Objective
This project has shown that resonance spectroscopy, when used to test a whole sample (global testing) and when a neural network is used for interpretation is an intrinsically simple test and can be used successfully to assess the mechanical quality of industrial components. It involves no surface scanning and no operator is needed to interpret data. The project has also shown that resonance spectroscopy can be used successfully for local testing with a neural network for interpretation. The output of the neural network can be as simple as either Pass or Fail. The only manipulation of the object required is to place the transducer pair in contact with the sample for the test. For these reasons resonance spectroscopy has considerable potential to be highly cost-effective tool for quality assurance of industrial parts made on a production-line. Resonance spectroscopy has been much less successful when it is used without an effective aid to interpretation - when that the operator is substantially responsible for deciding the quality of the inspected component and it cannot be recommended for use in this particular way. However, resonance spectroscopy when aided by a neural network has proved to be a highly effective tool for inspecting a range of industrial components.
Quality assurance inspection is known to be unsatisfactory for the following industrially important materials and components : concrete, concrete structures, composite honeycomb aerospace materials and high pressure die-cast aluminium components. Improvements sought by industry include : introducing new methods to allow testing for the first time, reducing cost per test, increasing sensitivity to flaw size, in-service monitoring, feature selectivity and pass/fail decision making.
It is proposed to investigate only one method of testing - the method of ultrasonic (and sonic) resonance spectroscopy. Although the method is long-established it is not used to its full potential. Important weaknesses in previous embodiments of the method have been identified which cause distortion to measured spectrums and hence severely reduce its effectiveness. An objective here is to collect spectrums accurately. Another objective is to provide software tools to help interpret the spectrums and hence improve the overall effectiveness of the method.
Two common characteristics of the materials of interest are (i) that they are all difficult or impossible to test by the ultrasonic pulse-echo method and (ii) that they all have fairly low acoustic attenuation at frequencies of interest. Due to the low attenuation standing wave patterns can be established in them and the method of ultrasonic resonance spectroscopy can be applied, however, the challenge remains to interpret spectrum. The range of frequencies of interest is from typically 10Hz (case of concrete structures) to 10MHz (case of aerospace components).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- natural sciences chemical sciences inorganic chemistry post-transition metals
- natural sciences physical sciences optics spectroscopy
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Coordinator
CB4 5NX Cambridge
United Kingdom
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