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- W2897532420 abstract "Abstract Although fault detection and diagnosis are extensively studied and demonstrated on synthetic benchmarks, very few demonstrations of industrial application exist. In this paper, an investigation of faulty conditions in an industrial base metal refinery is conducted using standard statistical fault detection and diagnosis methods, and the IntelliSenzo™ monitoring dashboard. A workflow for offline fault investigation is described, and demonstrated on the industrial data, highlighting the need for careful record keeping, a structured approach, and iterative investigative steps. Potential propagation paths established links between the identified fault, process variables of interest, and engineering hypotheses, guiding the investigation and leading to recommendations of corrective action to the operating plant. The root cause of the fault (leaking and choked feed valves) were identified as potential causes in the investigation. Plant personnel confirmed that this structured approach, using process data, statistical techniques, and engineering knowledge, could speed up fault investigations, and reduce the costs of production losses and plant downtime." @default.
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- W2897532420 date "2018-01-01" @default.
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- W2897532420 title "Fault Diagnosis for an Industrial High Pressure Leaching Process with a Monitoring Dashboard" @default.
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- W2897532420 doi "https://doi.org/10.1016/j.ifacol.2018.09.402" @default.
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