Preventive Maintenance System Research Articles

Метод оценки факторов, влияющих на вибрацию судового дизеля, вызванную работой цилиндропоршневой группы

The efficiency of the use of the marine fleet is associated with a reduction in the cost of transportation, the need for which is steadily increasing. A significant share of the total transportation costs is occupied by the costs associated with the operation of ships, therefore, reducing these costs is a reserve for reducing the cost of maritime transportation. The problem of increasing the efficiency of the operation of marine vessels is closely related not only to reducing the cost of it, but also to reducing the time for maintenance and repair of ships. The existing system of scheduled preventive maintenance and repair provides for the maintenance and restoration of the normal technical condition of the vessel and its elements with a pre-planned frequency. The transfer of ships to work with extended repair periods is possible only when solving a whole range of engineering and technical measures and scientific research aimed at improving the quality of repairs, the level of technical operation, improving logistics, etc. An essential role in this is played by the use of modern methods and means to determine the technical condition of shipboard devices and mechanisms, primarily engines of shipboard power plants (SEUs), without disassembling them. High vibration loads of SEU parts lead to fatigue stresses, accelerate wear of the contacting surfaces, reducing the reliability and service life of marine diesel engines, therefore monitoring of their vibration activity is important, especially during operation. The safe operation of ships of the transport fleet largely depends on the reliability of marine diesel engines. Technical means of monitoring their operability in the process of work are currently insufficiently effective and need to be improved. It is relevant not only to develop new, more advanced and mobile hardware and software, but also to search for new scientific and methodological approaches to using the information contained in the spectrum of vibration parameters. Marine diesel internal combustion engines are complex systems that involve many variable parameters. The study of such engines requires the use of methods that can be used to systematically investigate the influence of various factors on their operation, in particular, random experimental schemes are used, since they provide systematic control over variable parameters and maximize the accuracy of estimates. The results of the application of the method of ranking the factors influencing the vibration of a marine diesel engine are presented in order to establish the most significant of them. A mathematical model is presented that allows calculating current values and predicting changes in the most significant indicators, among which the most important is the size of the gap between the piston and the cylinder sleeve.

The mechanism for improving the management of the maintenance and repair process using neural network technology

The system of preventive maintenance for various types of equipment is considered. To identify the need for managerial influence on the processes of maintenance and repair of the product, the coefficient of variation of the maintenance (repair) cycle is proposed. This coefficient is formed by the values of operating time or work between stops for maintenance or repair. To determine its numerical value, it is recommended to use such concepts as "maintenance (repair) cycle" and "frequency of maintenance (repair)". The values of the coefficient characterizing the stability of the process of repair and maintenance of the product are determined. These values of the coefficient are proposed to be used to justify the need to analyze the causes of failures or, in other words, the instability of the repair and maintenance process. The main managerial influences on the process of maintenance and repair are determined, which can be taken as a result of the analysis of the causes of failures. These include: the decision to search for a technical service provider, expanding the competencies of employees, updating the material base. Modern industry 4.0 tools allow you to get the required level of quality when working with a large data stream. The use of neural network technology in various technical service management tasks is due to some advantages over classical methods of statistical processing of results. The experiments of various authors are presented in which it is shown that neural network technologies are able to interpret graphic information, justify its use in technical diagnostics at the stage of analyzing diagnostic information in the form of oscillograms, which allows the use of complex diagnostic equipment in the absence of experts. A neural network simulation was carried out to recognize defects in bearing assemblies. As a result, the created neural network recognized the type of defect in accordance with the matrices of input signals and the output matrix of types of defects, which makes it possible to develop a mechanism for improving technical service using neural networks as a tool for analyzing diagnostic information in the absence of experts in this field.

Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System

The share of wind energy in the energy mix is continuously increasing. However, a very important issue associated with its generation is the high failure rate of wind turbines. This situation particularly concerns large wind turbines, which are expensive and have a lower tolerance for system damage caused by various failures and faults. Vulnerable components include sensors, electronic control units, electrical systems, hydraulic systems, generators, gearboxes, rotor blades, and so on. As a result, significant emphasis is placed on improving the reliability, availability, and productivity of wind turbines. It is extremely important to detect and identify abnormalities as early as possible and predict potential failures and damages and the remaining useful life of components. One way to ensure turbine efficiency is to plan and implement preventive repairs. This work shows a semi-Markov model of a preventive maintenance system based on Enercon E82-2 wind turbines. The system’s performance quality is evaluated based on profit over time and an asymptotic availability coefficient. The developed model establishes formulas describing the efficiency functions and formulates the conditions for the existence of extremes (maxima) of these functions. Computational examples provided at the end of the paper illustrate the obtained research results. A preventive maintenance model is developed that can be applied to wind turbine hazard prevention (determining optimal times for wind turbine preventive maintenance).

