ABSTRACT
In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.
ABSTRACT
In this paper the extended autocorrelation velocity estimator is evaluated and compared using a nondestructive ultrasonic device. For this purpose, three velocity estimators are evaluated and compared. The autocorrelation method (ACM) is the most used and well established in current ultrasonic velocity profiler technology, however, the technique suffers with phase aliasing (also known as the Nyquist limit) at higher velocities. The cross-correlation method (CCM) is also well known and does not suffer with phase aliasing as it relies on time shift measurements between emissions. The problem of this method is the large computational burden due to several required mathematical operations. Recently, an extended autocorrelation method (EAM) which combines both ACM and CCM was developed. The technique is not well known within the fluid engineering community, but it can measure velocities beyond the Nyquist limit without the ACM phase aliasing issues and with a lower computational cost than CCM. In this work, all three velocity estimation methods are used to measure a uniform flow of the liquid inside a controlled rotating cylinder. The root-mean-square deviation variation coefficient (CVRMSD) of the velocity estimate and the reference cylinder velocity was used to evaluate the three different methods. Results show that EAM correctly measures velocities below the Nyquist limit with less than 2% CVRMSD. Velocities beyond the Nyquist limit are only measured well by EAM and CCM, with the advantage of the former of being computationally 15 times faster. Furthermore, the maximum value of measurable velocity is also investigated considering the number of times the velocity surpasses the Nyquist limit. The combination of number of pulses and number of samples, which highly affects the results, are also studied in this work. Velocities up to six times the Nyquist limit could be measurable with CCM and EAM using a set of parameters as suggested in this work. The results validate the use of the NDT tool to measure velocities even beyond Nyquist limit by using EAM.
ABSTRACT
Ultrasonic measurement techniques for velocity estimation are currently widely used in fluid flow studies and applications. An accurate determination of interfacial position in gas-liquid two-phase flows is still an open problem. The quality of this information directly reflects on the accuracy of void fraction measurement, and it provides a means of discriminating velocity information of both phases. The algorithm known as Velocity Matched Spectrum (VM Spectrum) is a velocity estimator that stands out from other methods by returning a spectrum of velocities for each interrogated volume sample. Interface detection of free-rising bubbles in quiescent liquid presents some difficulties for interface detection due to abrupt changes in interface inclination. In this work a method based on velocity spectrum curve shape is used to generate a spatial-temporal mapping, which, after spatial filtering, yields an accurate contour of the air-water interface. It is shown that the proposed technique yields a RMS error between 1.71 and 3.39 and a probability of detection failure and false detection between 0.89% and 11.9% in determining the spatial-temporal gas-liquid interface position in the flow of free rising bubbles in stagnant liquid. This result is valid for both free path and with transducer emitting through a metallic plate or a Plexiglas pipe.
