Dynamic kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes

Ahmed Shokry; Mohammad Hamed Ardakani; Gerard Escudero; Moisès Graells; Antonio Espuña

doi:10.1016/j.compchemeng.2017.03.016

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Dynamic kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes

Ahmed Shokry Mohammad Hamed Ardakani Gerard Escudero Moisès Graells Antonio Espuña

Year: 2017 Journal: Computers & Chemical Engineering Vol: 106 Pages: 758-776 Publisher: Elsevier BV

DOI: 10.1016/j.compchemeng.2017.03.016

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Keywords:

Kriging Benchmark (surveying) Fault detection and isolation Nonlinear system Fault (geology) Residual Process (computing) Computer science Set (abstract data type) Algorithm Data mining Engineering Mathematical optimization Machine learning Artificial intelligence Mathematics

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Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Mineral Processing and Grinding

Physical Sciences → Engineering → Mechanical Engineering

Advanced Statistical Process Monitoring

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Dynamic kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes

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