PWHT 대체 원자로 냉각계통 예방정비를 위한 와이어 아크 적층 제조를 통한 용접부 상분율 제어

PWHT 대체 원자로 냉각계통 예방정비를 위한 와이어 아크 적층 제조를 통한 용접부 상분율 제어

Refined evaluation methods for preventive maintenance of project-level asphalt pavement based on confusion-regression model

Accurate evaluation of the performance of airport pavement can help managers make scientific and systematic preventive maintenance (PM) decisions, ensuring pavement safety and extending service life. To this end, firstly, this paper sorted out the pavement performance evaluation index system, based on which a multi-dimensional evaluation system for PM was proposed, including control indexes, macroscopic indexes, and microscopic indexes. Then, the pavement decay model based on the pavement condition index (PCI) was developed, and the regression model between PCI and International roughness index (IRI) and friction coefficient (μ) was established. Finally, by converting the PM decisions for project-level pavement into a binary classification problem in machine learning, the optimal maintenance thresholds and intervals for PM of each index were determined using receiver operating characteristic (ROC) curve and Kolmogorov-Smirnov (K-S) curve. The optimal threshold represents the threshold when the index can separate the binary classification problem (PM decisions) with maximum probability. Based on confusion-regression model, the pavement performance can be evaluated more comprehensively, and the timing of PM can be accurately determined. The model helps airport managers develop accurate PM plans to address future maintenance needs.

Perencanaan Preventive Maintenance Pada Bengkel Mekanik SMKN 2 Pangkalpinang

Preventive maintenance is an activity to maintain the condition of the machine that is carried out in a planned/scheduled manner. Preventive maintenance itself includes scheduling, implementation, and improvement/modification. The purpose of this research is to carry out preventive maintenance on machine tools to maintain optimal engine conditions, ensure machine availability and reduce maintenance costs to a minimum. The preventive maintenance system design method is based on machine condition data collected by observing related machines and interviewing informants at SMKN 2 Pangkalpinang. Data from observations and interviews were used to calculate and determine the value of machine complexity so that a lathe maintenance system was obtained in the form of preventive maintenance design schedule data, annual preventive maintenance schedules, work specifications, and control cards. The results showed that the recommended preventive maintenance system design was acceptable to be implemented on lathes at SMKN 2 Pangkalpinang within 2 years. Further research is needed to increase the effectiveness of this preventive maintenance system. Some things that need to be further developed include a system for managing materials and machine parts inventory and changing engine oil using the oil listed in the lubrication table.

Experimental test of a building thermal system for preventive maintenance based on thermoeconomic analysis

An analysis of the sectorial structure of energy consumption shows that residential and tertiary sector buildings are the third-highest consumers, responsible for 29.5% of a city’s final energy consumption. The Building Quality Control Laboratory of the Basque Government aims to promote quality, innovation, and sustainability in buildings. To accomplish this goal, it has constructed an experimental facility with different energy generation technologies and a very versatile control system for testing different energy systems and operation modes. In this study, we tested a facility for supplying domestic hot water and heating for a multi-family house by means of a condensing boiler and an aerothermal heat pump (together with the corresponding control). This installation could reproduce the thermal demands required to be satisfied by the generation equipment through a programmed operation of the installation based on real demands. Additionally, this installation was analyzed using thermoeconomics (TE) to solve problems unable to be solved using traditional energy analyses based on the First Law of Thermodynamics. These problems include: (1) Determining the costs of the products of the installation based on physical criteria, (2) detecting the places where losses actually occur, evaluating their costs, and proposing cost-effective improvements, and (3) diagnosing issues in the installation. As a result, this paper suggests a solution to the preventive maintenance problems confronting the technical maintenance personnel for thermal installations in buildings by applying TE knowledge and using real data collected from sensors.

