João Paulo Bazzo

Thermal Imaging of Hydroelectric Generator Stator Using a DTS System

This paper presents a new method for thermal imaging of hydroelectric generators stators. The method is based on distributed temperature optical fiber sensing using Raman scattering. The thermal image is generated by combining the information of temperature and the spatial position of the sensor with the 3-D model of the structure. Regarding the use of conventional sensors, such as resistance temperature detector or PT100, the main advantage is the possibility to identify temperature variations over the entire stator surface. The results were obtained over a 22-h test with a 200-MW hydroelectric generator. The produced thermal images showed a great potential for monitoring the temperature distribution in the stator according to the generator load. The new method can contribute for identification of fault in the structure insulation, which when early identified can reduce damage caused by short circuit in the stator windings.

Digital control system using a thermoelectric cell for temperature electronic devices testing

This paper presents a temperature digital control system for performance evaluation of electronic devices under different operating temperatures. The system is based on a thermoelectric module of Peltier effect, which is used for heating or cooling the device under test (DUT). A digital PI controller is designed through simulations with an electric model of the structure, developed in Simulink®. Based on the parameters and results from simulations, the controller is implemented in Labview® and experimental results are obtained using a servo amplifier like actuator.

Improving Spatial Resolution of Raman DTS Using Total Variation Deconvolution

Traditional Raman distributed optical sensor (DTS) exhibits a low-pass characteristic that causes sharp temperature changes to be over smoothed. This behavior can be modeled as the convolution of the real temperature profile with the DTS impulse response. This paper presents a deconvolution algorithm developed to improve the spatial resolution of a Raman DTS system. The algorithm is based on a linear DTS model and total variation regularization. The main advantage is the ability to correctly reconstruct hot regions with dimensions down to 15 cm, which represents a resolution gain of up to six times when compared with the DTS spatial resolution of 1 m. We present simulations and experimental results demonstrating the efficacy of the proposed method.

Monitoring the junction temperature of an IGBT through direct measurement using a fiber Bragg grating

This paper proposes a new technique to monitor the junction temperature of an insulated gate bipolar transistor (IGBT) through direct measurement using 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. In addition to the online monitoring of the junction temperature, results show the thermal characteristics of the IGBT, which can be used to develop an accurate model to simulate the heat generated during the device conduction and switching processes.

Performance evaluation of an IGBT module by thermal analysis using fiber Bragg grating

This paper proposes a new method to estimate the energy losses in insulated gate bipolar transistors (IGBT) modules. The technique is based on measuring the temperature of the semiconductor junction through optical sensors based on fiber Bragg gratings. The IGBT module is monitored through software, enabling a real-time evaluation of performance, which facilitates the analysis of the device in different operating conditions. The results are compared with conventional techniques to validate the method.

Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring

This paper presents an image reconstruction method to monitor the temperature distribution of electric generator stators. The main objective is to identify insulation failures that may arise as hotspots in the structure. The method is based on temperature readings of fiber optic distributed sensors (DTS) and a sparse reconstruction algorithm. Thermal images of the structure are formed by appropriately combining atoms of a dictionary of hotspots, which was constructed by finite element simulation with a multi-physical model. Due to difficulties for reproducing insulation faults in real stator structure, experimental tests were performed using a prototype similar to the real structure. The results demonstrate the ability of the proposed method to reconstruct images of hotspots with dimensions down to 15 cm, representing a resolution gain of up to six times when compared to the DTS spatial resolution. In addition, satisfactory results were also obtained to detect hotspots with only 5 cm. The application of the proposed algorithm for thermal imaging of generator stators can contribute to the identification of insulation faults in early stages, thereby avoiding catastrophic damage to the structure.

Temperature Sensing of High Power Generator Stator using DTS

Stator surface temperature monitoring of a 182 MW hydroelectric generator using DTS is presented. The main advantage of this approach over conventional sensors is the possibility to identify temperature variations over with high spatial resolution.

Optical fiber Bragg grating sensors applied on energy conversion systems

This paper presents the applications of optical fiber Bragg grating (FBG) sensors in energy conversion systems developed by the Photonic Engineering Research Group at UTFPR over the last few years. The results show the monitoring of an IBGT module and the determination of its thermal model, temperature characterization of an induction motor and of a 6.5 MW power generator exciter bridge, and high temperature measurement of the intake gases of locomotive diesel engine turbines. All experiments are introduced and discussed in details in the following sessions.

Super-resolution algorithm applied in thermal imaging of hydroelectric generators stator using hybrid sensing with DTS and FBG

This paper presents a super-resolution algorithm developed to improve a thermal imaging system based on distributed optical sensors (DTS). The super-resolution is achieved by additional information provided by localized FBG sensors. The combination of the two types of sensors is an alternative to compensate the limitations of DTS due to spatial resolution of 1 m. The algorithm is applied to a thermal imaging system for monitoring stator temperature of hydroelectric generators, and the main advantage is the possibility to identify hotspots with dimensions up 10 times smaller than DTS spatial resolution.

200 MW hydroelectric generator stator surface temperature monitoring using a DTS system

A distributed temperature sensing (DTS) system is used to monitor the surface temperature of a high power hydroelectric generator. Two sensing fibers were installed; one is bare fiber whilst the other is jacketed with a Teflon® protection, in two distinct configurations: first, they were fixed parallel to the stator bars; secondly, they were wrapped around the stator surface. The fibers were embedded on the stator surface by using an electrically insulating resin which does not interfere with the generator operation. This technique can be used as a predictive maintenance tool.