scholarly journals Experimental Aspects in the Vibration-Based Condition Monitoring of Large Hydrogenerators

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Geraldo Carvalho Brito Junior ◽  
Roberto Dalledone Machado ◽  
Anselmo Chaves Neto ◽  
Mateus Feiertag Martini
Keyword(s):  
Condition Monitoring ◽  
Accurate Determination ◽  
Cooling Water ◽  
Journal Bearings ◽  
Operating Conditions ◽  
Normal Operation ◽  
Steady State Condition ◽  
Dimensional Changes ◽  
Cooling Water Temperature ◽  
Theoretical Predictions

Based on experimental observations on a set of twenty 700 MW hydrogenerators, compiled from several technical reports issued over the last three decades and collected from the reprocessing of the vibration signals recorded during the last commissioning tests, this paper shows that the accurate determination of the journal bearings operating conditions may be a difficult task. It shows that the outsize bearing brackets of large hydrogenerators are subject to substantial dimensional changes caused by external agents, like the generator electromagnetic field and the bearing cooling water temperature. It also shows that the shaft eccentricity of a journal bearing of a healthy large hydrogenerator, operating in steady-state condition, may experience unpredictable, sudden, and significant changes without apparent reasons. Some of these phenomena are reproduced in ordinary commissioning tests or may be noticed even during normal operation, while others are rarely observed or are only detected through special tests. These phenomena modify journal bearings stiffness and damping, changing the hydrogenerator dynamics, creating discrepancies between theoretical predictions and experimental measurements, and making damage detection and diagnostics difficult. Therefore, these phenomena must be analyzed and considered in the application of vibration-based condition monitoring to these rotating machines.

Thermodynamics Applied to Geothermal Power Plants: Case Study—Unit 5, Cerro Prieto, Baja California Mexico

2011 ◽  
Author(s):  
He´ctor Enrique Campbell Rami´rez ◽  
Gisela Montero Alpirez ◽  
Margarita Gil Samaniego Ramos ◽  
Benjamin Valdez Salas
Keyword(s):  
Power Plants ◽  
Cooling Tower ◽  
Cooling Water ◽  
Normal Operation ◽  
Vacuum System ◽  
Cooling Water Temperature ◽  
Exit Temperature ◽  
Higher Temperature ◽  
Geothermal Power ◽  
Cerro Prieto

Cerro Prieto Geothermal Power Plant has a capacity of 720 MW. The earliest 5 units are 23 years old, and unit 5 from Cerro Prieto Uno was restored in 2008. This paper presents a thermodynamic analysis on the effects that has the increase of non condensable gases content in geothermal steam. Results show that the cooling water temperature will rise due to the energy entering the system with the water flow of the new vacuum system that feeds the condenser. Normal operation would be limited and there exists a risk of not sustaining the condenser’s pressure. The new vacuum system, should extract from the condenser a flow 4 times larger, requiring 27% more steam at a higher pressure, as well as 4.5 times the quantity of cooling water. At this condition, the water returning to the condenser is 4.3 times larger than the original at a higher temperature, increasing in 218% the associated energy. A thermal behavior model was obtained for the cooling tower. In the most likely scenario the cooling tower exit temperature will be higher than the required, and to maintain the equilibrium it will be necessary to lower the condenser thermal load by reducing the steam flow to the turbine and accordingly, the power delivered.

scholarly journals Impact of the cold end operating conditions on energy efficiency of the steam power plants

2010 ◽  
Vol 14 (suppl.) ◽  
pp. 53-66 ◽  
Author(s):  
Mirjana Lakovic ◽  
Mladen Stojiljkovic ◽  
Slobodan Lakovic ◽  
Velimir Stefanovic ◽  
Dejan Mitrovic
Keyword(s):  
Energy Efficiency ◽  
Power Plant ◽  
Water Temperature ◽  
Flow Rate ◽  
Power Plants ◽  
Cooling Water ◽  
Operating Conditions ◽  
Steam Boiler ◽  
Steam Power ◽  
Cooling Water Temperature

