https://ir.cwi.nl/pub/30568/1-s2.0-S096014811831231X-main.pdf

Machine learning methods for wind turbine condition monitoring: A review

Rapid technological advances have revolutionized the industrial sector These advances range from automation of industrial processes to autonomous industrial processes, where a human input is not required Internet of Things (IoT), which has emerged a few years ago, has been embraced by industry, resulting in what is known as the Industrial Internet of Things (IIoT) IIoT refers to making industrial processes and entities part of the Internet Restricting the definition of IIoT to manufacturing yields another subset of IoT, known as Industry 40 IIoT and Industry 40, will consist of sensor networks, actuators, robots, machines, appliances, business processes, and personnel Hence, a lot of data of diverse nature would be generated The industrial process requires most of the tasks to be performed locally because of delay and security requirements and structured data to be communicated over the Internet to web services and the cloud To achieve this task, middleware support is required between the industrial environment and the cloud/web services In this context, fog is a potential middleware that can be very useful for different industrial scenarios Fog can provide local processing support with acceptable latency to actuators and robots in a manufacturing industry Additionally, as industrial big data are often unstructured, it can be trimmed and refined by the fog locally, before sending it to the cloud We present an architectural overview of IIoT and Industry 40 We discuss how fog can provide local computing support in the IIoT environment and the core elements and building blocks of IIoT We also present a few interesting prospective use cases of IIoT Finally, we discuss some emerging research challenges related to IIoT

Deploying Fog Computing in Industrial Internet of Things and Industry 4.0

Industrial internet of things: Recent advances, enabling technologies and open challenges

Industrial communication systems represent one of the most important innovations of the last decades in the context of factory and process automation systems. They are networks specifically designed to cope with the tight requirements of these challenging application fields such as real time, determinism, and reliability. Moreover, industrial networks are often deployed in environments characterized by strong electromagnetic interference, mechanical stress, critical temperature, and humidity. Over the last three decades, different classes of industrial networks have been developed according to changing requirements and available communication and information technologies. In this paper, we first provide an account of the state of the art, reviewing classical fieldbuses, real-time Ethernet networks, and industrial wireless networks, along with their most relevant features, applications, and performance figures. We introduce the complex standardization framework and analyze the market status and assumptions for future development. In the second part, we address the future perspectives focusing on new technologies, standards, and fields of application. In particular, we consider the time-sensitive networking (TSN) family of standards, Industrial Internet-of-Things (IIoT) systems, high-performance wireless LANs, industrial applications of cellular networks, and Ethernet networks for automotive communication.

Industrial Communication Systems and Their Future Challenges: Next-Generation Ethernet, IIoT, and 5G

A significant number of wind turbines will reach the end of their planned service life in the near future. A decision on lifetime extension is complex and experiences to date are limited. This review presents the current state-of-the-art for lifetime extension of onshore wind turbines in Germany, Spain, Denmark, and the UK. Information was gathered through a literature review and 24 guideline-based interviews with key market players. Technical, economic and legal aspects are discussed. Results indicate that end-of-life solutions will develop a significant market over the next five years. The application of updated load simulation and inspections for technical lifetime extension assessment differs between countries. A major concern is the uncertainty about future electricity spot market prices, which determine if lifetime extension is economically feasible.

Lifetime extension of onshore wind turbines: A review covering Germany, Spain, Denmark, and the UK

Wind energy has played an increasingly vital role in renewable power generation, driving the need for more cost-effective wind energy solutions. Health monitoring of turbines could provide a variety of economic and other benefits to aid in wind growth. A number of commercial and research health monitoring systems have been implemented for wind turbines. This paper surveys these systems, providing an analysis of the current state of turbine health monitoring and the challenges associated with monitoring each of the major turbine components. This paper also contextualizes the survey with the various potential benefits of health monitoring for turbines.

A survey of health monitoring systems for wind turbines

Energy-efficient and robust-time synchronization is crucial for industrial Internet of things (IIoT). Some energy-efficient time synchronization schemes that achieve high accuracy have been proposed recently. However, some unsynchronized nodes namely isolated nodes exist in the schemes. To deal with the problem, this paper presents R-Sync, a robust time synchronization scheme for IIoT. We use a pulling timer to pull isolated nodes into synchronized networks whose initial value is set according to level of spanning tree. Then, another timer is set up to select backbone node and its initial value is related to the distance to parent node. Moreover, we do experiments based on simulation tool NS-2 and testbed based on wireless hardware nodes. The experimental results show that our approach makes all the nodes get synchronized and gets the better performance in terms of accuracy and energy consumption, compared with three existing time synchronization algorithms TPSN, GPA, STETS.

A Robust Time Synchronization Scheme for Industrial Internet of Things

Barrier coverage is an important application of sensor networks. This paper studies how to build a strong barrier with mobile sensors in which the maximum moving distance of sensors is minimized. Our work differs from others in the way the y-coordinate of the barrier is determined. We optimize the y-coordinate of the barrier instead of fixing it a priori. An efficient algorithm is proposed, in which the search space of the y-coordinate of the barrier is first discretized and then searched over iteratively. In the theoretical worst case, O(N 4 ) iterations may be needed to find the optimal barrier location, where N is the number of sensors, but in practice, our algorithm requires less than O(N 2 ) iterations, as confirmed in simulation.

http://home.eng.iastate.edu/%7Edaji/papers/2015wcnc-z.pdf

Optimized barrier location for barrier coverage in mobile sensor networks

Recent efforts in applying anycast techniques to duty-cycled wireless sensor networks have shown promising results in terms of reduced delay and energy consumption. This paper further increases the energy savings by introducing EDAD, an energy-centric cross-layer data collection protocol designed for anycast communications in asynchronously duty-cycled wireless sensor networks. EDAD uses a new anycast routing metric, EEP, that minimizes the expected energy consumed along the path of a packet and automatically adapts to network settings. Simulation results show that EDAD consumes less energy than similar existing protocols, while maintaining a comparable delay and high delivery rate. I. INTRODUCTION

http://home.engineering.iastate.edu/~daji/papers/2015wcnc-w.pdf

EDAD: Energy-centric data collection with anycast in duty-cycled wireless sensor networks

Barrier coverage is a fundamental application for wireless sensor networks. In this paper, we consider a practical probabilistic sensing model and propose an iterative scheme, called BaCo, to provide strong barrier coverage under this model, with the objective of minimizing the number of active sensors. Moreover, we build the barrier under practical constraints of minimum detection probability and maximum false alarm probability. We use simulations to show that BaCo converges quickly and achieves better results than previous work while also bounding the system false alarm probability.

Mathew L. Wymore

Papers

A survey of health monitoring systems for wind turbines

A Robust Time Synchronization Scheme for Industrial Internet of Things

Optimized barrier location for barrier coverage in mobile sensor networks

EDAD: Energy-centric data collection with anycast in duty-cycled wireless sensor networks

An iterative method for strong barrier coverage under practical constraints