Detectability evaluation of attributes anomaly for electronic components using pulsed thermography

Counterfeit Electronic Components (CECs) pose a serious threat to all intellectual properties and bring fatal failure to the key industrial systems. This paper initiates the exploration of the prospect of CEC detection using pulsed thermography (PT) by proposing a detectability evaluation method for material and structural anomalies in CECs. Firstly, a numerical Finite Element Modelling (FEM) simulation approach of CEC detection using PT was established to predict the thermal response of electronic components under the heat excitation. Then, by experimental validation, FEM simulates multiple models with attribute deviations in mould compound conductivity, mould compound volumetric heat capacity and die size respectively considering experimental noise. Secondly, based on principal components analysis (PCA), the gradients of the 1st and 2nd principal components are extracted and identified as two promising classification features of distinguishing the deviation models. Thirdly, a supervised machine learning-based method was applied to classify the features to identify the range of detectability. By defining the 90% of classification accuracy as the detectable threshold, the detectability ranges of deviation in three attributes have been quantitively evaluated respectively. The promising results suggest that PT can act as a concise, operable and cost-efficient tool for CECs screening which has the potential to be embedded in the initial large scale screening stage for anti-counterfeit

Health Condition Assessment of Multi-Chip IGBT Module with Magnetic Flux Density

To achieve efficient conversion and flexible control of electronic energy, insulated gate bipolar transistor (IGBT) power modules as the dominant power semiconductor devices are increasingly applied in many areas such as electric drives, hybrid electric vehicles, railways, and renewable energy systems. It is known that IGBTs are the most vulnerable components in power converter systems. To achieve high power density and high current capability, several IGBT chips are connected in parallel as a multi-chip IGBT module, which makes the power modules less reliable due to a more complex structure. The lowered reliability of IGBT modules will not only cause safety problems but also increase operation costs due to the failure of IGBT modules. Therefore, the reliability of IGBTs is important for the overall system, especially in high power applications. To improve the reliability of IGBT modules, this thesis proposes a new health state assessment model with a more sensitive precursor parameter for multi-chip IGBT module that allows for condition-based maintenance and replacement prior to complete failure. Accurate health condition monitoring depends on the knowledge of failure mechanism and the selection of highly sensitive failure precursor. IGBT modules normally wear out and fail due to thermal cycling and operating environment. To enhance the understanding of the failure mechanism and the external characteristic performance of multi-chip IGBT modules, an electro-thermal finite element model (FEM) of a multi-chip IGBT module used in wind turbine converter systems was established with considerations for temperature dependence of material property, the thermal coupling effect between components, and the heat transfer process. The electro-thermal FEM accurately performed temperature distribution and the distribution electrical characteristic parameters during chip solder degradation. This study found an increased junction temperature, large change of temperature distribution, and more serious imbalanced current sharing during a single chip solder aging, thereby accelerating the aging of the whole IGBT module. According to the change of thermal and electrical parameters with chip solder fatigue, the sensitivity of fatigue sensitive parameters (FSPs) was analyzed. The collector current of the aging chip showed the highest sensitivity with the chip solder degradation compared with the junction temperature, case temperature, and collector-emitter voltage. However, the current distribution of internal components remains inaccessible through direct measurements or visual inspection due to the package. As the relationship between the current and magnetic field has been studied and gradually applied in sensor technologies, magnetic flux density was proposed instead of collector current as a new precursor for health condition monitoring. Magnetic flux density distribution was extracted by an electro-thermal-magnetic FEM of the multi-chip IGBT module based on electromagnetic theory. Simulation results showed that magnetic flux density had even higher sensitivity than collector current with chip solder degradation. In addition, the magnetic flux density was only related with the current and was not influenced by temperature, which suggested good selectivity. Therefore, the magnetic flux density was selected as the precursor due to its better sensitivity, selectivity, and generality. Finally, a health state assessment model based on backpropagation neural network (BPNN) was established according to the selected precursor. To localize and evaluate chip solder degradation, the health state of the IGBT module was determined by the magnetic flux density for each chip and the corresponding operating conduction current. BPNN featured good self-learning, self-adapting, robustness and generalization ability to deal with the nonlinear relationship between the four inputs and health state. Experimental results showed that the proposed model was accurate and effective. The health status of the IGBT modules was effectively recognized with an overall recognition rate of 99.8%. Therefore, the health state assessment model built in this thesis can accurately evaluate current health state of the IGBT module and support condition-based maintenance of the IGBT module

