No abstract

This paper proposes a new method to develop a thermal model of an insulated gate bipolar transistor (IGBT) employing an optical fiber sensor mounted on the chip structure. Some features of the sensor such as electromagnetic immunity, small size and fast response time, allow the identification of temperature changes generated by the energy loss during device operation through direct measurement. In fact, this measurement method is considered impossible with conventional sensors. The online monitoring of the junction temperature enables identify the thermal characteristics of the IGBT. The results are used to develop an accurate model to simulate the heat generated during the device conduction and switching processes. The model showed a difference of only 0.3% between measured and simulated results, besides allowing evaluate separately the heat generated by each turn-ON/OFF process.

No abstract

No abstract

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

No abstract

No abstract

Fiber Bragg grating (FBG) sensors are used to investigate the temperature dynamics of a three-phase induction motor under different supply conditions and also during startup. The temperature field distribution is monitored using eight uniformly distributed FBGs in the stator. Tests are performed with the motor running at no load and with intentional voltage disturbances in the motor feed. It is observed that the temperature distribution in the stator is not uniform either with or without a balanced voltage in the windings. An average level increase in temperature of 0.5°C is registered for all of the sensors and associated with the unbalanced voltage in the windings. The motor under the test is kept at synchronous speed and connected to a second motor to determine the temperature rise due to mechanical and stator losses. An increase in temperature of 4.5°C due to mechanical losses is registered as well as an increase of 15.5°C due to stator winding and stator iron losses.Index Terms-Fiber optic Bragg grating sensors, induction motor, thermoelectric behavior, unbalanced voltage supply.