Система непрерывного мониторинга технического состояния и оперативной диагностики паровой турбины

BWR steam line and turbine model with multiple piping capability

Prior to the initial steam admission to 1,000MW steam turbine in a thermal power plant after its construction, the turbine control system was verified by using a process model developed based on the heat balance and actual process operating data of same type thermal power plant. The total system where the process model was integrated into the controller hardware with input and output modules is generally called verification system. Unlike a widely used simulator composed of only personal computer and software in the laboratory, this verification system have a great difference which can be connected with actual speed control system and field devices by use of actual signal lines. So, if it is used for verification of control system and field devices immediately before steam turbine start up, though there is no steam from boiler to turbine, the field adaption test cab have a very similar result because the steam control valve in the field can be actuated according to the controller's command and its position can be transferred back to the controller. The above mentioned method is very helpful to verify the control algorithm and such field devices as poisoners, servo valves, limit switches and pressure switches. This paper introduces the whole procedure and the result of simulation test using the above mentioned verification system with actual control hardware and the steam turbine model.

A one-dimensional dual-pressure steam turbine (ST) model for the marine Rankine cycle is built in this paper. Based on constructal theory, the optimal design of the dual-pressure ST is performed with a fixed total volume of the high- and low-pressure STs. The total power output (PO) of the dual-pressure ST is maximized. Seventeen parameters, including the dimensionless average diameters (DADs) of the stages, steam inlet angles (SIAs) of the stages, average reaction degrees (ARDs) of the stages, and volume ratio of the high-pressure ST are taken as optimization variables. The optimal structure parameters of the stages are gained. It reveals that the total PO of the dual-pressure ST is increased by 2.59% by optimizing the average diameter of the Curtis stage, and the change in the total PO is not obvious by optimizing the average diameter of the third stage of the low-pressure ST. Both the total PO and the corresponding efficiency of the dual-pressure ST are increased by 10.8% after simultaneously optimizing 17 variables with the help of the Matlab optimization toolbox. The novelty of this paper is introducing constructal theory into turbine performance optimization by varying seventeen structure, thermal and flow parameters, and the result shows that the constructal optimization effect is remarkable. Optimal designs of practical STs can be guided by the optimization results gained in this paper.

Finite element models (FEMs) are extensively used in the design optimization of utility scale steam turbines. As an example, by simulating multiple startup scenarios of steam power plants, engineers can obtain turbine designs that minimize material utilization, and at the same time, avoid the damaging effects of large thermal stresses or rubs between rotating and stationary parts. Unfortunately, FEMs are computationally expensive and only a limited amount of simulations can be afforded to get the final design. For this reason, numerous model reduction techniques have been developed to reduce the size of the original model without a significant loss of accuracy. When the models are nonlinear, as is the case for steam turbine FEMs, model reduction techniques are relatively scarce and their effectiveness becomes application dependent. Although there is an abundant literature on model reduction for nonlinear systems, many of these techniques become impractical when applied to a realistic industrial problem. This paper focuses on a class of nonlinear FEM characteristic of thermo-elastic problems with large temperature excursions. A brief overview of popular model reduction techniques is presented along with a detailed description of the computational challenges faced when applying them to a realistic problem. The main contribution of this work is a set of modifications to existing methods to increase their computational efficiency. The methodology is demonstrated on a steam turbine model, achieving a model size reduction by four orders of magnitude with only 4% loss of accuracy with respect to the full order FEMs.

The diversification of power generation methods within existing power networks has increased the requirement for operational flexibility of plants employing steam turbines. This has led to the situation where steam turbines may operate at very low volume flow conditions for extended periods of time. Under operating conditions where the volume flow through the last stage moving blades (LSMBs) of a low-pressure (LP) steam turbine falls below a certain limit, energy is returned to the working fluid rather than being extracted. This so-called “ventilation” phenomenon produces non-synchronous aerodynamic excitation, which has the potential to lead to high dynamic blade loading. The aerodynamic excitation is often the result of a rotating phenomenon, with similarities to rotating stall, which is well known in compressors. Detailed unsteady pressure measurements have been performed in a single stage model steam turbine operated with air under ventilation conditions. Detailed analysis revealed that the rotating excitation mechanism observed in operating steam turbines, is reproduced in the model turbine. 3D CFD has been applied to simulate the unsteady flow in the air model turbine. The numerical model consists of the single stage modeled as a full annulus, as well as the axial-radial diffuser. An unsteady CFD analysis has been performed for sufficient rotor revolutions such that the flow is globally periodic. It has been shown that the simulation reproduces well the characteristics of the phenomenon observed in the tests. The detailed insight into the flow field allows the drawing of conclusions as to the nature of the excitation mechanism. One result is that the LSMB tip clearance flow is found to have very little or no effect on the characteristics of mechanism for the case studied.