Appraisal of injection molding systems: A statistical approach

The deployment of statistical process control (SPC) in manufacturing environments is a prominent global phenomenon. Statistical Process Control is largely used in industries for monitoring the process parameters. It is a standard method for visualizing and controlling processes on the basis of measurements of randomly selected samples. SPC was used to evaluate the quality of production of five sample products from Injection mould system for years 2012 and 2014. This paper presents a rapid method for quality appraisal using Statistical Process Control to analyse quality of production during corrective and preventive maintenance of Innoson Injection mould system. SPC was used to visualize and control processes of the Injection mould system for 2012 and 2014 on the basis of measurement of randomly selected sample of five product. SPC used mean, standard deviation and range to detect variations in the process so that it can be controlled. SPC was used to evaluate the quality of defective production during corrective maintenance in 2012. Quality of defective production during preventive maintenance in 2014 was also monitored and analysed. The data collected from the production personnel was used to adjust the process to achieve the desired results. Those results were dependent on customer requirements, efficiency, quality, and reliability. Statistical Process Control (SPC) is a powerful collection of problem-solving tools useful in achieving manufacturing process stability and improving capability through the reduction of variability. Charts were used to determine the actual capability of production process, guide modifications for improving the output quality of process, and monitor the output. The monitoring function shows the current status of output quality and provides an early warning of deviation from quality goals. The key to quality is to detect when the process goes out of control so that we can correct the malfunction and restore the control of the process. SPC in 2012 during corrective maintenance of the system, shows out of control reflecting excessive defective products. While SPC, in 2014 during preventive maintenance of the system, shows in control for the X, S and R charts, depicting reduce defective products. In this paper need of SPC to analyse quality of production during corrective and preventive maintenance of Innoson Injection Mould system, by SPC as a quality control tool is discussed.

Situation analysis of locomotive reliability on the Far Eastern railway

Under the operating conditions of the locomotive fleet, a preventive maintenance and current repair system for locomotives is used, on the basis of which reliability is managed by regulating the norms of overhaul runs. Regulation of the norms of overhaul runs is carried out to optimize the risks of failure of locomotives along the route, thus the system for managing the reliability of the locomotive fleet is arranged. The conditions for regulating the norms of overhaul runs of locomotives are limited by the internal regulations of the monopoly company (JSC Russian Railways) and take discrete values of no more than 20 % of the established values. Often, the regulation of the norms of overhaul runs of locomotives is carried out only in the direction of increase due to attempts to reduce the cost of maintenance and repair. However, this approach does not take into account the possibility of increasing costs due to the consequences of a failure along the route and unscheduled repairs, which characterizes the lack of accountability in making such a decision, which is undoubtedly an urgent problem for the locomotive complex.The article presents the statistics of failures of locomotive units for enlarged groups of equipment according to the form TO-15 “Report on unscheduled repair of locomotives” for the Far Eastern Railway and uses methods for situational analysis of locomotive failures.As a result of a situational analysis of locomotive failures, limiting (overhaul run norms) groups of locomotive units were established, the stages for resolving the issue of the lack of accountability of decisions made under the conditions of optimization of locomotive run overhaul norms were determined.The value of the results obtained lies in the possibility of improving the system for managing the reliability of locomotives — the system of maintenance and repair in the field of decision-making on the gradient of optimizing the norms of overhaul runs.

Renewable k-Out-of-n System with the Component-Wise Strategy of Preventive System Maintenance

At the SMARTY-22 conference, a review of the regenerative methods development was presented, including its application to the study of a non-renewable k-out-of-n system. This paper develops the previous study for the renewable k-out-of-n system, including an investigation different preventive maintenance strategies based on the system state observation. We also include the review of Smith’s regeneration idea development. Some new results are presented that form the basis for an algorithm for comparing preventing maintenance strategies with respect to the maximization of the availability factor. A numerical study was conducted for the 4-out-of-6 and 4-out-of-8 models. The study demonstrates the sensitivity of decision making to the shape of the repair time distribution.

