Measurements, Models, Systems and Design

531 s.

Artificial neural networks and their applications to intelligent fault diagnosis of power transmission lines

Over the past thirty years, the idea of computing based on models inspired by human brains and biological neural networks emerged. Artificial neural networks play an important role in the field of machine learning and hold the key to the success of performing many intelligent tasks by machines. They are used in various applications such as pattern recognition, data classification, stock market prediction, aerospace, weather forecasting, control systems, intelligent automation, robotics, and healthcare. Their architectures generally consist of an input layer, multiple hidden layers, and one output layer. They can be implemented on software or hardware. Nowadays, various structures with various names exist for artificial neural networks, each of which has its own particular applications. Those used types in this study include feedforward neural networks, convolutional neural networks, and general regression neural networks. Increasing the number of layers in artificial neural networks as needed for large datasets, implies increased computational expenses. Therefore, besides these basic structures in deep learning, some advanced techniques are proposed to overcome the drawbacks of original structures in deep learning such as transfer learning, federated learning, and reinforcement learning. Furthermore, implementing artificial neural networks in hardware gives scientists and engineers the chance to perform high-dimensional and big data-related tasks because it removes the constraints of memory access time defined as the von Neuman bottleneck. Accordingly, analog and digital circuits are used for artificial neural network implementations without using general-purpose CPUs. In this study, the problem of fault detection, identification, and location estimation of transmission lines is studied and various deep learning approaches are implemented and designed as solutions. This research work focuses on the transmission lines’ datasets, their faults, and the importance of identification, detection, and location estimation of them. It also includes a comprehensive review of the previous studies to perform these three tasks. The application of various artificial neural networks such as feedforward neural networks, convolutional neural networks, and general regression neural networks for identification, detection, and location estimation of transmission line datasets are also discussed in this study. Some advanced methods based on artificial neural networks are taken into account in this thesis such as the transfer learning technique. These methodologies are designed and applied on transmission line datasets to enable the scientist and engineers with using fewer data points for the training purpose and wasting less time on the training step. This work also proposes a transfer learning-based technique for distinguishing faulty and non-faulty insulators in transmission line images. Besides, an effective design for an activation function of the artificial neural networks is proposed in this thesis. Using hyperbolic tangent as an activation function in artificial neural networks has several benefits including inclusiveness and high accuracy

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Investigation of radiation-hardened design of electronic systems with applications to post-accident monitoring for nuclear power plants

