Fault diagnosis of the constant current remote power supply system in CUINs based on the improved water cycle algorithm

914-921Cabled Underwater Information Networks (CUINs) is an important platform for ocean observation where the Constant Current Remote Power Supply System (CCRPSS) guarantees the safe and normal operation of CUINs. The CCRPSS is mainly composed of the main node and underwater cables which require frequent fault diagnosis but how to improve the fault diagnosis rate is a difficult problem. This paper proposed a fault diagnosis method for the CCRPSS based on the Improved Water Cycle Algorithm (IWCA) and the multi-classifier group based on the Least Squares Support Vector Machine (LSSVM). Firstly, the multi-feature extraction method is used to obtain the characteristic information in the time and frequency domain; secondly, IWCA is established by combining the traditional Water Cycle Algorithm (WCA) with the chaotic mutation strategy, the elite memory strategy and the population reconstruction strategy. By applying 13 typical test functions to performance test, it can be found that the IWCA can effectively improve the global search ability and balance of the WCA algorithm. At last, IWCA is used to optimize the parameters of the LSSVM classifier and improve the classification efficiency. The comparisons of simulated results with traditional methods show that the proposed diagnostic model can not only obtain complete fault feature information, but also obtain the optimal classification parameters of LSSVM faster. Therefore, the proposed diagnostic method is verified to be suitable for the fault diagnosis of the constant current remote power supply system in CUINs

Fault diagnosis of the constant current remote power supply system in CUINs based on the improved water cycle algorithm

Cabled Underwater Information Networks (CUINs) is an important platform for ocean observation where the Constant Current Remote Power Supply System (CCRPSS) guarantees the safe and normal operation of CUINs. The CCRPSS is mainly composed of the main node and underwater cables which require frequent fault diagnosis but how to improve the fault diagnosis rate is a difficult problem. This paper proposed a fault diagnosis method for the CCRPSS based on the Improved Water Cycle Algorithm (IWCA) and the multi-classifier group based on the Least Squares Support Vector Machine (LSSVM). Firstly, the multi-feature extraction method is used to obtain the characteristic information in the time and frequency domain; secondly, IWCA is established by combining the traditional Water Cycle Algorithm (WCA) with the chaotic mutation strategy, the elite memory strategy and the population reconstruction strategy. By applying 13 typical test functions to performance test, it can be found that the IWCA can effectively improve the global search ability and balance of the WCA algorithm. At last, IWCA is used to optimize the parameters of the LSSVM classifier and improve the classification efficiency. The comparisons of simulated results with traditional methods show that the proposed diagnostic model can not only obtain complete fault feature information, but also obtain the optimal classification parameters of LSSVM faster. Therefore, the proposed diagnostic method is verified to be suitable for the fault diagnosis of the constant current remote power supply system in CUINs

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

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

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

Power and Energy Student Summit 2019: 9 – 11 July 2019 Otto von Guericke University Magdeburg ; Conference Program

The book includes a short description of the conference program of the "Power and Energy Student Summit 2019". The conference, which is orgaized for students in the area of electric power systems, covers topics such as renewable energy, high voltage technology, grid control and network planning, power quality, HVDC and FACTS as well as protection technology. Besides the overview of the conference venue, activites and the time schedule, the book includes all papers presented at the conference

Structural Health Monitoring for Bridge Structures using Smart Sensors

Structural health monitoring (SHM) has drawn significant attention in recent decades because of its potential to reduce maintenance costs and increase the reliability of structures. An important class of structures that can potentially benefit from SHM are bridges, many of which are structurally deficient due to lack of adequate maintenance. Through condition assessment of these bridges, an effective plan of maintenance can be determined, offering the possibility to prolong service life, as well as to prevent catastrophic disasters due to sudden collapse. To date, numerous damage detection algorithms have been proposed. Still, challenges remain in applying such algorithms to monitor bridges in the field. In reality, the extent of an SHM system is limited by available budgets, which define the number of sensors that can be deployed. A solution to include many sensors within a limited budget with increased efficiency is to use a Wireless Smart Sensor Network (WSSN) because of the merits of low cost, easy installation, and effective data management. An acceleration-based SHM algorithm for WSSN has been developed with a decentralized network topology. This approach has been implemented into a modularized damage detection service. The SHM application is designed to leverage the on-board computation capability of the WSSN, reducing the transmitted data size by distributing the computation burden. The SHM application for WSSN has been validated in lab-scale experiments on a truss bridge model. Nonetheless, the real challenge of SHM is in the deployment on full-scale bridges for continuous monitoring. The usability and stability of WSSN has been validated on an architectural staircase in the Siebel Center. Based on the usability investigation, the deployment of the world’s largest WSSN on the Jindo Bridge, a cable-stayed bridge has been achieved in South Korea. The main purpose of the deployment was to validate the bridge monitoring system using WSSN and energy harvesting devices in a long-term manner. The ultimate goal of this report is to deploy the developed on-board decentralized damage identification application using WSSN on a historic truss bridge. As a first step, a series of dynamic tests were conducted for modal analysis using both wired and wireless sensor systems. During the tests, the functionality of the wireless sensor system with ISHMP Services Toolsuite was confirmed. For model-based damage identification approach developed herein, a finite element (FE) model was created. The initial FE model was updated based on a visual estimate of the corrosion. The updated model was used to generate baseline information for damage detection. Finally, the WSSN-based autonomous SHM system using the decentralized damage detection application was deployed on the historic bridge. The permanent SHM system was installed on the bridge, and the damage detection application was successfully run on the bridge. The damage detection results using the decentralized comprehensive application will be compared with those from the centralized approach using WSSN. The performance of WSSN and energy harvesting devices will be evaluated. In summary, this report provides a robust SHM system for bridge structures in use of WSSN.Financial support for this research was provided in part by a Samsung Scholarship, the National Science Foundation (NSF) under NSF grant CMS 06-00433 (Dr. S. C. Liu, Program Manager), and the Global Research Network program from the Natural Research Foundation in Korea (NRF-2008-220-D00117).Ope