Towards a holistic quality assessment for guided wave-based SHM

• Applicant: Professorin Dr.-Ing. Inka Mueller
• Subject Area: Measurement Systems ; Acoustics ; Mechanics
• Term: since 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 424954879

SHM is known as the continuous or periodical and automated method for monitoring and evaluating the condition of a monitoring object. This is realized by measurements with permanently installed or integrated transducers and the automated analysis of the measured data with an expert system for diagnosis.For the quantification of system reliability, the state of the art is the specific test for a specific structure and a specific fault at a specific position. It is therefore limited to proof of concept in many cases. For a holistic quality assessment, which is necessary for the broad use in engineering practice and solid method comparison, no methods are known yet. Especially for SHM methods based on guided waves there is no established procedure to quantify the reliability of these methods. The scientific network focusses this question.There is a thematic link between wave-based SHM and traditional ultrasonic testing of materials. For the latter, methods to estimate the probability of detection, defining the reliability of these methods, exist. Nevertheless, several differences between SHM and NDT exist. Due to the permanently installed transducers, the probability of detection for guided wave-bases SHM is highly location dependent. Moreover, the output on an SHM system consists of a feature vector, which might include damage location, damage size, etc. A reduction to one parameter or a separate analysis for each parameter would neglect the relation between these quantities. Therefore, it is favourable to use this as an added value for a holistic reliability concept for guided wave-based SHM. Via an intensive scientific exchange over three years, this scientific network aims to draw up a solid common understanding of the requirements, develop possible new approaches and possible solution strategies, publish the generated knowledge and use it as a basis for joint research.

• DFG Programme: Scientific Networks