In this month’s Partner Spotlight, we explore the work of the Centre for Research and Technology Hellas (CERTH) on real-time flow monitoring. This article follows the evolution of their technology: from the initial challenge of non-invasive sensing and the use of machine learning to interpret complex acoustic data, to the rigorous laboratory validation using safe surrogates, and finally, the integration of these sensors into the wider smart control architecture of the project. 

Non-Invasive Sensing for Real-Time Monitoring

The primary technical objective within the Smart-Pumps project is to gather precise, real-time data from inside a heat pump without physically altering the system piping. Traditional methods for understanding the exact state of a refrigerant rely on invasive equipment that can disrupt the circuit. CERTH is bypassing this limitation by designing a completely non-invasive, “clamp-on” ultrasonic sensor system. Attached directly to the exterior of the circuit, this equipment characterises the two-phase refrigerant flow without disrupting the loop.

Translating Acoustic Signals into Data

Reading acoustic signals through a metal pipe presents significant challenges, primarily because two-phase refrigerant flow is thermodynamically complex. To interpret these raw echoes, the system uses an array of ultrasonic sensors mounted on custom metallic bases, paired with an advanced machine learning architecture. By applying continuous wavelet transform (CWT) scalograms and convolutional neural network (CNN) models, CERTH translates raw acoustic data into accurate predictions of critical parameters, such as mass flow rate, mixture density, and vapour quality.

Laboratory Validation and Safety

To bridge the gap between theory and application, these predictive models require rigorous laboratory validation. To do this safely, the team uses CO₂ as a non-flammable surrogate for R290 (propane), a natural refrigerant common in modern heat pumps. Because CO₂ and propane share similar acoustic properties and sound speeds under comparable thermodynamic conditions, researchers can calibrate the sensors effectively without the flammability risks associated with R290.

                                     

Left: CO₂ flow circuit with the inline pressure regulator, safety and isolation valves, and pressure gauges

 Right: The ultrasonic sensors in the test circuit mounted on the metallic bases

From Laboratory Prototypes to System Integration

Moving from a lab prototype to real-time control requires absolute reliability, as minor temperature or pressure fluctuations can drastically alter a refrigerant’s acoustic signature. To account for this, CERTH’s machine learning pipeline explicitly incorporates temperature and pressure as input channels alongside the acoustic data. Their calibration matrix covers demanding operating conditions, ranging from -15 °C to -25 °C and 10 to 20 bar, preparing the ground for the upcoming system integration phase.

This sensor technology feeds directly into the wider Smart-Pumps architecture. As the leader of Work Package 4, which focuses on demonstration, assessment, and validation, CERTH ensures these sensors integrate with the smart decision-making control loops developed by other partners. This allow the heat pump to dynamically adapt its operation. Beyond hardware, CERTH’s role also extends to standardisation, Life Cycle Assessment (LCA), and evaluating market transferability.

Impact on Efficiency and Maintenance

In conclusion, developing novel sensing technologies is practically meaningful only if they can be manufactured, standardised, and scaled. By providing the data required for self-diagnostics and adaptive control, CERTH’s work enables a measurable improvement in seasonal energy efficiency and predictive maintenance. Making heat pumps smarter and more reliable, particularly for retrofitting existing buildings, is how the Smart-Pumps consortium is actively contributing to the European energy transition.

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