Estimation of Gas Turbine Unmeasured Variables for an Online Monitoring System

2020 ◽  
Vol 37 (4) ◽  
pp. 413-428
Author(s):  
Igor Loboda ◽  
Luis Angel Miró Zárate ◽  
Sergiy Yepifanov ◽  
Cristhian Maravilla Herrera ◽  
Juan Luis Pérez Ruiz
Keyword(s):  
Gas Turbine ◽  
Monitoring System ◽  
Online Monitoring ◽  
Real Data ◽  
Data Driven ◽  
Monitoring Systems ◽  
Practical Implementation ◽  
Diagnostic Features ◽  
Thermal Boundary Conditions ◽  
Online Monitoring System

AbstractOne of the main functions of gas turbine monitoring is to estimate important unmeasured variables, for instance, thrust and power. Existing methods are too complex for an online monitoring system. Moreover, they do not extract diagnostic features from the estimated variables, making them unusable for diagnostics. Two of our previous studies began to address the problem of “light” algorithms for online estimation of unmeasured variables. The first study deals with models for unmeasured thermal boundary conditions of a turbine blade. These models allow an enhanced prediction of blade lifetime and are sufficiently simple to be used online. The second study introduces unmeasured variable deviations and proves their applicability. However, the algorithms developed were dependent on a specific engine and a specific variable. The present paper proposes a universal algorithm to estimate and monitor any unmeasured gas turbine variables. This algorithm is based on simple data-driven models and can be used in online monitoring systems. It is evaluated on real data of two different engines affected by compressor fouling. The results prove that the estimates of unmeasured variables are sufficiently accurate, and the deviations of these variables are good diagnostic features. Thus, the algorithm is ready for practical implementation.

A Mixed Data-Driven and Model Based Fault Classification for Gas Turbine Diagnosis

2010 ◽  
Author(s):  
Igor Loboda ◽  
Sergey Yepifanov
Keyword(s):  
Gas Turbine ◽  
Real Data ◽  
Statistical Testing ◽  
Data Driven ◽  
Fault Classification ◽  
Mixed Data ◽  
Monitoring Systems ◽  
Model Errors ◽  
Model Based ◽  
Common Diagnosis

In modern gas turbine health monitoring systems, the diagnostic algorithms based on gas path analysis may be considered as principal. They analyze gas path measured variables and are capable of identifying different faults and degradation mechanisms of gas turbine components (e.g. compressor, turbine, and combustor) as well as malfunctions of the measurement system itself. Gas path mathematical models are widely used in building fault classification required for diagnostics because faults rarely occur during field operation. In that case, model errors are transmitted to the model-based classification, which poses the problem of rendering the description of some classes more accurate using real data. This paper looks into the possibility of creating a mixed fault classification that incorporates both model-based and data-driven fault classes. Such a classification will combine a profound common diagnosis with a higher diagnostic accuracy for the data-driven classes. A gas turbine power plant for natural gas pumping has been chosen as a test case. Its real data with cycles of compressor fouling were used to form a data-driven class of the fouling. Preliminary qualitative analysis showed that these data allow creating a representative class of the fouling and that this class will be compatible with simulated fault classes. A diagnostic algorithm was created based on the proposed classification (real class of compressor fouling and simulated fault classes for other components) and artificial neural networks. The algorithm was subjected to statistical testing. As a result, probabilities of a correct diagnosis were determined. Different variations of the classification were considered and compared using these probabilities as criteria. The performed analysis has revealed no limitations for realizing a principle of the mixed classification in real monitoring systems.

Realization of Monitoring Systems of DC Breaker Based on GPRS Technology

2011 ◽  
Vol 52-54 ◽  
pp. 1003-1008
Author(s):  
Jun Wang ◽  
Tao Ning ◽  
Zhi Hua Li
Keyword(s):  
Data Acquisition ◽  
Monitoring System ◽  
Online Monitoring ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Monitoring Systems ◽  
Health State ◽  
Oscillation Circuit ◽  
Online Monitoring System ◽  
Dc Breaker

The inductance and capacitance parameters in oscillation circuit are very important for the HVDC breakers to interrupt the heavy current. In order to know the inductance and capacitance parameters, an online monitoring system of HVDC breaker is designed, and assorted software is also design to process the data got by the data acquisition system. After tested in laboratory, this online monitoring system has proved truly and reliably getting the inductance and capacitance parameters. This system can contribute to analyze the health state of the breaker proceedings breaker.

