Sensors (Basel, Switzerland)
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Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. ⋯ However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.
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The possibility of reliable, reasonably accurate and relatively inexpensive estimates of sensible heat and latent energy fluxes was investigated using a commercial combination thin-film polymer capacitive relative humidity and adjacent temperature sensor instrument. Long-term and unattended water vapour pressure profile difference measurements using low-power combination instruments were compared with those from a cooled dewpoint mirror hygrometer, the latter often used with Bowen ratio energy balance (BREB) systems. An error analysis, based on instrument relative humidity and temperature errors, was applied for various capacitive humidity instrument models. ⋯ This reasonable agreement showed that a combination capacitive humidity instrument, with similar relative humidity (RH) and temperature error magnitudes of at most 2% RH and 0.3 °C respectively, and similar measurement time response, would be an adequate and less expensive substitute for a dewpoint hygrometer. Furthermore, a combination capacitive humidity instrument requires no servicing compared to a dewpoint hygrometer which requires a bias adjustment and mirror cleaning each week. These findings make unattended BREB measurements of sensible heat flux and evaporation cheaper and more reliable with the system easier to assemble and service and with reduced instrument power.
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A mobile asset with a sensor node in a mobile asset tracking system moves around a monitoring area, leaves it, and then returns to the region repeatedly. The system monitors the in/out status of the mobile asset. Due to the continuous movement of the mobile asset, the system may generate an error for the in/out status of the mobile asset. ⋯ The battery lifetime is used to predict a valid working period for the mobile node. We evaluate our method using real data generated by a medical asset tracking system. The experimental results show that our method, by using the estimated battery life time or by using the invalid connection state, can detect and correct most cases of incorrect in/out statuses generated by the conventional approach.
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One of the current challenges in medicine is monitoring the patients' depth of general anaesthesia (DGA). Accurate assessment of the depth of anaesthesia contributes to tailoring drug administration to the individual patient, thus preventing awareness or excessive anaesthetic depth and improving patients' outcomes. In the past decade, there has been a significant increase in the number of studies on the development, comparison and validation of commercial devices that estimate the DGA by analyzing electrical activity of the brain (i.e., evoked potentials or brain waves). In this paper we review the most frequently used sensors and mathematical methods for monitoring the DGA, their validation in clinical practice and discuss the central question of whether these approaches can, compared to other conventional methods, reduce the risk of patient awareness during surgical procedures.
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The emergence of wireless technologies and advancements in on-body sensor design can enable change in the conventional health-care system, replacing it with wearable health-care systems, centred on the individual. Wearable monitoring systems can provide continuous physiological data, as well as better information regarding the general health of individuals. ⋯ In this paper, recent progress in non-invasive monitoring technologies for chronic disease management is reviewed. In particular, devices and techniques for monitoring blood pressure, blood glucose levels, cardiac activity and respiratory activity are discussed; in addition, on-body propagation issues for multiple sensors are presented.