Open Access

In this work we experimentally verify the theoretical prediction of the recently published Energy Density Fluctuation Model (EDF-model) of thermo-acoustic sound generation. Particularly, we investigate experimentally the influence of thermal inertia of an electrically conductive film on the efficiency of thermal airborne ultrasound generation predicted by the EDF-model. Unlike widely used theories, the EDF-model predicts that the thermal inertia of the electrically conductive film is a frequency-dependent parameter. Its influence grows non-linearly with the increase of excitation frequency and reduces the efficiency of the ultrasound generation. Thus, this parameter is the major limiting factor for the efficient thermal airborne ultrasound generation in the MHz-range. To verify this theoretical prediction experimentally, five thermo-acoustic emitter samples consisting of Indium-Tin-Oxide (ITO) coatings of different thicknesses (from 65 nm to 1.44 lm) on quartz glass substrates were tested for airborne ultrasound generation in a frequency range from 10 kHz to 800 kHz. For the measurement of thermally generated sound pressures a laser Doppler vibrometer combined with a 12 lm thin polyethylene foil was used as the sound pressure detector. All tested thermo-acoustic emitter samples showed a resonance-free frequency response in the entire tested frequency range. The thermal inertia of the heat producing film acts as a low-pass filter and reduces the generated sound pressure with the increasing excitation frequency and the ITO film thickness. The difference of generated sound pressure levels for samples with 65 nm and 1.44 lm thickness is in the order of about 6 dB at 50 kHz and of about 12 dB at 500 kHz. A comparison of sound pressure levels measured experimentally and those predicted by the EDF-model shows for all tested emitter samples a relative error of less than ±6%. Thus, experimental results confirm the prediction of the EDF-model and show that the model can be applied for design and optimization of thermo-acoustic airborne ultrasound emitters.

Thin steel sheets with a thickness of 0.3 mm and less are the base materials of many everyday life products (cans, batteries, etc.). Potential inhomogeneities such as non-metallic inclusions inside the steel can lead to a rupture of the sheets when it is formed into a product such as a beverage can. Therefore, there is a need to develop automated NDT techniques to detect hidden defects and inclusions in thin sheets during production. For this purpose Tata Steel Europe and BAM, the Federal Institute for Materials Research and Testing (Germany), collaborate in order to develop an automated NDT-system. Defect detection systems have to be robust against external influences, especially when used in an industrial environment. In addition, such a facility has to achieve a high sensitivity and a high spatial resolution in terms of detecting small inclusions in the μm-regime. In a first step, we carried out a feasibility study to determine which testing method is promising for detecting hidden defects and inclusions inside ferrous thin steel sheets. Therefore, two methods were investigated in more detail – magnetic flux leakage testing (MFL) using giant magneto resistance sensor arrays (GMR) as receivers [1,2] and eddy current testing (ET). The capabilities of both methods were tested with 0.2 mm-thick steel samples containing small defects with depths ranging from 5 μm up to 60 μm. Only in case of GMRMFL-testing, we were able to detect parts of the hidden defects with a depth of 10 μm trustworthily with a SNR better than 10 dB. Here, the lift off between sensor and surface was 250 μm. On this basis, we investigated different testing scenarios including velocity tests and different lift offs. In this contribution we present the results of the feasibility study leading to first prototypes of GMR-probes which are now installed as part of a demonstrator inside a production line.

Prospects and Restrictions of the Metal Magnetic Memory Technique

Giant magneto-resistive (GMR) sensor based metal magnetic memory (MMM) technique is proposed for mapping of deformation-induced self-magnetic leakage fields (SMLFs) in carbon steel. The specimens were subjected to different amounts of tensile deformation and the deformation-induced SMLFs were measured using a GMR sensor after unloading the specimens. 3D-nonlinear finite element modeling was performed to predict stress–strain state in a steel specimen under tensile load. The experimentally obtained SMLF images were correlated with the finite element model predicted stress–strain states. Studies reveal that the MMM technique can detect the plastic deformation with signal-to-noise ratio better than 20 dB. The technique enables the mapping of plastic deformation in carbon steels for the evaluation of the severity of deformation. The study also reveals that deformation-induced SMLF is influenced by the presence of initial surface residual stress, introduced by shot peening. The intensity of SMLF signal is found to increase with increase in tensile load and decrease with shot peening.