Noninvasive liquid level sensing with laser generated ultrasonic waves

Characterization of bismuth silicon oxide for high temperature ultrasound sensing

Clean energy production continues to grow as an international priority. Solar and nuclear power plants are being designed to operate at high temperatures, and some Generation IV nuclear plants are expected to operate at or above 850 °C. Monitoring of such structures requires advanced sensors able to survive in environments that would easily destroy conventional sensors. Bismuth Silicon Oxide (Bi12SiO20; BSO) is gaining attention as a robust piezoelectric material that can survive in extreme temperatures. In this work, we present a high temperature impedance and phase characterization of BSO transducers up to 600 °C. We also conducted experiments with 5.1 × 5.1 × 1 mm3 BSO face-shear transducers to generate quasi-shear horizontal waves in 3 mm thick steel bars. We performed high temperature acoustic transmission and receiving tests at temperatures up to 650 °C. BSO retains its material properties well until around 500 °C before experiencing major rises in capacitance and dielectric loss (measured at 100 kHz). The BSO transducers also experienced a shift in transmitting frequency from 209-213 kHz at room temperature to approximately 195 kHz at 650 °C. BSO was able to recover its material properties as environmental temperature decreased, and a cooldown test revealed that all properties returned to normal ranges when the sample was cooled. BSO was also able to perform continuously as an ultrasonic emitter and receiver on structural steel from room temperature to 650 °C. Additionally, we conducted multiple defect detection tests using an artificial damage, and BSO was able to detect damage-induced waves up to 600 °C with ≤10 % error. These findings suggest BSO is a material capable of performing high temperature ultrasonic sensing with durability and survivability.

Noninvasive Fluid-Level Sensing in Pipelines Using Ultrasonic Techniques

Accurate fluid-level assessment in sealed pipelines is crucial in wastewater treatment and petrochemical plants, among others. The traditional pulse-echo time-of-flight measurements using ultrasound sensors to measure the fluid level are challenging for low fill levels due to signal contamination with multiple echoes and the resonances in the pipe wall. Though signal-processing strategies such as baseline subtraction and narrowband filtering away from the pipe resonance frequencies improve pulse-echo measurements, low-fill-level detection remains challenging. In this work, we identify these limitations of the pulse-echo technique and propose a resonance-based ultrasonic technique that is accurate and sensitive even at low fill levels. This technique relies on the attenuation of pipe resonances in the presence of fluid, which is validated numerically using time-domain finite-element simulations and experimentally performing resonance measurements on a fluid-filled pipe using an array of transducers. However, the pulse-echo and resonance techniques demand precise calibration with the pipe system before use. To mitigate the need for calibration, we propose a wedge-based phased-array imaging technique based on the total focusing method (TFM) for fluid-level sensing. We discuss the challenges in wedge selection and array positioning and numerically validate the efficiency of TFM to provide better visualization of low fluid levels using a strategy to filter the image artifacts selectively. The presented ultrasonic techniques have significant industrial importance for applications requiring noninvasive fluid-level measurements.

A shadow enabled non-invasive probe for multi-feature intelligent liquid surveillance system

Liquid detection probes used to identify the features of liquids show great promise in a variety of important applications. However, some challenges, such as sample contamination by direct contact with the liquid, the requirement of additional signal emitters, and complex fabrication, hindered the development of liquid detection probes. Here, we developed a non-invasive shadow probe (SP) for a multi-feature intelligent liquid surveillance system (ILSS). The self-powered SP with the working mechanism of the shadow effect can detect the features of liquids by analyzing the variations of liquid shadows such as the area, wavelength, and brightness. The exact resolution (5 different colors, 6 different concentrations, 6 different levels, 100% accuracy) and fast response time (0.2 ms) are shown by the SP under ambient light conditions (even in 0.003 sun). The ILSS, which integrated the SPs with signal processing circuits and applied the artificial intelligence (AI) technique, successfully detects and synoptically learns about liquids simultaneously. The in-real time ILSS reaches a test accuracy of 99.3% for 10 types of liquids with multiple features. This work showcases a promising solution for non-invasive multi-feature liquid detection, displaying great potential for future applications.