This paper presents an application of a non-contacting blade tip timing measurement system using two-sensor method (so-called BSSM) at a low-pressure model steam turbine to investigate dynamic blade stress in extended operation conditions (so-called windage). An analysis method to identify the vibration frequencies and to determine the response amplitudes for the first few excited vibration mode shapes is described in detail. Objective of this paper is to discuss the performance and inherent limitations of the non-contacting measurement system. For that the BSSM results were compared with the blade vibration data obtained from strain gauges. Some experiences and suggestions are also made to improve the reliability and accuracy of this measurement system.

This paper presents methods for continuous condition monitoring of railway switches and crossings (S&C, turnout) via sleeper-mounted accelerometers at the crossing transition. The methods are developed from concurrently measured sleeper accelerations and scanned crossing geometries from six in situ crossing panels. These measurements combined with a multi-body simulation (MBS) model with a structural track model and implemented scanned crossing geometries are used to derive the link between the crossing geometry condition and the resulting track excitation. From this analysis, a crossing condition indicator is proposed. The indicator is defined as the root mean square (RMS) of a track response signal γ that has been band-passed between frequencies corresponding to track deformation wavelength bounds of and for the vehicle passing speed (f = v/). In this way, the indicator ignores the quasi-static track response with wavelengths predominantly above and targets the dynamic track response caused by the kinematic wheel-crossing interaction governed by the crossing geometry. For the studied crossing panels, the indicator ( and ) was evaluated for γ = u, v, or a as in displacements, velocities, and accelerations, respectively. It is shown that this condition indicator has a strong correlation with vertical wheel–rail contact forces that is sustained for various track conditions. Further, model calibrations were performed to measured sleeper displacements for the six investigated crossing panels. The calibrated models show (1) a good agreement between measured and simulated sleeper displacements for the lower frequency quasi-static track response and (2) improved agreement for the dynamic track response at higher frequencies. The calibration also improved the agreement between measurements and simulation for the crossing condition indicator demonstrating the value of model calibration for condition monitoring purposes.

The fault diagnosis model of steam turbine based on Bayesian network is direct impacts on the complexity of the diagnostic process, so the construction of Bayesian network model is the primary problem. According actual fault diagnosis system of steam turbine containing redundancy and uncertain information, proposed attribute reduction method to fault feature, obtained the minimal diagnosis rules. Based on two-node union reverse inference, proposed an improved program in the construction of Bayesian network. The Bayesian network model based on the minimum fault decision table can effectively reduce the complexity of the network structure, while the using of improved Bayesian network can further reduce complexity of structure and improve the diagnosis speed. Finally, the effectiveness and fastness of this method are validated by the result of practical fault diagnosis example in Bently-RK4 rotor vibration bench.

We have previously shown that intravascular microdialysis in a central vein is an accurate method for continuous glucose monitoring in patients undergoing cardiac surgery. However, no hypoglycemia occurred in our earlier studies, prompting further evaluation of the accuracy of intravascular microdialysis in the hypoglycemic range. Thus, this animal study was performed. A porcine model was developed; hypoglycemia was induced using insulin injections. The pigs were monitored with intravascular microdialysis integrated in a triple-lumen central venous catheter. As reference, venous blood gas samples were taken every 5 minutes and analyzed in a blood gas analyzer. Ethical permission for the animal experiments was obtained from the Stockholm Regional Ethical Committee, reference no N397/09. A total of 213 paired samples were obtained for analysis, and 126 (59.2%) of these were in the hypoglycemic range (<74 mg/dl). Using Clarke error grid analysis, 100% of the paired samples were in region AB and 99% in region A. The ISO standard (ISO15197) was met. Bland-Altman analysis showed bias (mean difference) ± limits of agreement was -0.18 ± 16.2 mg/dl. No influence from glucose infusions was seen. The microdialysis monitoring system was found to be very responsive in rapid changes in blood glucose concentration. This study shows that intravascular microdialysis in a central vein is an accurate method for continuous glucose monitoring in hypoglycemia in a porcine experimental model. Furthermore, the system was not influenced by glucose administration and was found to be responsive in rapid blood glucose fluctuations.