Characterisation and probability of detection analysis of rolling contact fatigue cracks in rails using eddy current pulsed thermography

PhD ThesisWith transportation volumes continuously increasing, railway networks are now facing problems of greater axle loads and increasing vehicle speeds. The most direct consequence is the initiation of rolling contact fatigue (RCF) defects in rails, which have become safety issues for all types of railway systems and received more attention due to lack of timely examination and management. Among different RCF defects, the RCF crack probably presents the biggest hazard in rails. Detection and characterisation of RCF cracks aim to provide detailed guidelines for safety management and preventative grinding. Unfortunately, current nondestructive testing and evaluation techniques are still facing several challenges and research gaps. One outstanding challenge is the characterisation of RCF cracks under their complex geometries and clustered distributions. One major research gap is how to evaluate the probabilistic performance in crack characterisation via a proper framework. By combining the advantages of eddy current pulse excitation and infrared thermography, this thesis proposes the use of eddy current pulsed thermography (ECPT) technique to address the detection and characterisation of RCF cracks in rails. To quantitatively investigate the ECPT’s performance in crack characterisation, a performance evaluation framework based on probability of detection (POD) analysis is proposed. The major contributions of the thesis are summarised as follows: (1) implementations of three-dimensional FEM models and a lab-based ECPT system for investigating the characterisation of RCF cracks under clustered distributions and geometric influences; (2) temporal/spatial-thermal-feature-based ECPT for angular slots and RCF cracks detection and characterisation; (3) investigations into the capability and the performance of ECPT for characterising angular slots and natural RCF cracks via a POD analysis framework. The thesis concludes that the proposed feature-based ECPT system can characterise RCF cracks in both light and moderate stages. Based on feature comparison and POD evaluation, tempo-spatial-based patterns are better fits for pocket length characterisation. Temporal domain-based features show better performances for inclination angle characterisation. A spatial domain-based feature, SST, can characterise vertical depths with reasonable POD values. One tempo-spatial-based pattern at the early heating stage, IET-PCA, gives the best performance for characterising surface lengths. Still, several issues need to be further investigated in future work, such as feature selection for crack characterisation, three-dimensional reconstruction of RCF cracks, model-assisted POD frameworks for improving the effectiveness of POD analysis with a limited number of physical specimens

Online junction temperature estimation of siC power MOSFETS

PhD ThesisSilicon Carbide (SiC) based power devices receive more and more popularity in the field of power electronics as they operate at higher voltages, higher switching frequencies and higher temperatures compared to traditional Silicon (Si) based power modules. As for SiC-based power devices, the temperature of SiC chip must be monitored in order to operate the device within its limit. However, it is not straight forward to directly measure the junction temperature (Tj) of a power device non-intrusively due to the package obstruction. Therefore, indirect Tj measurement methods like Temperature Sensitive Electrical Parameters (TSEPs) are preferred by researchers and been intensively investigated for Si devices as the dominant power devices in the past. However, those TSEPs which are effective for Si devices are mostly not applicable to SiC devices. This is due to different physical and electrical behaviour between SiC-based device and Si-based device. Thus, it is necessary to develop new method to implement indirect Tj measurement for SiC devices. This thesis presents a new on-line technique to estimate the Tj of discrete SiC MOSFET devices. In this work, small amplitude, high frequency chirp signals are injected into the gate of a discrete SiC device during its off-state operation. Then, the gate-source voltage (VGS) is measured and its frequency response (FR) characteristic is determined by using Discrete Fast Fourier Transform (DFFT) analysis. The captured VGS signal is a direct function of the gate-source loop impedance. The derived function becomes a linear function in respect Tj as it represents only the resistive elements of the gate-source loop. As the gate channel resistance of the SiC MOSFET (Rint) is the largest resistance in that loop and it is temperature dependent. As a result, the temperature of the SiC MOSFET chip can be estimated. The new method in the thesis will be explained in details and the theory will be backed up by analytical simulations. A 3D numerical model for the discrete SiC MOSFET is also established and simulated. Furthermore, a network analyser is used for initial validation of the new method and finally a boost circuit was built with signal injection circuit integrated within the gate driver circuit to demonstrate the feasibility of using this innovative method to extract junction temperature of a discrete SiC MOSFET