Forecasting the technical condition of hydraulic transmissions of agricultural machines based on kinematic viscosity and pressure indicators of oil

Maintenance of the technical condition of hydrostatic transmission of agricultural machines is not fully provided by the existing repair and maintenance system of Ukraine, which determines the search for available methods for early detection of hydraulic drive malfunctions. The purpose of the study was to synthesise a method for predicting the technical condition of the hydraulic transmission of modern agricultural machines by controlling the dynamics of changes in the values of the empirical dependence of pressure on the kinematic viscosity of oil in conditions of insufficient material and technical equipment of the production base. Generally accepted methods were applied to achieve this goal: analysissynthesis, induction, observation, experiment, graphic method. As a result of the study, the author’s hypothesis was confirmed, according to which the change in the kinematic viscosity of the working fluid relative to the initial value is determined by the current state of the hydraulic transmission, which is controlled by pressure measurement. Based on the identified shortcomings and problems of the current system of maintenance and repair, a methodology was proposed that provides for monitoring the operational indicators of agricultural machines and the kinematic viscosity of working fluid samples taken from their hydraulic transmissions. Kinematic viscosity values for constructing the predictive model were obtained by the capillary method and calculated using the Walter formula, and the dependence of viscosity on influencing factors was determined by bilinear interpolation. A regression model of pressure from kinematic viscosity was obtained by the least squares method, and the exponent was used as an approximating function. Based on the results of testing the models according to the Fischer criterion, their adequacy was confirmed, and the deviation of the theoretical values of the controlled parameters calculated using the most accurate model from the empirical ones was 0.34% for pressure and 1.3% for kinematic viscosity. The practical value of the study lies in the fact that the results allow reducing unproductive time costs associated with the downtime of equipment, due to emergency failures of hydraulic transmission units and contribute to the adaptation of the planned preventive maintenance system for agricultural machinery to the needs of the Ukrainian agro-industrial complex

FORMALIZATION OF ELECTRIC TRAIN REPAIR COMPONENT LIFE CYCLE ASSESSMENT

The article deals with the issue of the mathematical description of the repair component of the life cycle of the EPL9t electric train. At present, the development and use of the concept of the life cycle of traction rolling stock of railway transport is given considerable attention by both equipment manufacturers and its users. For Ukrainian railways, this scientific direction is especially relevant due to the fact that traction rolling stock is significantly worn out both physically and morally. This necessitates the rapid renewal of railway equipment through the acquisition of samples of domestic or foreign production. The feasibility study for choosing an alternative option for updating technology in world practice is based on the concept of the life cycle. The life cycle of an electric train covers a significant period of time. It includes both repair and operational components. The repair component is associated with carrying out technological measures to maintain it in a technically sound condition and periodically renew its original technical characteristics. This is facilitated by a system of scheduled preventive repairs. The determining factors in this case are the durability and maintainability of equipment. The results of forecasting long-term investment projects for the renewal of railway equipment depend on how accurately the technical and economic assessment of this component is given. The mathematical description is based on the standards of the preventive maintenance system for the repair of traction rolling stock of Ukrainian railways and, in particular, the electric train of the EPL9t series. The analysis of the operational factors of the use of the electric train, influencing the formation of the repair component of the life cycle, was carried out. A feasibility study using the proposed mathematical approach quite accurately estimates the repair component of the life cycle. The economic assessment of the repair component of the EPL9t series electric train was made according to the conditions of a specific route served by it during the life cycle. The results obtained will be used in the future to develop a complete mathematical model of the life cycle of an electric train.

Forecasting the Residual Life of Wheelsets of 81-740/741 «Rusich» Cars of the Metro Electric Trains

A modern approach to determining the useful life of components and parts of rolling stock allows not only to estimate the pre-failure state of an object, but also to predict its useful life.The objective of the study is to predict the mileage of wheelsets of modern electric trains of the «Rusich» series based on the use of statistical data and assessment of the residual life.The study used real data recorded during maintenance and repair of electric trains.The proposed approach allows getting a vivid presentation of the equipment wear rate, since it is based on the use of the measured parameters of the object. The analysis of these values makes it possible to determine the processes occurring in the product. When using large samples, it becomes possible to approximate the obtained numerical values and make a forecast of the technical condition with greater reliability.The task of predicting the residual life is quite complicated and must be solved separately for each type of equipment. That is why the generally accepted world practices are associated with preventive maintenance and repair system, while modern automated digital systems for technical diagnostics (including on-board and built-in ones) make it possible to partially switch to technical maintenance and repair considering the actual technical condition of the rolling stock.

