A new structural framework for parity equation-based failure detection and isolation
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Fault diagnosis in power plant using neural networks
Information Sciences: an International Journal - Intelligent manufacturing and fault diagnosis (II). Soft computing approaches to fault diagnosis
Fuzzy Control
Neural Networks for Identification, Prediction, and Control
Neural Networks for Identification, Prediction, and Control
Engineering Applications of Artificial Intelligence
An architecture for fault detection and isolation based on fuzzy methods
Expert Systems with Applications: An International Journal
Fuzzy logic-based decision-making for fault diagnosis in a DC motor
Engineering Applications of Artificial Intelligence
Towards Robustness in Neural Network Based Fault Diagnosis
International Journal of Applied Mathematics and Computer Science - Issues in Fault Diagnosis and Fault Tolerant Control
Active Fault Diagnosis Based on Stochastic Tests
International Journal of Applied Mathematics and Computer Science - Issues in Fault Diagnosis and Fault Tolerant Control
Online elicitation of Mamdani-type fuzzy rules via TSK-based generalized predictive control
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Fuzzy sets of rules for system identification
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Multiobjective identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Fuzzy Systems
Parameter Identification of Recurrent Fuzzy Systems With Fuzzy Finite-State Automata Representation
IEEE Transactions on Fuzzy Systems
Enhanced Fuzzy System Models With Improved Fuzzy Clustering Algorithm
IEEE Transactions on Fuzzy Systems
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A fault tolerant measurement system for a gas turbine in a combined cycle power plant, based on dynamic models, principal component analysis (PCA) and Q test, is presented. The proposed scheme makes use of a model-based symptom generator, which delivers fault signals obtained by using direct identification of parity relations and structured residuals. Symptoms are then analyzed in a statistical module achieving fault diagnosis and reconstruction of the faulty signals. The scheme presents as main advantage the ability of detecting faults in both input and output sensors due to its particular structure. Tests carried out on the gas turbine of the San Isidro combined cycle power plant in the V Region, Chile, show that Takagi-Sugeno fuzzy models present the best fitting performance and an acceptable computational cost in comparison with autoregressive exogenous, state space, and neural models. Real time software based on this scheme has been developed and connected to Osisoft PI System^(TM). The software is running at Endesa Monitoring and Diagnosis Center in Santiago, Chile.