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- Fault detection approach based on fuzzy qualitative reasoning applied to the DAMADICS benchmark problemPublication . Calado, João Manuel Ferreira; Carreira, F. P. N. F.; Mendes, Mário J. G. C.; Costa, J. M. G. Sá da; Bartys, M.A computer assisted fault detection methodology based on a fuzzy qualitative simulation algorithm is described. The adoption of fuzzy sets allows a more detailed description of physical variables, through an arbitrary, but finite, disaetisatioo of the quantity space. The fuzzy representation of qualitative values is more general than ordinary interval representation, since it can represent not only the information stated by a well defined real interval but also the knowledge embedded in the soft boundaries of the interval. Such a methodology was applied to a pneumatic servomotor actuated control valve that is the benchmark problem of the EC RTN DAMADlCS.
- Fault detection scheme using the agents paradigmPublication . Mendes, Mário J. G. C.; Calado, João Manuel Ferreira; Costa, J. M. G. Sá daAn agent based fault detection (FD) system for complexa nd dynamic processes is proposed in this work. The system is based in the agent paradigm where the modularity and complexity of the processes are important aspects in the FD system constructed. In the future, the FD agents must be able to cooperate and communicate with other systems to achieve a satisfactory performance, as a part of a fault tolerant control multi-agent system. The FD agents proposed here have hybrid architectures based in a horizontal layered architecture. Two types of FD agents are proposed, one based in decomposition wavelet methods with limit checking and other based in neural networks ARX models for residual generation. The agent based FD scheme proposed is applied in a three tank process.
- Fault detection system for the Évora irrigation canalPublication . Louro, Diogo; Mendes, Mário J. G. C.; Valério, Duarte; Costa, José Sá daA model-based fault detection (FD) system was developed for a Simulink simulation of a four pool irrigation canal in ´Evora, Portugal. Incipient and abrupt faults in the gates, the water off-take valves and the water level sensors were considered. Neural Networks were used to model the canal and find the residue. The training algorithm employed for the NNs was found to be an important factor determining the success of the FD system.
- Fault detection agents based on wavelet adaptive thresholdsPublication . Mendes, Mário J. G. C.; Costa, José Sá daDesigning a Fault Tolerant Networked Control System (FTNCS) to deal with large-scale complex networked control systems is a very difficult task due to the large number of sensors and actuators spatially distributed and networked connected. To deal with this problem, this paper presents a new agent based fault detection (FD) system for complex and dynamic processes, where the modularity and complexity of the processes are important aspects in the FD agent system constructed. The FD agents proposed here have hybrid architectures based in a horizontal layers, where the reactive layer is based on Wavelet Adaptive Thresholds. The results, using a distributed benchmark with a three tank process, show that the FD agents proposed are a good alternative to classic FD methods.
- Neuro-fuzzy fault detection approach using a Profibus networkPublication . Calado, João Manuel Ferreira; Mendes, Mário J. G. C.; Kowal, Marek; Korbicz, Józef; Costa, J. M. G. Sá daGenerally three methodologies to develop and test FDI algorithms can de distinguished: software benches, hardware benches and industrial data. The current approach uses a hardware bench constructed with components commonly used in industry that consists on a pilot plant under supervision, a supervision unit, a fault detection unit and a fault simulation unit. All elements are connected to a PROFIBUS network that acts as the communication system exchanging information between automation system and distributed field devices. A fault detection methodology, which is based on neuro-fuzzy models, has been developed and implemented. During the current studies actuator faults, sensor faults and leakages have been considered as incipient and abrupt faults. Several studies have also been performed under multiple simultaneous faulty scenarios.
- Fault detection using neuro-fuzzy networksPublication . Kowal, Marek; Korbicz, Józef; Mendes, Mário J. G. C.; Calado, João Manuel FerreiraGenerally three methodologies to develop and test fault detection (FD) algorithms can be distingguished: software benches, hardware benches and industrial data. The current approach uses a hardware bench that consists of process under supervision (two interconnected stations), supervision unit, fault diagnosis unit and fault simulation unit. All elements of the bench are connected to a PROFIBUS network that acts as the communication system exchaging information between automation system and distributed field devices. A realistic and fexible environment for developing and testing FD systems has been constructed using elements commonly used in industry. During the current studies actuator faults, sensor faults and leakages have been considered as incipiente and abrupt faults. The proposed FD algorithm bases on neuro-fuzzy models that are responsible for residual generation.