Orengo Rodríguez, José

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Time constant anomaly detection of thermocouples using transient data
(2006) Orengo Rodríguez, José; Just Agosto, Frederick A.; College of Engineering; Serrano, David; Jia, Yi; Department of Mechanical Engineering; Resto, Pedro
A specific methodology to detect anomalies in temperature sensors is developed in this thesis. The strategy evaluates sensor faults or variations in the transient region only by examining the signal produced by a thermocouple. The algorithm employed used a procedure in which several time derivatives are taken and filtering techniques must be present to ensure correct anomaly detection in the presence of noise. In order to test the procedure a neural network (NN) approach that uses the data processed by the algorithm was developed. The network developed was a Radial Basis probabilistic neural network (PNN). The algorithm distinguishes anomalous sensor behavior and classifies the cause of the behavior. In almost all of the trials the estimation of the NN technique proposed was less than one percent while the greatest error was less than five percent.