Within a large modern combine cycle gas turbine (CCGT) power station, it is typical for thousands of process signals to be continually recorded and archived. This data may contain valuable information about plant operations. However, the large volume of data accompanied with inconsistencies within the data often limits the ability to identify useful information about the process. Utilising data mining techniques, such as Principal Component Analysis (PCA) and Partial Least Squares (PLS), it is possible to create a reduced order statistical model representing normal plant conditions. Such a model can then be utilised for fault identification and identifying possible improvements in key performance indicators such as thermal efficiency. Moreover, the gas turbine performance can be affected by changes in ambient conditions. A long term nonlinear PLS techniques can be applied here to investigate the seasonal changes in gas turbine. In this chapter, an approach to establish a long term statistical model for gas turbine will be given, and the application of the model in fault detection and performance analysis will be demonstrated.

The article proposes an object-oriented method for modeling steam turbine plants. The novelty of the method is in the application of a steam turbine model that takes into account variations in internal efficiency under variable operating modes.The article presents the results of theoretical substantiation of nonlinear dependence of the power of the turbine compartments on the steam flow passing through them, based on the change in the internal efficiency of the stages under variable modes described by the Stodola-Flugel equation. An empirical dependence of the efficiency of the stage operation on the relative steam consumption is proposed. Recommendations on the use of empirical form in the development of models of steam turbine compartments are given. The empirical dependences of the relative internal efficiency of turbine compartments obtained from the results of thermal tests of an operating turbine unit are presented.As a factor of practical significance of the research, a model of PT-60-130/13 type steam turbine plant has been developed involving the use of an object-oriented programming language. Recommendations on the description of classes of objects within the steam turbine plant. The developed STP model enables to simulate any operating modes depending on electrical and thermal loads, as well as to take into account the influence of deviations of external factors from nominal values when developing a system of corrections or estimating an increase in fuel consumption associated with these deviations.

Geometric Modularity in the Thermal Modeling of Solar Steam Turbines

Subsynchronous vibration of high-pressure steam turbine is one of the difficult problems to improve the reliability of power plant. Extensive work has been done to prevent the low frequency vibration of high-capacity steam turbine and most of the problems were practically solved[1][2]. In the future, we must build up theoretical approach to design a new turbine operating under the steam condition of high-temperature and high-pressure. To design such an advanced steam turbine, it is necessary to solve the effect of partial admission on control stage of the steam turbine. This paper describes the experimental results from the scale model of the steam turbine and theoretical analysis of Alford force considered partial admission condition to solve the problem. (1) Subsynchronous vibration was reproduced in the scale model test. (2) Partial admission gave larger destabilizing force compared with full admission condition for same total flow rate. (3) Initial position of shaft center to the phase of admission arc on the partial admission had some effect on the stability of the rotor system. (4) Theoretical analysis of destabilizing force considered partial admission condition gave qualitative description of the experimental results from the scale model.

Steam turbines are increasingly being used in industries for duties other than base load operations, where fast start-ups, rapid load changes, and frequent shutdowns are involved. Generally, industrial steam turbines operate with constant inlet steam parameters and are partial admission turbines having the first turbine stage as an impulse stage and the subsequent turbine stages as reaction stages on drum-type rotors. During start-up, as control valves open, steam is admitted and passes through impulse blading, wheel chamber, and through the subsequent reaction stages. The turbine outer casing is horizontally split and the parting plane flanges have relatively thick sections. To limit thermal stresses which arise due to temperature differences in outer casings and rotors, the steam flow has to be increased gradually. The rate at which the steam flow is to be increased depends on the efficiency of heat transfer, i.e., the heat transfer coefficient, and hence knowledge of inside heat transfer coefficient is essential. The high heat transfer coefficients, h, at the beginning of cold start are attributable to condensation of steam at initial stages. The value of h decreased with lapse of time, and also its variation reduced considerably over time. Further, the h value varies more with more » location rather than with lapse of time. The variations observed in h show the complexity of heat transfer process and also bring out the fact that semi-empirical formulas, such as Gazley`s (1958), are not accurate for application in steam turbines. More studies need to be conducted on models of steam turbines to generate adequate data based on which a new correlation for the heat transfer coefficient h for start-up phase of operation could be proposed. « less

Condition monitoring of wind turbine based on incremental learning and multivariate state estimation technique