Portable motorized telescope system for wind turbine blades damage detection

AbstractWind turbines are among the fastest‐growing sources of energy production and the maintenance operations include regular inspection of their blades, causing considerable downtime and cost. In addition, the manual inspection process involves a great risk. To address this challenge, in this article a preventive maintenance system for wind turbines based on deep computational learning techniques is presented. This open‐source project aims to detect and classify possible surface damages on wind turbine blades to facilitate and improve the inspection of such infrastructures. The system consists of a stand‐alone Android application that makes use of convolutional neural networks for image processing, a portable telescope to take precise photographs of the turbine blades, and a motorized mount that allows the movement of the telescope. The application tries to carry out a complete sweep of the surface of the wind turbine blades in an autonomous way based on the predictions of neural network models and finally presents the defects found to the user. Thanks to this, maintenance time would be reduced and the risk of manual intervention would be avoided. Accuracies of around 97% for label predictions and 90% for bounding box coordinate predictions have been achieved on the validation dataset. The proposed low‐cost inspection system for detecting surface damages on blades has been experimentally validated in a real wind farm.

A New Integrated Risk-Assessment Model for Minimizing Human-Machine Error Consequences in a Preventive Maintenance System

In this paper, a risk-assessment model for minimizing human-machine error consequences during the implementation of preventive maintenance tasks has developed. The developed model aimed to find the optimal preventive maintenance interval (PMI) and corresponding minimum risk consequences costs per unit of time. Based on expert judgment, a human error probability (HEP) model was developed using the success likelihood index methodology (SLIM). In addition, we developed a system failure probability (SFP) model based on the failure and repair data of the system. The HEP model was integrated with an SFP model to develop a human-machine error model. Then, the risk-assessment model was developed based on the consequences of system failure and human error. The effectiveness of the developed human-machine error model was shown by applying a numerical example for a multi-component series system. The optimization toolbox from MATLAB R2022b was applied to solve the developed human-machine model. The results showed that the optimal PMI can be implemented after 24 working hours to 105 hours under the acceptable limit of risk in the system which is 100 SR/h. Finally, the developed model is an effective method that can be applied to a wide range of manufacturing systems to minimize financial risks related to system inspection and maintenance while meeting safety and availability requirements.

MODERN TRENDS IN TECHNICAL CONDITION MONITORING SYSTEMS OF HYDRAULIC DRIVES IN AGRICULTURAL MACHINERY

Increasing technical complexity of hydraulic systems in modern agricultural machines causes a low level of their maintainability in the domestic agro-industrial complex. In order to avoid unforeseen financial costs associated with equipment downtime due to emergency failures of their hydraulic drives, there is a need to identify the prerequisites for their efficiency loss in advance by using effective methods and means of monitoring the technical condition of machines in operation. The aim of the article is to analyse the applicability of methods for monitoring the technical condition of hydraulic drives in agricultural machinery and to substantiate the prospects for their improvement, in accordance with the level of modern information technology development and the conditions of the material and technical base of the domestic agro-industrial complex. To achieve this goal, a structural, logical, and comparative analysis of materials from periodicals and electronic information sources on the relevant topics was conducted. The article considers the known methods for diagnosing hydraulic drives and trends in improving the means of monitoring the technical condition through information technology. The study showed that the methods of the non-destructive testing group are the most applicable in conditions of weak material and technical base. Among the existing methods aimed at improving the process of monitoring the technical condition of agricultural machinery are remote diagnostic systems that combine the diagnostic parameters reading and their remote processing on electronic computers. Currently, artificial neural networks are being actively developed, which are finding their way into the monitoring hydraulic drive technical condition and can significantly improve the overall level of the planned preventive maintenance system.

EVALUATION OF THE EFFICIENCY OF USING A MIXED SYSTEM OF MAINTENANCE AND REPAIR OF ROAD VEHICLES OF ROAD TRANSPORT

The article argues the relevance of determining the efficiency of the mixed system of maintenance and repair of road vehicles. Improving the system of maintenance and repair of road transport is one of the main ways to increase the efficiency of motor transport enterprises. This is due to the high growth rate of work performed, the significant complexity of the design of modern vehicles and the variety of implementation of new maintenance strategies and diagnostic methods. Significant complications in the design of components and units of modern road vehicles, increasing their functions, more busy modes of operation of components, units, etc. - significantly exacerbated the problem of traffic safety, which is largely due to the quality of maintenance and repair. The urgent need to improve the system of maintenance and repair is due to changes in the technical condition of automotive equipment and the requirements for maintaining the working condition of vehicles during operation. An analysis of existing maintenance and repair strategies has shown that each has its advantages and disadvantages. The combination of advantages of each strategy and elimination of shortcomings will lead to the creation of a mixed system of maintenance and repair, which along with high-quality staffing of repair companies and equipping them with modern diagnostic equipment will increase the readiness of road vehicles, technical efficiency and efficiency quality of operation, reduce maintenance and repair costs at a given level of reliability. © О. М. Рікунов, В. І. Кужелович, 2022 Keywords: road transport vehicles, maintenance and repair system, preventive maintenance system, average total duration of maintenance and repair, technical readiness coefficient, technical utilization coefficient, economic feasibility

