A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels.

Pressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the research showed that the accuracy of the traditional probabilistic ellipse imaging method was severely affected by the truncation length of the signal. In order to improve the defect location accuracy of the probabilistic elliptic imaging algorithm, an adaptive signal truncation method based on signal difference analysis was proposed, and a novel probabilistic elliptic imaging method was developed. Firstly, the relationship model between the signal difference coefficient (SDC) and the distance coefficient was constructed. Through this model, the distance coefficient of each group signal can be calculated, so that the adaptive truncation length for each group of signals can be determined and the truncated signals used for defect imaging. Secondly, in order to improve the robustness of the new imaging method, the relationship between the defect location accuracy and SDC thresholds were investigated and the optimal threshold was determined. The experimental results showed that the probabilistic ellipse imaging algorithm, based on the new adaptive signal truncation method, can effectively locate a single defect on a pressure vessel.

Si0.97Ge0.03 microelectronic thermoelectric generators with high power and voltage densities.

Microelectronic thermoelectric generators are one potential solution to energizing energy autonomous electronics, such as internet-of-things sensors, that must carry their own power source. However, thermoelectric generators with the mm2 footprint area necessary for on-chip integration made from high thermoelectric figure-of-merit materials have been unable to produce the voltage and power levels required to run Si electronics using common temperature differences. We present microelectronic thermoelectric generators using Si0.97Ge0.03, made by standard Si processing, with high voltage and power generation densities that are comparable to or better than generators using high figure-of-merit materials. These Si-based thermoelectric generators have <1 mm2 areas and can energize off-the-shelf sensor integrated circuits using temperature differences ≤25 K near room temperature. These generators can be directly integrated with Si circuits and scaled up in area to generate voltages and powers competitive with existing thermoelectric technologies, but in what should be a far more cost-effective manner.