A new technique for measuring liquid-level utilizing wedge wave is presented and demonstrated through FEM simulation and a corresponding experiment. The velocities of wedge waves in the air and the water, and the sensitivities for the measurement, are compared with the simulation and the results obtained in the experiments. Combining the simulation and the measurement theory, it is verified that the foundation framework for the methods is available. The liquid-level sensing is carried out using the aluminum waveguide with a 30° wedge in the water. The liquid-level is proportional to the traveling time of the mode 1 wedge wave. The standard deviations and the uncertainties of the measurement are 0.65 mm and 0.21 mm using interface echo, and 0.39 mm and 0.12 mm utilized by end echo, which are smaller than the industry standard of 1.5 mm. The measurement resolutions are 7.68 μm using the interface echo, which is the smallest among all the guided acoustic wave-based liquid-level sensing.

Measuring Liquid-Level Utilizing Wedge Wave.

Liquid level measurement in lab on a chip (LOC) devices is a challenging task due to the demand for a sensor with ultra-high resolution but miniature in nature. In this Letter, we report a simple, compact in size, yet highly sensitive liquid level sensor based on a hollow core fiber (HCF) structure. The sensor is fabricated by fusion splicing a short section of HCF between two singlemode fibers (SMFs). Sensor samples with different lengths of HCF have been studied; it is found that the sensor with a HCF length of ∼4.73  mm shows the best sensitivity of ∼0.014  dB/μm, corresponding to a liquid level resolution of ∼0.7  μm, which is over five times higher than that of the previous reported fiber optic sensors to date. In addition, experimental results have demonstrated that the proposed sensor shows good repeatability of measurement and a very low cross sensitivity to changes in the refractive index of the surrounding medium.

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Sub-micrometer resolution liquid level sensor based on a hollow core fiber structure

The study demonstrates the development of a novel low-cost plastic optical fiber (POF) based sensor for liquid level measurement. The sensor works on the principle of reduction in scattering-based optical losses (in contrast to the increase in optical losses for evanescent wave-based sensing) in a straight decladded fiber with an increase in the liquid level due to refractive index changes in the medium surrounding the fiber. A compact optical setup is developed in-house consisting of two U-bent fiber probes coupled to a single LED on one end and two photodetectors on the other ends to measure the optical intensity changes. One of the U-bent probes is decladded over the length of the fiber to act as a test probe to measure the liquid level, while the other probe acts as a reference to compensate for the light intensity fluctuations due to light source instability and ambient conditions. The difference in voltage responses of the two photodetectors gives a measure for liquid level. We have investigated the fiber optic level sensor response to rising and falling liquid levels over 55 cm in presence of aqueous liquids of different refractive index values (1.33 to 1.38) and 95% ethanol as well as DI water at various temperatures from 16 °C up to 70 °C. A level sensitivity of 1.4 and 3.3 mV/mm for water level changes was obtained for the liquid level below and above 45 cm respectively. In addition, the fiber optic level sensor shows a stable and reproducible response over several cycles of 30 min duration at different liquid levels. The results demonstrate that this fiber optic level sensor is not only easy-to-make, cost-effective and robust but also offers sensitive, stable and reproducible instantaneous level measurements.

Plastic fiber optic sensor for continuous liquid level monitoring

Multiphase Flow Meters Targeting Oil & Gas Industries

The popularity of Internet-of-Things (IoT) has provided us with unprecedented opportunities to enable a variety of emerging services in a smart home environment. Among those services, sensing the liquid level in a container is critical to building many smart home and mobile healthcare applications that improve the quality of life. This paper presents LiquidSense, a liquid level sensing system that is low-cost, high accuracy, widely applicable to different daily liquids and containers, and can be easily integrated with existing smart home networks. LiquidSense uses existing home WiFi network and a low-cost transducer that attached to the container to sense the resonance of the container for liquid level detection. In particular, our system mounts a low-cost transducer on the surface of the container and emits a well-designed chirp signal to make the container resonant, which introduces subtle changes to the home WiFi signals. By analyzing the subtle phase changes of the WiFi signals, LiquidSense extracts the resonance frequency as a feature for liquid level detection. Our system constructs prediction models for both continuous and discrete predictions using curve fitting and SVM respectively. We evaluate LiquidSense in home environments with containers of three different materials and six types of liquids. Results show that LiquidSense achieves an overall accuracy of 97% for continuous prediction and an overall F-score of 0.968 for discrete predication. Results also show that our system has a large coverage in a home environment and works well under non-line-of-sight (NLOS) scenarios.

Liquid Level Sensing Using Commodity WiFi in a Smart Home Environment

In many circumstances, the conventional ultrasonic liquid-level detection presents the unreliable estimations due to the dynamically changed liquid level. In addition, there are circumstances where the level change involves not only the fluctuation but also the rise or fall of liquid level. To improve the measuring accuracy of liquid level using the ultrasonic method in dynamically changed level case, an attractive ultrasonic method, named the liquid-level detection based on the multiple-input multiple-output ultrasonic transducer array, is proposed in this paper. This method is different from the early ultrasonic liquid-level detections, including those that utilize transducer array. Based on the virtual element technology, the method employs the multitransducer array to achieve the reduction of system complexity and cost, and then applies the synthetic aperture technology to realize rapid samples of liquid level. Besides, one adaptive searching scheme of focused position in beamforming of synthetic aperture in each scanning direction is optimized to get the high precise samples of liquid level. The proposed method is verified by simulation and a real system, and compared with the conventional single-channel approach. We still proposed a simulation method of ultrasonic echo signal from liquid level based on the boundary-layer theory and the ultrasonic scattering theory. The simulated and actual measurement results demonstrate that the proposed method is obviously superior to the conventional approach. Meanwhile, the factors influencing on the proposed method are investigated by simulation also. The investigations reveal that the focus position in beamforming, the SNR of echo signal, and the wave size of liquid level have impact on the suggested method. However, it is indicated that the good performance of the proposed method remains, provided that the focus in beamforming is properly set in every scanning direction and the noise of echo signal is effectively controlled.

An Accurate Detection for Dynamic Liquid Level Based on MIMO Ultrasonic Transducer Array

The challenge of detecting the infrared small target in complex scenes is how to enhance the target area and suppress the interference of the background and noise. We present an infrared small target detection method based on saliency and difference of Gaussian. By calculating the spectral residuals of the original infrared images to obtain the saliency map, and a gray difference map is computed by adopting the difference of Gaussian. By normalizing and fusing these maps, the final feature response map is obtained, which can restrain the background noise and enhance the targets. Finally, the adaptive threshold segmentation method is used to detect small targets from the feature response map. Experimental result indicates that the proposed method achieves better image processing effect than traditional detection algorithm, works well under the interference of background and noise as well as detects the target accurately under different complex backgrounds.

Jie Yin

Papers

An Accurate Detection for Dynamic Liquid Level Based on MIMO Ultrasonic Transducer Array

Infrared small target detection based on saliency and difference of Gaussian