This research aims at improving the robustness of electronic systems used-in high level radiation environments by combining with radiation-hardened (rad-hardened) design and fault-tolerant techniques based on commercial off-the-shelf (COTS) components. A specific of the research is to use such systems for wireless post-accident monitoring in nuclear power plants (NPPs). More specifically, the following methods and systems are developed and investigated to accomplish expected research objectives: analysis of radiation responses, design of a radiation-tolerant system, implementation of a wireless post-accident monitoring system for NPPs, performance evaluation without repeat physical tests, and experimental validation in a radiation environment. A method is developed to analyze ionizing radiation responses of COTS-based devices and circuits in various radiation conditions, which can be applied to design circuits robust to ionizing radiation effects without repeated destructive tests in a physical radiation environment. Some mathematical models of semiconductor devices for post-irradiation conditions are investigated, and their radiation responses are analyzed using Technology Computer Aided Design (TCAD) simulator. Those models are then used in the analysis of circuits and systems under radiation condition. Based on the simulation results, method of rapid power off may be effectively to protect electronic systems under ionizing radiation. It can be a potential solution to mitigate damages of electronic components caused by radiation. With simulation studies of photocurrent responses of semiconductor devices, two methods are presented to mitigate the damages of total ionizing dose: component selection and radiation shielding protection. According to the investigation of radiation-tolerance of regular COTS components, most COTS-based semiconductor components may experience performance degradation and radiation damages when the total dose is greater than 20 K Rad (Si). A principle of component selection is given to obtain the suitable components, as well as a method is proposed to assess the component reliability under radiation environments, which uses radiation degradation factors, instead of the usual failure rate data in the reliability model. Radiation degradation factor is as the input to describe the radiation response of a component under a total radiation dose. In addition, a number of typical semiconductor components are also selected as the candidate components for the application of wireless monitoring in nuclear power plants. On the other hand, a multi-layer shielding protection is used to reduce the total dose to be less than 20 K Rad (Si) for a given radiation condition; the selected semiconductor devices can then survive in the radiation condition with the reduced total dose. The calculation method of required shielding thickness is also proposed to achieve the design objectives. Several shielding solutions are also developed and compared for applications in wireless monitoring system in nuclear power plants. A radiation-tolerant architecture is proposed to allow COTS-based electronic systems to be used in high-level radiation environments without using rad-hardened components. Regular COTS components are used with some fault-tolerant techniques to mitigate damages of the system through redundancy, online fault detection, real-time preventive remedial actions, and rapid power off. The functions of measurement, processing, communication, and fault-tolerance are integrated locally within all channels without additional detection units. A hardware emulation bench with redundant channels is constructed to verify the effectiveness of the developed radiation-tolerant architecture. Experimental results have shown that the developed architecture works effectively and redundant channels can switch smoothly in 500 milliseconds or less when a single fault or multiple faults occur. An online mechanism is also investigated to timely detect and diagnose radiation damages in the developed redundant architecture for its radiation tolerance enhancement. This is implemented by the built-in-test technique. A number of tests by using fault injection techniques have been carried out in the developed hardware emulation bench to validate the proposed detection mechanism. The test results have shown that faults and errors can be effectively detected and diagnosed. For the developed redundant wireless devices under given radiation dose (20 K Rad (Si)), the fault detection coverage is about 62.11%. This level of protection could be improved further by putting more resources (CPU consumption, etc.) into the function of fault detection, but the cost will increase. To apply the above investigated techniques and systems, under a severe accident condition in a nuclear power plant, a prototype of wireless post-accident monitoring system (WPAMS) is designed and constructed. Specifically, the radiation-tolerant wireless device is implemented with redundant and diversified channels. The developed system operates effectively to measure up-to-date information from a specific area/process and to transmit that information to remote monitoring station wirelessly. Hence, the correctness of the proposed architecture and approaches in this research has been successfully validated. In the design phase, an assessment method without performing repeated destructive physical tests is investigated to evaluate the radiation-tolerance of electronic systems by combining the evaluation of radiation protection and the analysis of the system reliability under the given radiation conditions. The results of the assessment studies have shown that, under given radiation conditions, the reliability of the developed radiation-tolerant wireless system can be much higher than those of non-redundant channels; and it can work in high-level radiation environments with total dose up to 1 M Rad (Si). Finally, a number of total dose tests are performed to investigate radiation effects induced by gamma radiation on distinct modern wireless monitoring devices. An experimental setup is developed to monitor the performance of signal measurement online and transmission of the developed distinct wireless electronic devices directly under gamma radiator at The Ohio State University Nuclear Reactor Lab (OSU-NRL). The gamma irradiator generates dose rates of 20 K Rad/h and 200 Rad/h on the samples, respectively. It was found that both measurement and transmission functions of distinct wireless measurement and transmission devices work well under gamma radiation conditions before the devices permanently damage. The experimental results have also shown that the developed radiation-tolerant design can be applied to effectively extend the lifespan of COTS-based electronic systems in the high-level radiation environment, as well as to improve the performance of wireless communication systems. According to testing results, the developed radiation-tolerant wireless device with a shielding protection can work at least 21 hours under the highest dose rate (20 K Rad/h). In summary, this research has addressed important issues on the design of radiation-tolerant systems without using rad-hardened electronic components. The proposed methods and systems provide an effective and economical solution to implement monitoring systems for obtaining up-to-date information in high-level radiation environments. The reported contributions are of significance both academically and in practice

Deep Learning-Based Machinery Fault Diagnostics

This book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis

MFPA: Mixed-Signal Field Programmable Array for Energy-Aware Compressive Signal Processing

Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the MFPA (Mixed-signal Field Programmable Array) approach is presented as a hybrid spin-CMOS reconfigurable fabric specifically designed for implementation of CS data sampling and signal reconstruction. The resulting fabric consists of 1) slice-organized analog blocks providing amplifiers, transistors, capacitors, and Magnetic Tunnel Junctions (MTJs) which are configurable to achieving square/square root operations required for calculating vector norms, 2) digital functional blocks which feature 6-input clockless lookup tables for computation of matrix inverse, and 3) an MRAM-based nonvolatile crossbar array for carrying out low-energy matrix-vector multiplication operations. The various functional blocks are connected via a global interconnect and spin-based analog-to-digital converters. Simulation results demonstrate significant energy and area benefits compared to equivalent CMOS digital implementations for each of the functional blocks used: this includes an 80% reduction in energy and 97% reduction in transistor count for the nonvolatile crossbar array, 80% standby power reduction and 25% reduced area footprint for the clockless lookup tables, and roughly 97% reduction in transistor count for a multiplier built using components from the analog blocks. Moreover, the proposed fabric yields 77% energy reduction compared to CMOS when used to implement CS reconstruction, in addition to latency improvements

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

Crosstalk computing: circuit techniques, implementation and potential applications

Title from PDF of title [age viewed January 32, 2022Dissertation advisor: Mostafizur RahmanVitaIncludes bibliographical references (page 117-136)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020This work presents a radically new computing concept for digital Integrated Circuits (ICs), called Crosstalk Computing. The conventional CMOS scaling trend is facing device scaling limitations and interconnect bottleneck. The other primary concern of miniaturization of ICs is the signal-integrity issue due to Crosstalk, which is the unwanted interference of signals between neighboring metal lines. The Crosstalk is becoming inexorable with advancing technology nodes. Traditional computing circuits always tries to reduce this Crosstalk by applying various circuit and layout techniques. In contrast, this research develops novel circuit techniques that can leverage this detrimental effect and convert it astutely to a useful feature. The Crosstalk is engineered into a logic computation principle by leveraging deterministic signal interference for innovative circuit implementation. This research work presents a comprehensive circuit framework for Crosstalk Computing and derives all the key circuit elements that can enable this computing model. Along with regular digital logic circuits, it also presents a novel Polymorphic circuit approach unique to Crosstalk Computing. In Polymorphic circuits, the functionality of a circuit can be altered using a control variable. Owing to the multi-functional embodiment in polymorphic-circuits, they find many useful applications such as reconfigurable system design, resource sharing, hardware security, and fault-tolerant circuit design, etc. This dissertation shows a comprehensive list of polymorphic logic gate implementations, which were not reported previously in any other work. It also performs a comparison study between Crosstalk polymorphic circuits and existing polymorphic approaches, which are either inefficient due to custom non-linear circuit styles or propose exotic devices. The ability to design a wide range of polymorphic logic circuits (basic and complex logics) compact in design and minimal in transistor count is unique to Crosstalk Computing, which leads to benefits in the circuit density, power, and performance. The circuit simulation and characterization results show a 6x improvement in transistor count, 2x improvement in switching energy, and 1.5x improvement in performance compared to counterpart implementation in CMOS circuit style. Nevertheless, the Crosstalk circuits also face issues while cascading the circuits; this research analyzes all the problems and develops auxiliary circuit techniques to fix the problems. Moreover, it shows a module-level cascaded polymorphic circuit example, which also employs the auxiliary circuit techniques developed. For the very first time, it implements a proof-of-concept prototype Chip for Crosstalk Computing at TSMC 65nm technology and demonstrates experimental evidence for runtime reconfiguration of the polymorphic circuit. The dissertation also explores the application potentials for Crosstalk Computing circuits. Finally, the future work section discusses the Electronic Design Automation (EDA) challenges and proposes an appropriate design flow; besides, it also discusses ideas for the efficient implementation of Crosstalk Computing structures. Thus, further research and development to realize efficient Crosstalk Computing structures can leverage the comprehensive circuit framework developed in this research and offer transformative benefits for the semiconductor industry.Introduction and Motivation -- More Moore and Relevant Beyond CMOS Research Directions -- Crosstalk Computing -- Crosstalk Circuits Based on Perception Model -- Crosstalk Circuit Types -- Cascading Circuit Issues and Sollutions -- Existing Polymorphic Circuit Approaches -- Crosstalk Polymorphic Circuits -- Comparison and Benchmarking of Crosstalk Gates -- Practical Realization of Crosstalk Gates -- Poential Applications -- Conclusion and Future Wor