This book documents some of the results of such dialogue and reports on progress in sensors and sensing systems for existing and emerging real-time monitoring applications. This review provides a critical assessment of the applicability of various technologies for real-time water quality monitoring, with an emphasis on technologies reported to have been tested in real-life scenarios. Beck, Real-time water quality monitoring to identify pollution pathways in small and medium-sized rivers, Pages Copyright (2019), courtesy of Elsevier.
Water Quality Monitoring Systems
Another station used was a multisensor for the detection of pH, redox potential, dissolved oxygen, turbidity and conductivity. The results of field tests on treatment plants using automatic systems produced water quality profiles and demonstrated the possibility of determining random and model pollutants. Furthermore, the idea of monitoring water quality through water body analysis is clearly limited: it is impossible to track pollutants that are not sufficiently volatile.
Application of Biosensors and Optical Sensors for Water Quality Assessment
Removal of the template leads to recognizable sites (cavities) within the polymer that are complementary to the target molecule in terms of size, shape and chemical functionality and are suitable for selective rebinding of the analyte [25]. To investigate the applicability of the system on real biological and water samples, different amounts of diazinon were added to urine, tap water, and river water. In addition, the system was able to regenerate itself without the addition of regeneration buffer, demonstrating the reusability of the sensor.
Functionalised Electromagnetic Wave Sensors 1. Microwave Spectroscopy and Water Analysis
Also, changes in the shape pattern of the sensing structure cannot improve the performance of the required pollutant sensitivity and selectivity [55]. Especially at 0.91–1.00 GHz (peak 2), the f-EM sensor shows an improvement for Cu detection with an improvement in sensitivity, higher Q-factor and low LoD compared to an uncoated (UNC) sensor, shown in bold in Table 1[74]. The sensor was able to detect Cu concentrations with a limit of detection (LoD) of 0.036, just above environmental quality standards for fresh water (28–34μg/L). Responses for Cu and Zn were then compared by analyzing microwave spectral responses using a Lorentzian peak fitting function and examining multi-peaks (peaks 0–6) and multi-peaks parameters (peak center, xc, FWHM, w, area, A and height, H, of the peaks) for specific discrimination between these two similar toxic metals [74]. The sensor was able to identify more and less polluted samples in real time with high repeatability (with a coefficient of variation <0.05 dB), and to evaluate changes in water composition.
New Trends in Water Quality Monitoring
Therefore, f-EM sensors can be considered a viable option for real-time water quality monitoring for a wide range of pollutants. A similar system was used for water quality evaluation of Ganga River and city ponds in Kolkata (India). In addition to the traditional analysis of water quality by analytical devices, a completely different approach has been developed.
Conclusions
Real-time monitoring of stream water quality using sulfur-oxidizing bacteria as a bioindicator. Monitoring of water quality in real time and without danger based on a microwave planar resonator sensor.Sens. Water quality—Determination of the inhibitory effect of water samples on the light emission of Vibrio Fischeri (luminescent bacteria assay).
Body Condition Score Estimation Based on Regression Analysis Using a 3D Camera
- Introduction
- Related Work
- Data Collection and Preprocessing
- Automatic Image Selection Process by Filtering
- Proposed BCS Modeling
- Performance Evaluation
- Discussion and Conclusions
The position of the 3D camera and an illustration of the cows in the parlor are shown in Figure 1a,b. Therefore, we only extract the image of the middle of the cow as the desired ID number in the rotary parlor, as shown in Figure 3a,b. The side images of other identification numbers are removed in reverse. Development of a body condition scoring system in Murrah buffaloes: Validation through ultrasound assessment of body fat reserves. J.
Wireless Module for Nondestructive
Testing/Structural Health Monitoring Applications Based on Solitary Waves
- Wireless HNSW Sensor System Overview
- Experimental Setup and Procedure
- Experimental Results 1. Steel Plate: Control Test
- Numerical Results
- Discussion and Conclusions
Many researchers have demonstrated that the amplitude and arrival time of reflected solitary waves depend on key properties of the adjacent structure/material. Section 4 complements the experimental finding with the results of a numerical analysis that models the dynamic interaction of solitary waves with different materials. Figure 3 shows a photo of the printed circuit board with color-coded parts corresponding to individual components.
Figure 5 shows one of the time waveforms and the corresponding Fourier transform associated with this control test. Figure 12b shows that the number of cases of the ToF is more dispersed with respect to the steel test. In addition, the appearance of the ToF measured with the wireless platform is skewed to the left, that is, the PSW moving along transducerT1 appears faster than intransducerT2.
In the future, the experiments will be repeated by first connecting the solenoid and sensor disk terminals to the circuit board and then to the PXI. Figure 15 shows the amplitude of the dynamic force measured on the sensor disc (location #5 in Figure 14a). 6 on the sensor disk and the second peak is the upward impact of the disk on particle #4.
CoV represents the coefficient of variation, i.e. the ratio of the standard deviation to the mean.
Quantified Activity Measurement for Medical Use in Movement Disorders through IR-UWB Radar Sensor †
- Problem Statement
- Algorithm for Measuring Activity 1. Measuring the Sedentary Movement
- Experiment Results
- Conclusions
With respect to sedentary movement (which refers to the movement of the subject accompanied by little or no change in position), the degree of movement was calculated by continuously measuring the amount of change in the magnitude of the reflected signal from the target. The following sections introduce the signal model of the IR-UWB radar and the basic concept of the algorithm for the activity measurement. The received signal from the radar is generated by the bounce[k]through N paths from the surrounding environment.