The conventional steam power plant working under the Rankine Cycle and the steam condenser as a heat sink and the steam boiler as a heat source have the same importance for the power plant operating process. Energy efficiency of the coal fired power plant strongly depends on its turbine-condenser system operation mode. For the given thermal power plant configuration, cooling water temperature or/and flow rate change generate alterations in the condenser pressure. Those changes have great influence on the energy efficiency of the plant. This paper focuses on the influence of the cooling water temperature and flow rate on the condenser performance, and thus on the specific heat rate of the coal fired plant and its energy efficiency. Reference plant is working under turbine-follow mode with an open cycle cooling system. Analysis is done using thermodynamic theory, in order to define heat load dependence on the cooling water temperature and flow rate. Having these correlations, for given cooling water temperature it is possible to determine optimal flow rate of the cooling water in order to achieve an optimal condensing pressure, and thus, optimal energy efficiency of the plant. Obtained results could be used as useful guidelines in improving existing power plants performances and also in design of the new power plants. <br><br><font color="red"><b> This article has been corrected. Link to the correction <u><a href="http://dx.doi.org/10.2298/TSCI151102198E">10.2298/TSCI151102198E</a><u></b></font>

Organic Fluids in a Supercritical Rankine Cycle for Low Temperature Power Generation

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Rachana Vidhi ◽  
Sarada Kuravi ◽  
D. Yogi Goswami ◽  
Elias Stefanakos ◽  
Adrian S. Sabau
Keyword(s):  
Cooling Water ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Operating Conditions ◽  
Variable Pressure ◽  
Working Fluid ◽  
Source Temperature ◽  
Cooling Water Temperature ◽  
Energy And Exergy ◽  
Organic Fluids

This paper presents a performance analysis of a supercritical organic Rankine cycle (SORC) with various working fluids with thermal energy provided from a geothermal energy source. In the present study, a number of pure fluids (R23, R32, R125, R143a, R134a, R218, and R170) are analyzed to identify the most suitable fluids for different operating conditions. The source temperature is varied between 125 °C and 200 °C, to study its effect on the efficiency of the cycle for fixed and variable pressure ratios. The energy and exergy efficiencies for each working fluid are obtained and the optimum fluid is selected. It is found that thermal efficiencies as high as 21% can be obtained with 200 °C source temperature and 10 °C cooling water temperature considered in this study. For medium source temperatures (125–150 °C), thermal efficiencies higher than 12% are obtained.

Engine Fault Diagnosis Using Acoustic Signals

2013 ◽  
Vol 295-298 ◽  
pp. 2013-2020 ◽  
Author(s):  
Wail M. Adaileh
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Internal Combustion Engines ◽  
Fault Detection And Diagnosis ◽  
Operating Conditions ◽  
Normal Operation ◽  
Sound Emission ◽  
Ic Engine ◽  
Promising Alternative ◽  
Spark Plug

This work presents an experimental study to detecting the faults of engine using its noise. The noises produced by the engine and its accessory systems are numerous: whines, squeals, knock, rattles, and many other sounds. Faults diagnosis for Mitsubishis car engine model 2006 has been conducted and this diagnosis includes normal operating conditions for the engine (without malfunction) and for malfunctions situations at variable engine speed 1000,2000, 3000 and 4000 rpm respectively The engine data is acquired from a four cylinder one- petrol engine test bed under consideration at different operating states, and then simulated. Most of the conventional fault diagnosis techniques using sound emission and vibration signals are based on analyzing the signal amplitude in the time or frequency domain. For engine under fired and misfires spark the all the domain parameters (RMS amplitude, peak amplitude and energy) was processed using MATLAB software.It was found that fault detection and diagnosis for internal combustion engines is complicated by the presence of engine noise during normal operation. The average of amplitude found to be 450 x10-3m for normal engine working without any malfunction and 458x10-3m for misfire of one spark plug and for misfire of two spark plugs 457.8 x10-3m. In this study, some of the engine malfunction such as failure spark plug has been recorded, but we can generalize it to include all engine breakdown. Generally, sound emission signal serves as a promising alternative to the condition monitoring and fault diagnosis in rotating machinery when the vibration signal is not available. This research paper explores that automobiles could be major sources of noise pollution. Condition monitoring and fault diagnosis of IC engine through acoustic signal analysis is an established technique for detecting early stages of component degradation.

