Terahertz has been rapidly developed and applied in the field of non-destructive testing because of its features such as perspective and safety. Ceramic devices have the advantages of high-temperature resistance and fatigue resistance and are now widely used in various fields. But at the same time, the ceramic device will have debonding defects due to process quality and environmental problems during the preparation process, which greatly reduces its performance. In this paper, terahertz time-domain spectroscopy is used to image defects in ceramics. Firstly, the optical parameters of ceramics are extracted by transmission terahertz time-domain spectroscopy, and then the defects of ceramics are imaged by maximum imaging, time-of-flight imaging, peak-to-peak imaging, and peak-to-peak time imaging. The defect image obtained by the imaging method is clearer. The type and size of defects can be further obtained by using the terahertz time-domain imaging method, which is an effective method to ensure the quality and safety of devices.
Precision ceramic bonded structural parts have an irreplaceable position in the aerospace business and are widely used in various industries due to their various advantages, but at the same time, the uneven thickness of the adhesive layer will affect the quality of ceramic adhesive structural par. In this paper, terahertz time-domain spectroscopy is used for nondestructive detection of the adhesive layer inside the sample, and the thickness information is reconstructed from the experimental data using an autoregressive spectral extrapolation method based on improved covariance, and the difference in the time of flight of the echoes on the upper and lower surfaces of the adhesive layer is used to find the thickness of the adhesive layer. This paper analyzes the thickness of the adhesive layer of 0.5mm and 1mm respectively, and finally gets the error rate of 7.2% and 6.3%. This error rate is basically in line with the quality of the product and provides reliable technical support for the aerospace business.
Terahertz reflectance spectrum is widely used in material thickness measurement, material composition detection and other aspects. However, the reflection wave is easily affected by the surface roughness produced in the process of material processing, resulting in noise and measurement error. In this paper, the terahertz reflection model of three-layer medium is derived, and the relationship between smooth surface and rough surface is established by Kirchhoff approximation theory. Secondly, the terahertz reflection spectrum and frequency spectrum of aloe emodin were measured by THz-TDS(terahertz-time domain spectral system). By introducing controllable roughness surface with sandpaper of different specifications, the reflection spectrum of roughness of each specification surface was measured, the reflectance corresponding to different frequencies was calculated, and the reflection spectrum of smooth surface was compared and analyzed. The influence of these results on the ability of THz reflection spectrum to detect Chinese medicinal herbs was discussed. In addition, by introducing Kirchhoff approximation, the reflection spectrum relation model of rough surface and smooth surface is established to compensate the reflection spectrum of rough surface. It is found that the power of reflection spectrum can be improved to some extent and the influence of rough surface on reflection spectrum can be reduced.
The loss characteristics of the low-frequency terahertz band (0.325THz-0.50 THz) were tracked during sample aging from perspective of loss tangent, amplitude and phase. The attenuation of signal not only increases with the frequency but also with the aging time. Phase decrease with frequency and is also related to aging time. But the change of rate is almost same for all samples. Besides, it is observed that the loss tangent increases with the frequency, which will also increase with the aging time. Thus, investigators may get a deep understanding of rubber’s remaining life by analyzing optical parameter in terahertz range.
In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.
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