Spark-Plasma Sintering and Related Field-Assisted Powder Consolidation Technologies

Electromagnetic field-assisted sintering techniques have increasingly attracted attention of scientists and technologists. Spark-plasma sintering (SPS) and other field-assisted powder consolidation approaches provide remarkable capabilities to the processing of materials into configurations previously unattainable. Of particular significance is the possibility of using very fast heating rates, which, coupled with the field-assisted mass transport, stand behind the purported ability to achieve high densities during consolidation and to maintain the nanostructure of consolidated materials via these techniques. Potentially, SPS and related technologies have many significant advantages over the conventional powder processing methods, including the lower process temperature, the shorter holding time, dramatically improved properties of sintered products, low manufacturing costs, and environmental friendliness

Effect of water on electrical properties of Refined, Bleached, and Deodorized Palm Oil (RBDPO) as electrical insulating material

This paper describes the properties of refined, bleached, deodorized palm oil (RBDPO) as having the potential to be used as insulating liquid. There are several important properties such as electrical breakdown, dielectric dissipation factor, specific gravity, flash point, viscosity and pour point of RBDPO that was measured and compared to commercial mineral oil which is largely in current use as insulating liquid in power transformers. Experimental results of the electrical properties revealed that the average breakdown voltage of the RBDPO sample, without the addition of water at room temperature, is 13.368 kV. The result also revealed that due to effect of water, the breakdown voltage is lower than that of commercial mineral oil (Hyrax). However, the flash point and the pour point of RBDPO is very high compared to mineral oil thus giving it advantageous possibility to be used safely as insulating liquid. The results showed that RBDPO is greatly influenced by water, causing the breakdown voltage to decrease and the dissipation factor to increase; this is attributable to the high amounts of dissolved water

Industrial and Technological Applications of Power Electronics Systems

The Special Issue "Industrial and Technological Applications of Power Electronics Systems" focuses on: - new strategies of control for electric machines, including sensorless control and fault diagnosis; - existing and emerging industrial applications of GaN and SiC-based converters; - modern methods for electromagnetic compatibility. The book covers topics such as control systems, fault diagnosis, converters, inverters, and electromagnetic interference in power electronics systems. The Special Issue includes 19 scientific papers by industry experts and worldwide professors in the area of electrical engineering

Feature Papers in Electronic Materials Section

This book entitled "Feature Papers in Electronic Materials Section" is a collection of selected papers recently published on the journal Materials, focusing on the latest advances in electronic materials and devices in different fields (e.g., power- and high-frequency electronics, optoelectronic devices, detectors, etc.). In the first part of the book, many articles are dedicated to wide band gap semiconductors (e.g., SiC, GaN, Ga2O3, diamond), focusing on the current relevant materials and devices technology issues. The second part of the book is a miscellaneous of other electronics materials for various applications, including two-dimensional materials for optoelectronic and high-frequency devices. Finally, some recent advances in materials and flexible sensors for bioelectronics and medical applications are presented at the end of the book

Innovation: Key to the future

The NASA Marshall Space Flight Center Annual Report is presented. A description of research and development projects is included. Topics covered include: space science; space systems; transportation systems; astronomy and astrophysics; earth sciences; solar terrestrial physics; microgravity science; diagnostic and inspection system; information, electronic, and optical systems; materials and manufacturing; propulsion; and structures and dynamics