Analyses of threshold-detection and phase-difference techniques for wind-speed measurement using ultrasonic transducers are presented. The influence of uncertainties that are associated with additive noise and attenuation of the ultrasonic signal on the wind-speed measurement uncertainty is analyzed. A data-fusion procedure based on the maximum-likelihood estimation (MLE) algorithm is developed for the determination of wind speed, with data gathered through threshold-detection and phase-difference techniques. The data-fusion procedure provides a lower measurement uncertainty than those obtained with the above techniques when taken separately. Practical design issues are considered, and an application example is shown to illustrate the proposed procedure.

In this paper, a survey on the characteristics of thermoresistive sensors [positive temperature coefficient (PTC) and negative temperature coefficient (NTC)] and their applications to measurement structures that use the electric equivalence principle, in special radiometers and anemometers, is presented. The dynamic responses of the architectures and the influence of the operational amplifier offset voltage on the instrument performance are discussed. Alternative architectures employing pulsewidth modulation (PWM) and sigma-delta analog-to-digital (A/D) converters are also shown.

The availability of real-time information about the biological activity is a valuable matter in wastewater treatment employing activated sludge processes, and this is represented by the oxygen uptake rate (OUR). In these processes, OUR measurements have been used as a fast indicator of changes in waste load or influx of toxic organic compounds and for monitoring of the process efficiency. In this paper, we propose a method for OUR estimation by using Kalman filters and PWM control of the dissolved oxygen (DO) concentration in the activated sludge reactor. The proposed method presents a shorter response time than the standard online procedure and a lower measurement uncertainty compared to a previous feedback control method, which estimates the OUR from values of the applied control signal and the DO concentration measurements. Simulations are presented to illustrate the method and experiments are performed in a bench scale activated sludge reactor to show the applicability of the proposed estimator in a real system. The results confirm the fast response of the proposed method and its consistency with respect to the standard procedure for OUR computation.

Thermoelectricity energy harvesting based on the thermoelectric generator (TEG) has had a prominent role in energy harvesting solutions since they have dramatically grown recently due to the existence of significant thermal gradients $\Delta{{\mathrm {T}}}$ in both natural and industrial environments. However, to prove that a given environment is adequate to generate energy is a hard task. In order to early evaluate the potential of a given environment to get enough thermal energy to be converted to electric energy, we propose in this paper an automatic emulation system of thermal energy that can be used with any thermal source in a simple way. Experimental results show that the proposed platform can emulate any thermal gradient pattern, apply this pattern on a TEG and measure the actual electric energy generated by the TEG. An example of application is described, and the results are shown. The example is an experiment to harvest energy from tree trunks.

Water supply systems are constantly improving their operation through energy efficiency actions that involve the use of advanced measurement, control, and automation techniques. The maintenance and reliability of water distribution is directly associated with hydraulic pressure control. The main challenges encountered in hydraulic pressure control are associated with random changes in the supply plant and the presence of noise and outliers in the sensor measurements. These undesired characteristics cause inefficiency and instability in the control system of the pumping stations. In this scenario, this paper proposes an indirect adaptive control methodology by reference model for modeling and controlling water supply systems. The criterion adopted in the parametric estimation mechanism and the controller adaptation is the Maximum Correntropy. Experimental results obtained with an experimental bench plant showed that the maximum tracking error was 15% during demand variation, percentage overshoot less than 5%, and steady-state error less than 2%, and the control system became robust to noise and outliers. In comparison to the Mean Squared Error criterion, when noise and outliers influence the sensor signal, the proposed methodology stands out, reducing the mean error and the standard deviation, in the worst-case scenario, by more than 1500%. The proposed methodology, therefore, allows for increased reliability and efficiency of an advanced pump control system, avoiding downtime and equipment damage.