Acoustic waves are often suitable for measuring and influencing physical systems and processes. For this purpose, our expertise in transducers for transmitting and receiving waves and the knowledge of the interaction between the waves and such systems or processes is essential. Increasingly, ultrasound is being used for non-destructive testing of materials and systems.
TRANSDUCERS AND SENSORS
The Department of Acoustics has knowledge about a vast variety of transducers of different sizes for use with both gases and liquids. These transducers can be used as loudspeakers or microphones, as well as for energy harvesting. We have experience in selection and modelling of commercially available products, as well as in-house design of piezo-electrical (plastic or crystalline) and electrodynamical transducers (loudspeakers).
Sensor technology in the general area of technical acoustics involves applications where the sound signal is not necessarily audible. The sensors detect or generate acceleration, speed, deflection, or pressure for a specific application in a given medium.
Intimate knowledge about the mechanisms that generate the phenomena that are being measured, as well as a thorough understanding of the medium or material with respect to diffraction, absorption, noise sources, and coupling to the sensor or other materials; all this is required for an optimal design of a sensor, together with basic competency in transducer technology. The fact that these factors show a frequency dependency complicates matters further. The department has tools for modelling of transducers. We also have access to lab facilities at the Department of Electronics and Telecommunications at NTNU, enabling us to prototype our own transducer designs.
The department has experience in modelling and design of sensors from a number of different applications and a wide frequency range, spanning from a few hundred Hz up to several MHz. Examples of such applications are:
- A multi-frequency system for detection of plankton in the sea
- A sensor for measurements of sea currents
- Sensors for analysis of metal melts
- Sensors for detection of break-ins
- Sensors for signalling in oil pipe walls
- An acoustic fence for fish
- A system for steering of fertilizer production aided by controlled sound
We also apply transducers for energy harvesting from different media. The energy is in turn used for powering of other sensors. An example of this is in gas pipes, where the energy in the gas flow can be harvested and used for signalling. Similarly, the kinetic energy of a fish can be exploited for signalling purposes. In both these cases the energy is stored in a battery or a capacitor.
Contact: Tone Berg
Acoustic signature analysis / pattern recognition is used for categorizing, classifying and characterizing sources, objects or sound/noise-events.
Humans do this intuitively; if we hear a train coming, we know immediately that this is a train, and not a dog nor a car – and we can even decide if the train is approaching or moving away. The sound processing capability of the human ear combined with the cognitive power of the brain; make us good pattern recognisers in many situations.
We try to mimic this capability by making systems that analyze acoustic signals, in order to make some judgements about the origin of the sound. The acoustic signal might be generated by the source itself. Alternatively the signal might be generated by humans, either by exciting the source in some way directly (knocking for instance), or by transmitting an acoustic signal that in turn results in an echo. The source could be a car, a human, a fracture, just simply anything that is able to generate or reflect audible or non-audible sound. By analyzing the signal with respect to time and frequency, it is possible to train a system that recognizes specific sounds or properties.
At SINTEF ICT we have addressed this problem in different applications:
- SINTEF has in collaboration with civil aviation (Avinor) and Norsonic developed a monitoring system that records all noise close to an airport, and extracts the noise that is due to air traffic only. This classification is based on neural networks.
- Within the health field we work with a system whose aim is to support the diagnostics related to snoring. By analyzing the sound of the snoring, we aim to find the positions where the sound generation occurs.
- For traffic monitoring we have developed systems that can measure whether the car has tyres with or without studs.
- For Nordan (a window manufacturer) we have developed criteria and specifications for a sensor that detects break-ins.
- For the power industry we have developed a system capable of diagnosing the condition of high voltage circuit-breakers.
Contact: Tone Berg