A Scoping Review of Pipeline Maintenance Methodologies Based on Industry 4.0

The fourth industrial revolution was a milestone at the industrial level. It forced most industries to evolve technically and for their collaborators to prepare and advance together with technology; the oil industry was no exception. It develops its activities in dangerous and dynamic environments and needs to protect its human resources, equipment, and infrastructure. This article presents a scoping review, based on the PRISMA guidelines, of pipeline maintenance methodologies based on Industry 4.0. From the first collection of 123 articles from prestigious databases such as SpringerLink, MDPI, Scopus, IEEEXplore and ACM, a final sample of 31 articles was obtained. Here, technologies that enhance preventive and predictive maintenance systems are discussed. The results show that predictive maintenance compared to preventive maintenance has a percentage difference in upkeep time optimization of 38% in the last five years. This difference was corroborated with a Student’s t-test for independent samples, with a significance of 0.023. Likewise, the most used technologies were analyzed, with artificial intelligence standing out with 45.16%.

Additive manufacturing process design for complex aircraft components

The process of metal additive manufacturing (AM) is now widely used in fabricating complex parts in today’s industry. The scope of this paper is to redesign a manufacturing process for complex aircraft components using wing ribs as example by considering embedded Internet of Things (IoT) sensory capability that can be used in an Industry 4.0 ecosystem for moving away from a condition-based preventive maintenance system to a data-driven predictive maintenance-based system. This work is based on a previous study that considered the part design stage which deals with finding the best design solution for a single part. Considering a wing rib geometry of 3-mm web thickness with 6-mm upper and lower caps, the manufacturing process is designed and assessed using the Simufact Additive™ software. The use of AM when embedding IoT sensors allows more flexibility without compromising the structural integrity of parts, as well as the advantage of design freedom and limited cost when modifying geometries. The outcomes show that the manufacturing process depends strongly on hot isostatic pressing (HIP) for the wing rib, but for the sensory covers it presented no significant improvement. The results also show that the support optimisation can lead to an important reduction of mass and volume as well as an improvement of the structural performance.

Математическая модель расходных характеристик паротурбинных установок

A large number of generating equipment installed at thermal power plants (TPPs) operate at the limit of their fleet life resource or beyond it. Malfunctions and defects occur during the entire period of operation of steam turbine plant (STP) of TPPs. It causes performance degradation of efficiency, reliability, and maneuverability of STP. Thus, the methods to provide monitoring over the technical position of the elements and/or functional units of steam turbine plant are to be applied. Hence, special attention is to be paid to the development of methods to monitor the technical position and diagnostics of generating equipment of TPPs. The methods are based on a mathematical model of flow characteristics of steam turbine plants. It allows us to consider the effect of changes in the open flow area of the individual compartments of a steam turbine on the pressure distribution over the flow path. To develop the model, the authors have applied mathematical modeling methods and the balance relations of mass and energy methods. The solution of the equations of the obtained linear and nonlinear systems is carried out by methods of computational mathematics. Calculation of thermodynamic parameters of the coolant is carried out based on tables of properties of water and water vapor and software for their description. A mathematical model of a steam turbine plant has been developed. It represents a set of linear and nonlinear algebraic equations that consider the flow discharge characteristics of the steam turbine compartments. Also, it makes possible to assess the technical position and it considers the effect of defects on the pressure distribution over the flow path of the steam turbine. The results of the statistical analysis prove that the model has been recognized adequate under the variation range in the electrical load. The results of the development of mathematical steam turbine plant model can be used to develop intelligent systems to monitor and diagnose power generating equipment of TPPs. Application of these systems allow the management of the TPP to change over from the system of preventive maintenance of equipment to the system of the repair of equipment according to technical position.