Due to new sensor concepts, increasing computer performance originating from smaller hardware (Notebook), cut-price offers and information exchange via networks the possibilities of computer based medical signal processing and diagnostics have improved significantly. In addition, automatic artefact detection and algorithms of artificial intelligence put new diagnostic tools at physicians disposal. some advanced signal processing techniques applied in medical research projects of our institute at the University of Paderborn like Wavelets, Wigner-ville transform, adaptive filtering and neural networks are discussed. Two-dimensional imaging methods are not treated.
During deep drawing of metal components an automatic quality control is necessary to detect cracks or orifices. A reliable recognition of crack development during the deep drawing is process is presently not possible. In this paper a method to supervise deep drawing processes with acoustic emission is discussed. Acoustic emission arise from rapid state changes by exceeding of stress limits in microscopic range. During crack formation energy is set free and delivered to the environment as a dilational wave, which wave, which on flat structures spread as surface waves. Acoustic emission signals having a low energy content are superimposed by machine vibrations, shocks and stream noise. For a reliable detection of acoustic emission they must by characterised. Bending tests with metal strips have been performed. First results of the investigations are presented in this paper. Several sensor systems have been investigated regarding their suitability in practice.
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