Ultra-Wideband Signal Propagation Experiments in Liquid Media

Šelmić, Rastko R.; Mitra, Atindra K.; Challa, S.; Šimičević, N.

doi:10.1109/tim.2009.2022452

Cited by 11 publications

(5 citation statements)

References 9 publications

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“…Non-contact material identification method. At present, there are several popular methods for non-contact material identification: based on RF signals [ 3 , 4 , 5 ], based on UWB signals [ 6 , 7 , 8 ], based on radar signals [ 9 ], and based on Wi-Fi signals [ 10 ]. For example, TagScan [ 5 ] identifies the liquid by measuring the phase and the received signal intensity change when the RF signals penetrate through the liquid.…”

Section: Materials Identification-related Workmentioning

confidence: 99%

“…The most popular non-contact material identification models are based on the following signals: radio frequency (RF) signals [ 3 , 4 , 5 ], ultra-wideband (UWB) signals [ 6 , 7 , 8 ], radar signals [ 9 ], and Wi-Fi signals [ 10 ]. For example, TagScan [ 5 ] uses RF signals to identify similar liquids, such as Pepsi and Coke.…”

Section: Introductionmentioning

confidence: 99%

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Identification of Solid and Liquid Materials Using Acoustic Signals and Frequency-Graph Features

Zhang,

Zhou

2023

Entropy

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Material identification is playing an increasingly important role in various sectors such as industry, petrochemical, mining, and in our daily lives. In recent years, material identification has been utilized for security checks, waste sorting, etc. However, current methods for identifying materials require direct contact with the target and specialized equipment that can be costly, bulky, and not easily portable. Past proposals for addressing this limitation relied on non-contact material identification methods, such as Wi-Fi-based and radar-based material identification methods, which can identify materials with high accuracy without physical contact; however, they are not easily integrated into portable devices. This paper introduces a novel non-contact material identification based on acoustic signals. Different from previous work, our design leverages the built-in microphone and speaker of smartphones as the transceiver to identify target materials. The fundamental idea of our design is that acoustic signals, when propagated through different materials, reach the receiver via multiple paths, producing distinct multipath profiles. These profiles can serve as fingerprints for material identification. We captured and extracted them using acoustic signals, calculated channel impulse response (CIR) measurements, and then extracted image features from the time–frequency domain feature graphs, including histogram of oriented gradient (HOG) and gray-level co-occurrence matrix (GLCM) image features. Furthermore, we adopted the error-correcting output code (ECOC) learning method combined with the majority voting method to identify target materials. We built a prototype for this paper using three mobile phones based on the Android platform. The results from three different solid and liquid materials in varied multipath environments reveal that our design can achieve average identification accuracies of 90% and 97%.

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Section: Materials Identification-related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of Solid and Liquid Materials Using Acoustic Signals and Frequency-Graph Features

Zhang,

Zhou

2023

Entropy

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“…Wide-band wireless signals have been used in several papers to classify liquids using simple and cheap systems. − The liquid can be identified when estimating its permittivity by noninvasively shining the wireless signals through it. Wang et al proposed a system that is capable to identify 10 liquids using RFID readers and tags.…”

Section: Introductionmentioning

confidence: 99%

Contactless Optical Liquid Identifier

Obeidat,

Abu Mousa,

Mushaljy

2023

ACS Omega

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This paper presents the development of a portable device that can be used for liquid identification using the concept of Beer–Lambert law. The final device can recognize up to 30 different materials in their liquid state and provides some other useful features that can enhance its operation. The user can set a group of 30 liquids according to specific needs and applications. The device can provide the user with some specific settings to start the measurements. The volume of a fluid is identified by a 4 mL sample inserted in the cuvette, then the user can start measuring the concentration of some common solvents like methanol, ethanol, etc. by passing a light of different wavelengths through the sample. The amount of the transferred light is measured using photodetectors and the readings depend on the amount of absorption. The amount of absorption depends on the sample types, colors, contents, and concentrations, so it is used as the main indicator to identify a specific sample.

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“…Previous studies have shown that gases, solids and liquids affect the electromagnetic wireless channel coefficients measured at individual frequencies (Alshabo et al, 2012;Baghdady and Ely, 1966;Boan, 2007;Selmic et al, 2010;Shimomura et al, 2012;Wee et al, 2009;Yin-Chung and Porter, 1978;Micheli et al, 2015). Vector Network Analyzers (VNA) are used with antennas to measure a range of complex wireless channel coefficients at many different frequencies.…”

Section: Introductionmentioning

confidence: 99%

Ultra wideband channel coefficient measurements for detecting methane gas in a multipath environment

Alshabo

Stirling

Ros

et al. 2016

Australian Journal of Electrical and Electronics Engineering

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In this paper, an investigation was carried out into the effect of a non-explosive methane gas mixture on various Ultra Wide Band Channel Coefficients. Using simplified apparatus consisting of a rubberized tube (6 mm diameter) connected for significant periods to either a (pressurized) source of mixed Methane and Nitrogen or alternatively to a Nitrogen only source. The tube containing either gas feed was wrapped using two complete turns around a 160mm diameter PVC pipe. Several flows of the mixed gas, containing 2.57% methane, were introduced and flowed through the pipe before being sealed in the tube. Removal of any Methane in the tube was achieved by flushing it with the pure Nitrogen source, initially and in-between samples of the mixed source. A Vector Network Analyser was connected using two identical directional antennas with the wrapped section of tubing placed between the two antennas and the wireless channel coefficients were measured over the Ultra Wide Band frequency span of 0.3GHz to 8GHz. Magnitude differences were taken between the baseline condition (tube flushed out with Nitrogen) and alternatively containing the methane mixture. It was found that consistent and repeatable experiments produced the same trend of differences over the same frequency span. This system based on this approach could thus be used as a simple sensor to detect the acc Disciplines Disciplines Engineering | Science and Technology Studies

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Ultra-Wideband Signal Propagation Experiments in Liquid Media

Cited by 11 publications

References 9 publications

Identification of Solid and Liquid Materials Using Acoustic Signals and Frequency-Graph Features

Identification of Solid and Liquid Materials Using Acoustic Signals and Frequency-Graph Features

Contactless Optical Liquid Identifier

Ultra wideband channel coefficient measurements for detecting methane gas in a multipath environment

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