Inspection/maintenance

Predictive-Maintenance Approach Uses Machine Learning To Increase Efficiency

This paper focuses on compressor systems associated with major production deferments. An advanced machine-learning approach is presented for determining anomalous behavior to predict a potential trip and probable root cause with sufficient warning to allow for intervention.

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This paper focuses on compressor systems associated with major production deferments. An advanced machine-learning approach is presented for determining anomalous behavior to predict a potential trip and probable root cause with sufficient warning to allow for intervention. This predictive-maintenance approach has the potential to reduce downtime associated with rotating-equipment failures.

Introduction

The first step in using a machine-learning system is to train the model to identify normal and abnormal operating conditions. The model can then classify real-time data from the equipment and indicate when the equipment’s performance strays outside the identified steady state.

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