The authors studied the fracture mechanical properties under half-symmetric loading in this paper. The stress distribution around the crack tip and the stress intensity factor of three kinds of notched specimens under half symmetric loading were compared. The maximum tensile stress σmax of double notch specimens was much greater than that of single notch specimens and the maximum shear stress τmax was almost equal, which means that the single notch specimens were more prone to Mode II fractures. The intensity factors KII of central notch specimens were very small compared with other specimens and they induced Mode I fractures. For both double notch and single notch specimens, KII was kept at a constant level and did not change with the change of a/h, and KII was much larger than KI. KII has the potential to reach its fracture toughness KIIC before KI and Mode II fractures occurred. Rock-like materials were introduced to produce single notch specimens. Test results show that the crack had been initiated at the crack tip and propagated along the original notch face, and a Mode II fracture occurred. There was no relationship between the peak load and the original notch length. The average value of KIIC was about 0.602 MPa×m1/2, and KIIC was about 3.8 times KIC. The half symmetric loading test of single notch specimens was one of the most effective methods to obtain a true Mode II fracture and determine Mode fracture toughness.
This paper proposes a speech enhancement method using the multi-scales and multi-thresholds of the auditory perception wavelet transform, which is suitable for a low SNR (signal to noise ratio) environment. This method achieves the goal of noise reduction according to the threshold processing of the human ear's auditory masking effect on the auditory perception wavelet transform parameters of a speech signal. At the same time, in order to prevent high frequency loss during the process of noise suppression, we first make a voicing decision based on the speech signals. Afterwards, we process the unvoiced sound segment and the voiced sound segment according to the different thresholds and different judgments. Lastly, we perform objective and subjective tests on the enhanced speech. The results show that, compared to other spectral subtractions, our method keeps the components of unvoiced sound intact, while it suppresses the residual noise and the background noise. Thus, the enhanced speech has better clarity and intelligibility.
In this paper, a new lifting wavelet domain audio watermarking algorithm based on the statistical characteristics of sub-band coefficients is proposed. First of all, an original audio signal was segmented and each segment was divided into two sections. Then, the Barker code was used for synchronization, the LWT (lifting wavelet transform) was performed on each section, a synchronization code and a watermark were embedded into the first section and the second section, respectively, by modifying the statistical average value of the sub-band coefficients. The embed strength was determined adaptively according to the auditory masking property. Experiments show that the embedded watermark has better robustness against common signal processing attacks than present algorithms based on LWT and can resist random cropping in particular.