Amar Kumar

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Model based approach for damage fault diagnostic solution and life prognostic methodology is addressed in the paper. A life cycle management model and a working algorithm for coated hot section gas turbine blades are presented. Physics based modeling is developed with experimental thermally grown oxide damage data, while the fracture mechanics model is(More)
Multivariate data analysis by artificial neural network (ANN) approach was carried out in a previous work to identify anomalous regime in a gas turbine operational data. In this work, statistical hypothesis analysis using univariate time series exhaust temperature data from the same engine model has been carried out. The objective is to compare the results(More)
Time series temperature data from an industrial steam turbine are used in the present analysis to develop methodology for anomaly detection. Simple and exponential smoothing techniques are used to study the effectiveness of the technique for prediction considering different periods for analysis. The analysis of the lags between the predicted and observed(More)
This present work follows our earlier research efforts on fault diagnosis and prognosis solutions considering statistical and physics based approaches. In-service performance analysis and detection of any malfunctioning in an operating small sized gas turbine engine using artificial neural network approach is the central theme of this work. The measured(More)
Data based approach and methodology for real time diagnosis and prognosis solutions for thermomechanical systems is discussed. Coated turbine blade operation is emulated to sensor online temperature data as the real-time inputs for the software code developed. An algorithm is presented first and extended sampling based statistical hypothesis tests are used(More)
Statistical multivariate linear regression technique has been applied in predicting exhaust gas temperature (EGT) for a small gas turbine engine using three independent input variables. Data collected earlier over three years (YR) of operational cycle are used for modeling, training, testing and validation of the models. Regression coefficients, probability(More)
A statistical algorithm was developed for the damage fault diagnosis and prognosis tool and the present work focuses on the experimental validation. The oxide scale growth experiments using laboratory samples under thermal cycling simulate the hot section turbine blade coating failures. The experimental steps, oxide thickness data measurement, collection(More)
An algorithm and optimization analysis results for standalone (wind and solar) and hybrid renewable power sources is presented. A generic iteration approach considering dual criteria, namely power reliability and minimum cost of energy is considered for the analysis. Yearlong environmental data (wind speed and solar insolation) is used to test and validate(More)
Gas turbine engine performance and health conditions are continuously assessed by exhaust gas temperature that indicate the thermal health condition of engine. Analysis of exhaust gas temperature (EGT) data and its prediction is very important for operational safety, reliability, life cycle cost and power output. Autoregressive (AR) and moving average (MA)(More)
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