K-Means algorithm to detect solenoid valve function status.
Abstract
Now days, the applications of artificial intelligence within engineering processes in general are extremely broad, given the characteristics of both artificial intelligence and engineering in general. In this investigative work we expose the use of artificial intelligence, specifically clustering to be able to detect when a valve is faulty or not, in this way to be able to know, precisely, the operating state of the solenoid valve by Artificial Intelligence from collected data, providing with the analysis carried out in MatLab as a Data-Set for training process. The item of study for this article is a spring compensated three position solenoid valve (DIVW style C). The valve is used in the present experiment in two different operating regions: at 5 MPa and 20 MPa. In addition, a scenario in which the valve presents damage was added to the analysis, which consists of a groove 0.1 [mm] deep.
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