This paper addresses the problem of predictive diagnostic in high-power transformers. Particularly, this paper is focused on their use in uninterruptible power supply systems for safety critical applications, such as railway interlocking signaling installations. With respect to the state of the art, where typically only thermal and electrical faults are monitored, this work proposes a distributed network of measuring nodes where also vibration-based mechanical stress diagnosis is implemented. Mechanical degradation is tracked through vibration measures, using multichannel accelerometers, with sensitivity down to 0.5 mg and local signal processing in the transformed frequency domain, up to 1 kHz. A compact hardware-software implementation of the nodes is also presented. The performances of the diagnostic system are assessed through experimental measurements on real three-phase high-power transformers used in railway applications

The paper addresses the problem of predictive maintenance in high power supply systems. According to FMECA (Failure Mode, Effects and Criticality Analysis) study key issues for power system reliability are the faults occurring in 3-phase high power transformers. With respect to the state of art where typically only thermal and electrical faults are monitored this work proposes a distributed network of measuring nodes where also vibration-based mechanical stress diagnostic is implemented. Mechanical degradation is tracked through multichannel vibration measures with sensitivity down to 0.5 mg and local processing in the transformed frequency (100 Hz-1 kHz) domain. A compact hardware-software implementing platform is also presented whose performances are assessed through experimental measurements on real high power transformers used in railway applications

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Volatile methylsiloxanes (VMSs) constitute a group of compounds used in a great variety of products, particularly personal care products. Due to their massive use, they are continually discharged into wastewater treatment plants and are increasingly being detected in wastewater and in the environment at low concentrations. The aim of this work was to develop and validate a fast and reliable methodology to screen seven VMSs in water samples, by headspace solid-phase microextraction (HS-SPME) followed by gas chromatography with flame ionization detection (GC-FID). The influence of several factors affecting the extraction efficiency was investigated using a design of experiments approach. The main factors were selected (fiber type, sample volume, ionic strength, extraction and desorption time, extraction and desorption temperature) and optimized, employing a central composite design. The optimal conditions were: 65 µm PDMS/Divinylbenzene fiber, 10 mL sample, 19.5% NaCl, 39 min extraction time, 10 min desorption time, and 33 °C and 240 °C as extraction and desorption temperature, respectively. The methodology was successfully validated, showing low detection limits (up to 24 ng/L), good precision (relative standard deviations below 15%), and accuracy ranging from 62% to 104% in wastewater, tap, and river water samples.

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Muscle fatigue refers to the transient decrease in the capacity to perform physical actions and can cause productivity loss, human errors, unsafe actions, injuries and work-related musculoskeletal disorders (WMSDs). A total of 13 participants repetitively lifted a 2.5 kg load at a total elevation of 0.5 m, until voluntary exhaustion or intensive pain. Several indicators of muscle fatigue were found, including increased forward bending, micro-expressions, changing load support strategy, holding load closer to the chest during elevation and increase in eccentric movement speed. Volunteers that practiced sports regularly lasted longer in the experiment and it was found that smoking and sedentarism limited the exercise capacity of some subjects. Volunteers increased the wrists and elbows velocity during the experiment. It was verified that half of the volunteers had less fluid movement during lifting, with higher acceleration values in some parts and lower values in others, translating into more impulsive movements. It was concluded that to compensate muscle fatigue, people adapt their working strategy, changing movement patterns, recruiting different muscles and changing kinetic or kinematic components of the movement (like joint angles and velocities).