Simulation-Driven Deep Learning Approach for Wear Diagnostics in Hydrodynamic Journal Bearings

2020 ◽  
pp. 1-26
Author(s):  
Ozhan Gecgel ◽  
Joao Paulo Dias ◽  
Stephen Ekwaro-Osire ◽  
Diogo Alves ◽  
Tiago H. Machado ◽  
...  
Keyword(s):  
Deep Learning ◽  
Condition Monitoring ◽  
Learning Algorithm ◽  
Journal Bearings ◽  
Operating Conditions ◽  
Intelligent Machines ◽  
The Past ◽  
Deep Learning Algorithm ◽  
Promising Tool ◽  
Rotating Systems

Abstract Early diagnosis in rotating machinery has been a challenge when looking towards the concept of intelligent machines. A crucial and critical component in these systems is the lubricated journal bearing, subjected to wear fault by abrasive removing of material in its inner wall, mainly during run-ups and run-downs. In extreme conditions, wear faults can cause unexpected shutdowns in rotating systems. Consequently, advanced condition monitoring is an essential procedure in the wear diagnosis of journal bearings. Although an increasing number of data-driven condition monitoring approaches for rotating machines have been proposed in the past decade, they mostly rely on substantial amounts of experimental data for training, which is expensive and time-consuming to obtain. The objective of this work is to develop a framework using a deep learning algorithm to classify wear faults in hydrodynamic journal bearings using simulated vibrations signals. Numerically simulated datasets under different wear severity levels and operating conditions were used to train and test the diagnostics framework. The results show that the proposed framework can be a promising tool to wear fault diagnostics in journal bearings.

scholarly journals Experimental Estimation of Journal Bearing Stiffness for Damage Detection in Large Hydrogenerators

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Geraldo Carvalho Brito ◽  
Roberto Dalledone Machado ◽  
Anselmo Chaves Neto
Keyword(s):  
Damage Detection ◽  
Journal Bearing ◽  
Turbine Rotor ◽  
Journal Bearings ◽  
Operating Conditions ◽  
Tilting Pad ◽  
Theoretical Predictions ◽  
Bearing Stiffness ◽  
Stiffness And Damping

Based on experimental pieces of evidence collected in a set of twenty healthy large hydrogenerators, this article shows that the operating conditions of the tilting pad journal bearings of these machines may have unpredictable and significant changes. This behavior prevents the theoretical determination of bearing stiffness and damping coefficients with an adequate accuracy and makes damage detection difficult. Considering that dynamic coefficients have similar sensitivity to damage and considering that it is easier to monitor bearing stiffness than bearing damping, this article discusses a method to estimate experimentally the effective stiffness coefficients of hydrogenerators journal bearings, using only the usually monitored vibrations, with damage detection purposes. Validated using vibration signals synthesized by a simplified mathematical model that simulates the dynamic behavior of large hydrogenerators, the method was applied to a journal bearing of a 700 MW hydrogenerator, using two different excitations, the generator rotor unbalance and the vortices formed in the turbine rotor when this machine operates at partial loads. The experimental bearing stiffnesses obtained using both excitations were similar, but they were also much lower than the theoretical predictions. The article briefly discusses the causes of these discrepancies, the method’s uncertainties, and the possible improvements in its application.

scholarly journals Reduction of CO2 Emissions in Steelmaking by Means of Utilization of Steel Plant Waste Heat to Stabilize Seasonal Cooling Water Temperature

2021 ◽  
Vol 13 (11) ◽  
pp. 5957
Author(s):  
Tomas Mauder ◽  
Michal Brezina
Keyword(s):  
Continuous Casting ◽  
Water Temperature ◽  
Co2 Emissions ◽  
Waste Heat ◽  
Cooling Water ◽  
Main Idea ◽  
Casting Process ◽  
Spray Cooling ◽  
Steel Plant ◽  
Cooling Water Temperature

Production of overall CO2 emissions has exhibited a significant reduction in almost every industry in the last decades. The steelmaking industry is still one of the most significant producers of CO2 emissions worldwide. The processes and facilities used at steel plants, such as the blast furnace and the electric arc furnace, generate a large amount of waste heat, which can be recovered and meaningfully used. Another way to reduce CO2 emissions is to reduce the number of low-quality steel products which, due to poor final quality, need to be scrapped. Steel product quality is strongly dependent on the continuous casting process where the molten steel is converted into solid semifinished products such as slabs, blooms, or billets. It was observed that the crack formation can be affected by the water cooling temperature used for spray cooling which varies during the year. Therefore, a proper determination of the cooling water temperature can prevent the occurrence of steel defects. The main idea is based on the utilization of the waste heat inside the steel plant for preheating the cooling water used for spray cooling in the Continuous Casting (CC) process in terms of water temperature stabilization. This approach can improve the quality of steel and contribute to the reduction of greenhouse gas emissions. The results show that, in the case of billet casting, a reduction in the cooling water consumption can be also reached. The presented tools for achieving these goals are based on laboratory experiments and on advanced numerical simulations of the casting process.

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