO DIAGNOSING THE OVERHEAD LINE FAULTS LOCATION IN SINGLE-PHASE GROUND FAULTS BASED ON A DIGITAL SUBSTATION DATA PROCESSING ALGORITHM

Link for citation: Sushkov V.V., Sukhachev I.S., Sidorov S.V. Development of a comprehensive approach to diagnosing the overhead line faults location in single-phase ground faults based on a digital substation data processing algorithm. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 66-77. In Rus. Relevance. Emergency of electric complex of outgoing transmission lines is associated with the occurrence of damage to the line isolation and the resulting transients, marked by the presence of higher harmonic components of currents and voltage, which reduce the reliability and energy efficiency of electrical equipment of oil and gas companies: degrade the mechanical characteristics and efficiency of electric motors, accelerate aging of their isolation, disrupt the operation of control systems and emergency automatics, fault diagnostics systems. One of the reasons of high-level emergency situations, outages and emergency repairs in electric complexes of outgoing transmission lines of oil and gas companies is appearance of phase-to-ground faults. A large number of changing factors are known to influence the reliability of phase-to-ground fault location methods: parameters of transmission line operating mode, its structural and electrical parameters, fault type, transient resistance value, ground resistance and others. Inclusion in the transmission line fault location algorithms of averaged values of a number of the factors listed above independent of changes of humidity of soil and air, its temperature and other factors causes an error of methods of fault location up to 30 %. Accordingly, the research to develop a fault location method for overhead transmission lines with isolated neutral points during phase-to-ground faults based on a digital substation data processing algorithm, accounting for tower parameters and natural-climatic factors, is relevant. Objective: improving the reliability of power grids and providing consumers with power of the required standard by applying a digital fault location system to the outgoing transmission lines electrical complex. Methods: mathematical analysis of a power transmission line, taking into account its design features and natural-climatic factors on the basis of the method of mirror images; mathematical analysis of steady-state and transient modes of transmission line operation considering self and mutual parameters terms of wires; transmission line currents and voltages Fourier analysis; validation of developed method of phase-to-ground fault location in power grid of Tyumen region energy company. Results. The authors have developed the phase-to-ground faults location method for transmission lines in power grids with isolated neutral points, which differs in the following – first the faulty overhead line feeder branch is identified by correspondences between the negative sequence voltage values of the phase voltages at the transformer substation inputs, and then the distance to the location of the single-phase ground fault is determined along the branch line based on the resonant frequencies of the line taking into account its design features and natural and climatic factors.

Mathematical Analysis of the Reliability of Modern Trolleybuses and Electric Buses

The rhythmic and stable operation of trolleybuses and autonomous trolleybuses or urban electric buses, depends to a large extent on the reliability of the equipment installed on the trolleybus. The actual operational reliability of trolleybus electrical equipment (EE) depends on its technical condition. Under the influence of external factors and specific operating modes, the technical condition of the equipment is continuously deteriorating, reliability indicators are decreasing, and the number of failures is increasing. Using the mathematical theory of reliability, probability theory and mathematical statistics, numerical methods of solving nonlinear and transcendental equations, this article defines the conditions of diagnostics depending on the intensity of failures and the given probability of failure-free operation of the equipment. Additionally, the inverse problem of determining the current reliability of electrical engineering systems depends on the terms of diagnostics and the intensity of failures being solved. As a result of the processing of statistical information on failures it is established that for the electrical equipment of a trolleybus, after a number of repair measures, the maximum density of failures occurs at a lower mileage, and the probability of failure-free operation can vary depending on the degree of wear of the equipment, i.e., on the number of previous failures. It is theoretically substantiated and experimentally confirmed that the reliability of trolleybus electrical equipment changes according to the exponential law of distribution of a random variable. It has been established that the real averaged diagnostic terms regulated by instructions are not optimal in most cases and differ several times from those defined in this paper. The dependence of switching equipment run-in on time has been clarified, which served as a prerequisite for specifying the inter-repair period for various types of trolleybus electrical equipment. A method of adjustment of the inter-repair time for the electrical equipment of trolleybuses is proposed.