TUV SUD National Engineering Laboratory

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Real-Time Sensors Allow Data-Driven Monitoring of Flow-Measurement Systems


Author: Behzad Nobakht

Vertical: Petroleum and Coal

Organizations: TUV SUD National Engineering Laboratory

The downtime of manufacturing machinery, engines, or industrial equipment can cause an immediate loss of revenue. Reliable prediction of such failures using multivariate sensor data can prevent or minimize the downtime. With the availability of real-time sensor data, machine-learning and deep-learning algorithms can learn the normal behavior of the sensor systems, distinguish anomalous circumstances, and alert the end user when a deviation from normal conditions occurs.

Read more at Journal of Petroleum Technology