Computational fluid dynamics modeling and in situ physics-based monitoring of aerosol jet printing toward functional assurance of additively-manufactured, flexible and hybrid electronics

Aerosol jet printing (AJP)—a direct-write, additive manufacturing technique—has emerged as the process of choice particularly for the fabrication of flexible and hybrid electronics. AJP has paved the way for high-resolution device fabrication with high placement accuracy, edge definition, and adhesion. In addition, AJP accommodates a broad range of ink viscosity, and allows for printing on non-planer surfaces. Despite the unique advantages and host of strategic applications, AJP is a highly unstable and complex process, prone to gradual drifts in machine behavior and deposited material. Hence, real-time monitoring and control of AJP process is a burgeoning need. In pursuit of this goal, the objectives of the work are, as follows: (i) In situ image acquisition from the traces/lines of printed electronic devices right after deposition. To realize this objective, the AJP experimental setup was instrumented with a high-resolution charge-coupled device (CCD) camera, mounted on a variable-magnification lens (in addition to the standard imaging system, already installed on the AJ printer). (ii) In situ image processing and quantification of the trace morphology. In this regard, several customized image processing algorithms were devised to quantify/extract various aspects of the trace morphology from online images. In addition, based on the concept of shape-from-shading (SfS), several other algorithms were introduced, allowing for not only reconstruction of the 3D profile of the AJ-printed electronic traces, but also quantification of 3D morphology traits, such as thickness, cross-sectional area, and surface roughness, among others. (iii) Development of a supervised multiple-input, single-output (MISO) machine learning model—based on sparse representation for classification (SRC)—with the aim to estimate the device functional properties (e.g., resistance) in near real-time with an accuracy of ≥ 90%. (iv) Forwarding a computational fluid dynamics (CFD) model to explain the underlying aerodynamic phenomena behind aerosol transport and deposition in AJP process, observed experimentally. Overall, this doctoral dissertation paves the way for: (i) implementation of physics-based real-time monitoring and control of AJP process toward conformal material deposition and device fabrication; and (ii) optimal design of direct-write components, such as nozzles, deposition heads, virtual impactors, atomizers, etc

Arc fault protections for aeronautic applications: a review identifying the effects, detection methods, current progress, limitations, future challenges, and research needs

©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Arc faults are serious discharges, damaging insulation systems and triggering electrical fires. This is a transversal topic, affecting from residential to aeronautic applications. Current commercial aircrafts are being progressively equipped with arc fault protections. With the development of more electric aircrafts (MEA), future airliners will require more electrical power to enhance fuel economy, save weight and reduce emissions. The ultimate goal of MEAs is electrical propulsion, where fault management devices will have a leading role, because aircraft safety is of utmost importance. Therefore, current fault management devices must evolve to fulfill the safety requirements of electrical propelled aircrafts. To deal with the increased electrical power generation, the distribution voltage must be raised, thus leading to new electrical fault types, in particular arc tracking and series arcing, which are further promoted by the harsh environments typical of aircraft systems, i.e., low pressure, extreme humidity and a wide range of temperatures. Therefore, the development of specific electrical protections which are able to protect against these fault types is a must. This paper reviews the state-of-the-art of electrical protections for aeronautic applications, identifying the current status and progress, their drawbacks and limitations, the future challenges and research needs to fulfill the future requirements of MEAs, with a special emphasis on series arc faults due to arc tracking, because of difficulty in detecting such low-energy faults in the early stage and the importance and harmful effects of tracking activity in cabling insulation systems. This technological and scientific review is based on a deep analysis of research and conference papers, official reports, white papers and international regulations.This research was partially funded by the Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

Wireless Sensors and Actuators for Structural Health Monitoring of Fiber Composite Materials

This work evaluates and investigates the wireless generation and detection of Lamb-waves on fiber-reinforced materials using surface applied or embedded piezo elements. The general target is to achieve wireless systems or sensor networks for Structural Health Monitoring (SHM), a type of Non-Destructive-Evaluation (NDE). In this sense, a fully wireless measurement system that achieves power transmission implementing inductive coils is reported. This system allows a reduction of total system weight as well as better integration in the structure. A great concern is the characteristics of the material, in which the system is integrated, because the properties can have a direct impact on the strength of the magnetic field. Carbon-Fiber-Reinforced-Polymer (CFRP) is known to behave as an electrical conductor, shielding radio waves with increasing worse effects at higher frequencies. Due to the need of high power and voltage, interest is raised to evaluate the operation of piezo as actuators at the lower frequency ranges. To this end, actuating occurs at the International Scientific and Medical (ISM) band of 125 kHz or low-frequency (LF) range. The feasibility of such system is evaluated extensively in this work. Direct excitation, is done by combining the actuator bonded to the surface or embedded in the material with an inductive LF coil and setting the circuit in resonance. A more controlled possibility, also explored, is the use of electronics to generate a Hanning-windowed-sine to excite the PWAS in a narrow spectrum. In this case, only wireless power is transmitted to the actuator node, and this lastly implements a Piezo-driver to independently excite Lamb-waves. Sensing and data transfer, on the other hand, is done using the high-frequency (HF) 13.56 MHz. The HF range covers the requirements of faster sampling rate and lower energy content. A re-tuning of the antenna coils is performed to obtain better transmission qualities when the system is implemented in CFRP. Several quasi-isotropic (QI) CFRP plates with sensor and actuator nodes were made to measure the quality of transmission and the necessary energy to stimulate the actuator-sensor system. In order to produce baselines, measurements are prepared from a healthy plate under specific temperature and humidity conditions. The signals are evaluated to verify the functionality in the presence of defects. The measurements demonstrate that it is possible to wirelessly generate Lamb-waves while early results show the feasibility to determine the presence of structural failure. For instance, progress has been achieved detecting the presence of a failure in the form of drilled holes introduced to the structure. This work shows a complete set of experimental results of different sensor/-actuator nodes