A Review on the Advancement of Online Monitoring System for Cellulosic Ethanol Production

2015 ◽  
Vol 1113 ◽  
pp. 751-756
Author(s):  
Rosmaria Abu Darim ◽  
Amizon Azizan ◽  
Jailani Salihon
Keyword(s):  
Renewable Energy ◽  
Monitoring System ◽  
Cellulosic Ethanol ◽  
Transfer Rate ◽  
Fermentation Process ◽  
Online Monitoring ◽  
Environmental Concern ◽  
Oxygen Transfer Rate ◽  
Sugar Fermentation ◽  
Online Monitoring System

Bioethanol is mainly produced by sugar fermentation process. Due to global demand on energy for transportation and environmental concern, biofuels as renewable energy in replacing petrol, the non-renewable energy source, has come into picture. Utilization of lignocellulosic biomass such as woody biomass (trees), herbaceous biomass (grasses) and waste cellulosic materials (solid waste) could be used in replacing starch (such as corn and potato) as source of sugar in producing bioethanol. Recently, study on cellulosic ethanol was focussing on fermentation process using ethanologenic strain such as engineered Escherichia coli and Saccharomyces cerevisiae. Invasive method in the study during fermentation may lead to uncertain or unwanted screening strategies or metabolic pathways. This paper reviews about the online monitoring system used by researchers in order to study the growth kinetics of ethanologenic strain. Online monitoring system for the Oxygen Transfer Rate (OTR) and Carbon dioxide Transfer Rate (CTR) is found to be the important method to study kinetic model of ethanologenic strain, thus increasing metabolic yields with optimum design condition.

Analyzing the kinetics of degradation of Acid Red B dye through Fenton oxidation with online monitoring system

2021 ◽  
Vol 216 ◽  
pp. 412-422
Author(s):  
Aiguo Li ◽  
Xiaofeng Fang ◽  
Jiangyuan Sun ◽  
Qianpeng Liu ◽  
Yingying Lian ◽  
...  
Keyword(s):  
Monitoring System ◽  
Online Monitoring ◽  
Fenton Oxidation ◽  
Kinetics Of Degradation ◽  
Online Monitoring System ◽  
Kinetics Of

Online Monitoring System for Stand-Alone Photovoltaic Applications—Analysis of System Performance From Monitored Data

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
M. Torres ◽  
F. J. Muñoz ◽  
J. V. Muñoz ◽  
C. Rus
Keyword(s):  
Performance Analysis ◽  
Real Time ◽  
Monitoring System ◽  
Virtual Instrument ◽  
System Performance ◽  
Online Monitoring ◽  
Research Centre ◽  
Photovoltaic Systems ◽  
System Monitoring ◽  
Online Monitoring System

The Guidelines for the Assessment of Photovoltaic Plants provided by the Joint Research Centre (JRC) and the International Standard IEC 61724 recommend procedures for the analysis of monitored data to asses the overall performance of photovoltaic (PV) systems. However, the latter do not provide a well adapted method for the analysis of stand-alone photovoltaic systems (SAPV) with charge regulators without maximum power point tracker (MPPT). In this way, the IDEA Research Group has developed a new method that improves the analysis performance of these kinds of systems. Moreover, it has been validated an expression that compromises simplicity and accuracy when estimating the array potential in this kind of systems. SAPV system monitoring and performance analysis from monitored data are of great interest to engineers both for detecting a system malfunction and for optimizing the design of future SAPV system. In this way, this paper introduces an online monitoring system in real time for SAPV applications where the monitored data are processed in order to provide an analysis of system performance. The latter, together with the monitored data, are displayed on a graphical user interface using a virtual instrument (VI) developed in LABVIEW®. Furthermore, the collected and monitored data can be shown in a website where an external user can see the daily evolution of all monitored and derived parameters. At present, three different SAPV systems, installed in the Polytechnic School of University of Jaén, are being monitorized and the collected data are being published online in real time. Moreover, a performance analysis of these stand-alone photovoltaic systems considering both IEC 61724 and the IDEA Method is also offered. These three systems use the charge regulators more widespread in the market. Systems #1 and #2 use pulse width modulation (PWM) charge regulators, (a series and a shunt regulator, respectively), meanwhile System #3 has a charge regulator with MPPT. This website provides a tool that can be used not only for educational purposes in order to illustrate the operation of this kind of systems but it can also show the scientific and engineering community the main features of the system performance analysis methods mentioned above. Furthermore, it allows an external user to download the monitored and analysis data to make its own offline analysis. These files comply with the format proposed in the standard IEC 61724. The SAPV system monitoring website is now available for public viewing on the University of Jaén. (http://voltio.ujaen.es/sfa/index.html).

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