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Unprecedented progress during the last three decades in our understanding of the principles of a living cell, particularly the identification of genes and signaling pathways involved in cell differentiation and organ development, has brought us a broader insight into plant biological processes. Technological advancements are revealing new and fundamental knowledge at the molecular and cellular levels,...
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) techniques, either singly or in combination...
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 of these two methods. The applicability and...
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 data is performed using associated parameters...
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 for anomaly detection tests. Paired t-test...
This paper describes an approach and methodology for data anomaly detection and fault isolation for a diagnostic solution of hot section aeroengine components. The essence of the methodology is the combination of qualitative data exceedence check and quantitative data analysis. Three data sets, namely reference, operational and test data and two significance test methods are proposed and tested using...
Physical damages like thermally grown oxide (TGO) layer develop in the coated gas turbine blade during the aeroengine operation and severely limits the life and performance. This life critical damage data has been considered for the validation of a diagnostic fault analysis. High level architecture, statistical algorithm and experimental modeling of oxide growth data are discussed. Experimental measurement...
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