Advanced Process Monitoring for Industry 4.0

This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and “extreme data” conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Design and Development of Robotic Part Assembly System under Vision Guidance

Robots are widely used for part assembly across manufacturing industries to attain high productivity through automation. The automated mechanical part assembly system contributes a major share in production process. An appropriate vision guided robotic assembly system further minimizes the lead time and improve quality of the end product by suitable object detection methods and robot control strategies. An approach is made for the development of robotic part assembly system with the aid of industrial vision system. This approach is accomplished mainly in three phases. The first phase of research is mainly focused on feature extraction and object detection techniques. A hybrid edge detection method is developed by combining both fuzzy inference rule and wavelet transformation. The performance of this edge detector is quantitatively analysed and compared with widely used edge detectors like Canny, Sobel, Prewitt, mathematical morphology based, Robert, Laplacian of Gaussian and wavelet transformation based. A comparative study is performed for choosing a suitable corner detection method. The corner detection technique used in the study are curvature scale space, Wang-Brady and Harris method. The successful implementation of vision guided robotic system is dependent on the system configuration like eye-in-hand or eye-to-hand. In this configuration, there may be a case that the captured images of the parts is corrupted by geometric transformation such as scaling, rotation, translation and blurring due to camera or robot motion. Considering such issue, an image reconstruction method is proposed by using orthogonal Zernike moment invariants. The suggested method uses a selection process of moment order to reconstruct the affected image. This enables the object detection method efficient. In the second phase, the proposed system is developed by integrating the vision system and robot system. The proposed feature extraction and object detection methods are tested and found efficient for the purpose. In the third stage, robot navigation based on visual feedback are proposed. In the control scheme, general moment invariants, Legendre moment and Zernike moment invariants are used. The selection of best combination of visual features are performed by measuring the hamming distance between all possible combinations of visual features. This results in finding the best combination that makes the image based visual servoing control efficient. An indirect method is employed in determining the moment invariants for Legendre moment and Zernike moment. These moments are used as they are robust to noise. The control laws, based on these three global feature of image, perform efficiently to navigate the robot in the desire environment

On-line measurement of partial discharges in high voltage rotating machines.

The on-line condition monitoring of rotating machines is given paramount importance, particularly in Oils and Gas industries where the financial implications of machine shutdown is very high. This project work was directed towards the on-line condition monitoring of high voltage rotating machines by detection of partial discharges (PD) which are indicative of stator insulation degradation. Partial discharge manifests itself in various forms which can be detected using various electrical and non-electrical techniques. The electrical method of detecting small current pulses generated by PD using a Rogowski coil as a sensor has been investigated in this work. Dowding & Mills, who are commercially involved in the condition monitoring of rotating machines, currently use a system called StatorMonotor® for PD detection. The research is intended to develop a new partial discharge detection system that will replace the existing system which is getting obsolete. A three phase partial discharge detection unit was specified, designed and developed that is capable of filtering, amplifying and digitising the discharge signals. The associated data acquisition software was developed using LabVIEW software that was capable of acquiring, displaying and storing the discharge signals. Additional software programs were devised to investigate the removal of external noise. A data compression algorithm was developed to store the discharge data in an efficient manner; also ensuring the backward compatibility to the existing analysis software. Tests were performed in laboratory and on machines on-site and the results are presented. Finally, the data acquisition (DAQ) cards that used the PCMCIA bus was replaced with new USB based DAQ cards with the software modified accordingly. The three phase data acquisition unit developed as a result of this project has produced encouraging results and will be implemented in an industrial environment to evaluate and benchmark its performance with the existing system. Most importantly, a hardware data acquisition platform for the detection of PD pulses has been established within the company which is easily maintainable and expandable to suit any future requirements

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity