A self-adaptive data-driven fault diagnosis method and device for complex refining and chemical processes
A data-driven, fault-diagnosing technology, applied in instrumentation, electrical testing/monitoring, control/regulation systems, etc., to solve problems such as inability to apply
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[0083] According to the calculation process and calculation steps of Granger causality test, the common refinery process—the initial distillation column in atmospheric and vacuum distillation was taken as the research object, and the device fault diagnosis was carried out by using the simulation data.
[0084] This technical solution uses MATLAB to program the Granger causality test, and takes the failure data of the initial distillation column feed reduction as input.
[0085] In the primary distillation tower, the main process parameters are primary distillation tower feed volume and temperature, primary distillation tower top pressure, primary distillation tower top temperature, primary distillation tower bottom liquid level, primary bottom and primary side flow. According to the knowledge of chemical process, the interaction relationship between various process parameters can be known, such as image 3 Shown is the process parameter relationship diagram of this embodiment....
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