Fault Detection and Isolation of Industrial Processes Using Optimized Fuzzy Models

Mendonça, L. F.; Sousa, João; Costa, José Sá da

doi:10.1007/978-1-84628-631-5_3

Cited by 1 publication

(1 citation statement)

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“…Dexter [18] created fuzzy reference models to describe the symptoms of both faulty and fault-free plant operations and subsequently used them to identify whether the system is operating correctly or a particular fault is present. Another work based on fuzzy models is reported in [19]. The authors obtain the fuzzy models using a modified regularity criterion algorithm while they optimized them by a genetic algorithm (GA).…”

Section: Related Literaturementioning

confidence: 99%

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

Ntalampiras¹

2015

IEEE Trans. Neural Netw. Learning Syst.

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This paper proposes a holistic modeling scheme for fault identification in distributed sensor networks. The proposed scheme is based on modeling the relationship between two datastreams by means of a hidden Markov model (HMM) trained on the parameters of linear time-invariant dynamic systems, which estimate the specific relationship over consecutive time windows. Every system state, including the nominal one, is represented by an HMM and the novel data are categorized according to the model producing the highest likelihood. The system is able to understand whether the novel data belong to the fault dictionary, are fault-free, or represent a new fault type. We extensively evaluated the discrimination capabilities of the proposed approach and contrasted it with a multilayer perceptron using data coming from the Barcelona water distribution network. Nine system states are present in the dataset and the recognition rates are provided in the confusion matrix form.

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Section: Related Literaturementioning

confidence: 99%

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

Ntalampiras¹

2015

IEEE Trans. Neural Netw. Learning Syst.

View full text Add to dashboard Cite

show abstract

Fault Detection and Isolation of Industrial Processes Using Optimized Fuzzy Models

Cited by 1 publication

References 28 publications

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

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