This paper analyzes and presents the detection of mono and combined short-circuit, broken bar and static eccentricity based on harmonics of stator current of a squirrel-cage induction motor using 3D finite element models.

The article presents the importance of renewable energy in reducing the potential dangers of global warming and climate crises in the context of increase in global energy comp Sumption that will lead to increase of emission of greenhouse gases. to and of the maintenance in solar energy systems. The operation and maintenance activities of photovoltaic systems represent aspects not to be neglected for obtaining the profitability of investments and ensuring their viability and reliability. Currently, the procedures applied mainly refer to simple techniques such as visual inspection and scheduled maintenance strategies. Also, the types of faults that can may appear in photovoltaic panels and the ones can be detected by thermography (single hot spot, multiple hot spots, activation of the bypass diode and a higher temperature of the junction box) are presented with their characteristics and severity. In the last part of the article a thermal imaging processing software based on artificial intelligence technology is proposed for use for the preventive maintenance, in order to detect the photovoltaic(solar) panels with faults to be repaired or changed to increase the efference of the system. The Software will be use to develop an innovative maintenance and repair curricula for the departments related to solar energy in vocational and technical education schools in order to better predict and prevent malfunctions in solar energy systems.

This paper studies the influence on the magnetic field outside induction motors of a short-circuit fault in the stator winding through experimental investigations and time domain finite element analysis of the electromagnetic field. The detection of the stator short-circuit fault is the result of the comparison of amplitudes of particular harmonics of the output voltage of coil sensors placed around the motor, for the healthy and faulty motor states, for no-load and loaded motor operation. A detection system with two identical coil sensors ensures increased efficiency of fault detection and offers the possibility to identify the position of the faulty coil inside the motor.

The use of smart technologies and the Internet of Things (IoT) is becoming more and more popular in order to enhance the overall building performance by monitoring parameters related to occupants’ comfort and health in the built environment. A new modular, custom-made and replicable IoT system is proposed based on an Arduino development board (MKR WiFi 1010) connected to the Arduino IoT Cloud. An Application Programming Interface (API) enables the integration of this system with other possible ones, thus making the system modular, custom-made and replicable. A series of parameters were simultaneously monitored over a 7-day period in two office spaces and a photovoltaic (PV)-testing laboratory. While the meteorological and comfort parameters (temperature, relative humidity, CO₂) were monitored in all three spaces, the health parameters (total volatile organic compounds—TVOCs; formaldehyde—HCHO; particulate matter—PM; and radon—²²²Rn) were monitored only in an office setup located right next to a Chemical Analysis and Testing Laboratory. Generally, the registered values of the health parameters fell within the recommended thresholds. However, the thermal comfort parameters were constantly exceeded: over 90% of the working time in the two office spaces and 83.33% in the PV-testing laboratory. Still, the optimal relative humidity values in the monitored spaces contributed to the discomfort reduction in the occupants. Also, CO₂ and TVOCs had some exceptions in particular conditions. CO₂ values of up to 1500 ppm due to poor ventilation and TVOC levels of up to 1000 ppb related to chemical experiment development were registered. Also, several other peaks were recorded when monitoring HCHO as well as PM. Thus, special attention must be paid to natural ventilation or to the improvement of building characteristics. Also, the time intervals when experiments in the Chemical Analysis and Testing Laboratory are carried out should be communicated to other personnel from the nearest offices. The testing of the monitoring system over a one-week period showed that the proposed solution operated adequately, representing a reliable tool for data acquisition via the Arduino IoT Cloud.

Based on the finite element analysis of the electromagnetic field in time domain, this paper studies effects of the short-circuit faults in the stator winding of an induction motor and the influence of this fault on the magnetic field outside the motor. The detection of the short-circuit fault through the magnetic field is based on the comparison of harmonics of the output voltage of coil sensors for the healthy and faulty motor states. The influence of the magnetic saturation of the motor on the fault diagnose efficiency is studied.

This paper relates to the detection of the short-circuit faults in the stator winding of induction motors. Amplitudes of harmonics of the stator currents and of the magnetic field outside the motor are evaluated through the finite element analyses of the 3D electromagnetic field in time domain. In the perspective of early faults detection, the evolution of short-circuit faults based on changing of the amplitude of particular harmonics of the stator currents or of the magnetic field is studied.