Acoustic Emission Features of Anthracite under the Influence of Loading Rate

Loading rate is an important impactor of the mechanical properties, as well as the deformation and failure mode of coal and rock. Using an RMT-301 rock mechanics tester and a Soft Island acoustic emitter, uniaxial compression and acoustic emission (AE) tests were carried out on coal samples under different loading rates. The results show that uniaxial compressive stress-strain curves of the rock samples each consist of four segments: compaction, elasticity, yield, and failure. As the loading rate increased from 0.01mm/s to 0.02mm/s, the peak strength rose, the post-peak deformability dropped, the brittle failure features of anthracite became more obvious, more AE events took place, and AE frequency increased. Energy analysis shows that, the faster the loading rate, the larger the AE count, the faster the energy accumulation, but the fewer the total energy accumulation.

Measurement of GT exhaust gas temperature by acoustic pyrometry: Preliminary error investigation

Acoustic pyrometry is an interesting technique that may find several useful applications in turbomachinery. It is well known that the speed of sound in a medium is directly related to its temperature. Acoustic pyrometry estimates the temperature of a gas by considering the time of flight of an acoustic wave moving through it. If one acoustic emitter-receiver couple is used, only the average temperature along the acoustic path can be determined. If multiple emitter-receiver couples laying on the same plane are used, a reconstruction of the temperature map in the section is possible. In this last case, the analysis is based on the fact that the temperature of each sub portion of the section affects the time of flight of all the acoustic paths travelling across it. Many parameters affect the accuracy of the measurement. They are mainly related to the physic of the sound propagation in a medium, the accuracy of the instrumentation used, the interaction between the acoustic wave and the flow velocity and the hardware set-up. In this study, the impact of the measurement set up of an acoustic pyrometry for the measurement of the exhaust gas temperature in a gas turbine was investigated to determine the optimal solution in terms of accuracy and robustness to uncertainties.

Combining Denoising Autoencoders and Dynamic Programming for Acoustic Detection and Tracking of Underwater Moving Targets

Accurate detection and tracking of moving targets in underwater environments pose significant challenges, because noise in acoustic measurements (e.g., SONAR) makes the signal highly stochastic. In continuous marine monitoring a further challenge is related to the computational complexity of the signal processing pipeline—due to energy constraints, in off-shore monitoring platforms algorithms should operate in real time with limited power consumption. In this paper, we present an innovative method that allows to accurately detect and track underwater moving targets from the reflections of an active acoustic emitter. Our system is based on a computationally- and energy-efficient pre-processing stage carried out using a deep convolutional denoising autoencoder (CDA), whose output is then fed to a probabilistic tracking method based on the Viterbi algorithm. The CDA is trained on a large database of more than 20,000 reflection patterns collected during 50 designated sea experiments. System performance is then evaluated on a controlled dataset, for which ground truth information is known, as well as on recordings collected during different sea experiments. Results show that, compared to the benchmark, our method achieves a favorable trade-off between detection and false alarm rate, as well as improved tracking accuracy.

Advanced CFD-MBS coupling to assess low-frequency emissions from wind turbines

The low-frequency emissions from a generic 5 MW turbine are investigated numerically. In order to regard airborne noise and structure-borne noise simultaneously a process chain was developed. It considers fluid-structure coupling (FSC) of a computational fluid dynamics (CFD) solver and multibody simulations (MBS) solver as well as a Ffowcs Williams-Hawkings (FW-H) acoustic solver. The approach was applied to a generic 5 MW turbine to get more insight into the sources and mechanisms of low-frequency emissions from wind turbines. For this purpose simulations with increasing complexity in terms of considered components in the CFD model, degrees of freedom in the structural model and inflow in the CFD model were conducted. Consistent with literature, it has been found that aeroacoustic low-frequency emission is dominated by the blade-passing frequency harmonics. The tower base loads, which excite seismic emission, tend to be dominated by structural eigenfrequencies with increasing complexity of the model. The main source of aeroacoustic emissions is the blade-tower interaction and the contribution of the tower as an acoustic emitter is stronger than the contribution of the rotor. Aerodynamic tower loads also significantly contribute to the external excitation acting on the structure of the wind turbine.