Artificial Intelligence (CSD)

Innovative automation for complex calculations

Monitoring and automation options for improving the efficiency of trailing suction hopper dredgers were impossible until recently. Now available, these options depend on the online availability of important but immeasurable process parameters, such as grain size of pumped material. These parameters can be successfully estimated using Artificial Intelligence (AI) algorithms.
  • Increases productivity by 10-15% 
  • Enhances uptime, and reduces fuel consumption and emissions
  • Prevents water hammer, clogging pipelines and cavitation
  • Estimated value presentation for failing sensors
  • Greater peace of mind for operators

Applications and main features

  • ECO Pump Controller (EPC): optimises dredge pump and pipeline production capability, and prevents water hammer, cavitation and clogging of discharge pipeline. The EPC can simultaneously serve up to three on-board dredge pumps and four booster pumps. Modules within the EPC can jointly operate and serve complete, Artificial Intelligence-based mixture transportation chain control as part of the Automatic Cutter Controller.
  • Sensor Diagnostics (SD): replaces certain failing sensor by estimated signals.
  • Anchor Position Estimator (APE) – see ‘Monitoring System’.
 

 

Backgrounds of AI applications

The AI algorithms apply comprehensive physical models in which signals from all available dredge process instrumentation are coherently processed and filtered by Kalman and other techniques. Therefore, AI applications work as long as high-quality DPM, production, pump pressure and torque measurements have been installed. The more AI applications that are installed, the higher the operational efficiency. It also results in greater peace of mind for operators. The need to interfere in the process considerably decreases.

Downloads

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    Boost to sustainable growth

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  • Document
    Estimating the immeasurable: Soil properties

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