Therefore, it is impossible for a radar to miss even the very small movements of a human, and the amount of activity of the target can be measured by the change. In cases where the movement is small, the amplitude of the target signal can be reduced. The position of the target can be obtained by using the obtained di and least squares (LS) method.
Position data for time can be represented as p[n] = [xt[n],yt[n],zt[n]]T, where xt[n],yt[n] and zt[n] are the three-dimensional coordinates of the target. The signal from the radars can disrupt the movement of the target's arms or legs. Scenarios 2 and 3 were also measured for sedentary movement situations, sitting in front of a desk.
In each actigraphy sensor there is an accelerometer to measure the movement of the body part.
Pre-Pressure Optimization for Ultrasonic Motors Based on Multi-Sensor Fusion
- A Simulation Model with Power Dissipation
- Experimental Setup
- Simulation and Experimental Results by Varying the Preload Force
- Discussion and Verification of the Optimal Preload Force
- Conclusions
As shown in Figure 1b, due to the contact status and speed of the stator and rotor, two function points are generated on the stator teeth. The output friction can be calculated by the surface integral of the forces within the contact area [25]. From the second curve, the length of the drive zone is equal to 40◦ when the stator is free of bias.
And when the torque is constant, the contact area and driving area gradually expand with the increase in pre-pressures. The speed fluctuations can be attributed to errors of the shaft system during manufacture or assembly. Derived from the images, the stalling torque and the maximum efficiency as a function of the pre-pressures are shown in Figure 8c.
Pre-pressure is one of the critical parameters that limit the performance of an ultrasonic motor. Finally, the optimization region of the preload force is determined as , and the smaller speed stability error in the optimization region verifies the validity of the criterion. Evaluation of the effect of bias force on resonant frequencies of a traveling wave ultrasonic motor. IEEE Trans.
Optimization of traveling wave ultrasonic motors using a three-dimensional analysis of the contact mechanism at the stator-rotor interface.Eur.
![Figure 1. The mechanism of TRUM: (a) the motor structure [26]; (b) the traveling wave and contact state.](https://thumb-ap.123doks.com/thumbv2/1libvncom/9201527.0/75.723.141.591.583.743/figure-mechanism-trum-motor-structure-traveling-contact-state.webp)
On-Line Monitoring of Pipe Wall Thinning by a High Temperature Ultrasonic Waveguide System at the
- Issue of High-Temperature Ultrasonic Thickness Measurements
- Ultrasonic On-Line Monitoring System for Measuring Wall Thinning of High Temperature Pipe
- High Temperature Pipe Thickness Measuring Program
- Verification Experiment in the FAC Proof Facility and Results
In the case of a nuclear power plant, the temperature of the fluid flowing inside the pipe increases to about 200 °C. The shear horizontal wave transducer was attached to the edge of the waveguide strip shown in Figure 2. This method had no main bang signal and the signal reflected from the end of the waveguide strip was very small.
The first gate was set to the signal from the end of the transmitting waveguide strip as shown in Figure 3. Figure 7 shows the change in wall thickness reduction slope with flow rate in the waveguide system. As the flow rate in the pipes increased, the rate at which the pipe wall thinned increased.
The reliability of the developed waveguide system was verified by comparing the conventional buffer rod system and the manual room temperature UT. A shear horizontal ultrasonic pitch/catch waveguide system was developed for accurate online pipe wall thickness monitoring in the FAC certification test facility. A clamping device was designed and installed for the gold plate contact between the end of the waveguide strip and the tube surface.
In addition, the developed waveguide system was able to predict the velocity of the fluid flowing inside the pipe by analyzing the thickness reduction rate.
A Low-Cost Continuous Turbidity Monitor
- Appliance Sensors
- Validation of the Low-Cost Nephelometric Sensor
- Low-Cost Continuous Turbidity Sensing
- Conclusions and Future Work
Although promising, the results were limited and the precision of the turbidity measurement was not presented. According to the TST-10 data sheet, the sensor's usable range is 0–4000 NTU with a voltage difference of 2.7 V. We suspect that some of the error is due to the large reflections and optical impurities in the test tube.
In the previous tests, the separation between LED and sensor was proportional to the width of the cuvette, which is 10 mm. The further the points fall from the diagonal line, the greater the error in the prediction. After calibrating and investigating the performance of the low-cost continuous turbidity monitor in a laboratory environment, we now move to a simulated real-world test.
We plan to investigate the long-term stability of the low-cost continuous turbidity monitor in future work. In our tests, the main source of error was the inaccuracy of the sample holder (cuvette or test tube) in the sensor device. Like all turbidity sensors, periodic calibration is necessary to maintain the accuracy of the low cost continuous turbidity monitor.
We are also planning longer trials to verify the long-term behavior of the low-cost continuous turbidity monitor.
![Figure 5. Construction principle and setup of chloramphenicol sensor. Reproduced from [30] with permission © Elsevier B.V](https://thumb-ap.123doks.com/thumbv2/1libvncom/9201527.0/15.723.195.529.561.903/figure-construction-principle-chloramphenicol-sensor-reproduced-permission-elsevier.webp)
