Adaptive Multiscale Weighted Permutation Entropy for Rolling Bearing Fault Diagnosis

© 2020 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.Bearing vibration signals contain non-linear and non-stationary features due to instantaneous variations in the operation of rotating machinery. It is important to characterize and analyze the complexity change of the bearing vibration signals so that bearing health conditions can be accurately identified. Entropy measures are non-linear indicators that are applicable to the time series complexity analysis for machine fault diagnosis. In this paper, an improved entropy measure, termed Adaptive Multiscale Weighted Permutation Entropy (AMWPE), is proposed. Then, a new rolling bearing fault diagnosis method is developed based on the AMWPE and multi-class SVM. For comparison, experimental bearing data are analyzed using the AMWPE, compared with the conventional entropy measures, where a multi-class SVM is adopted for fault type classification. Moreover, the robustness of different entropy measures is further studied for the analysis of noisy signals with various Signal-to-Noise Ratios (SNRs). The experimental results have demonstrated the effectiveness of the proposed method in fault diagnosis of rolling bearing under different fault types, severity degrees, and SNR levels.Peer reviewedFinal Accepted Versio

A survey on fault diagnosis in wireless sensor networks

Wireless sensor networks (WSNs) often consist of hundreds of sensor nodes that may be deployed in relatively harsh and complex environments. In views of hardware cost, sensor nodes always adopt relatively cheap chips, which makes these nodes become error-prone or faulty in the course of their operation. Natural factors and electromagnetic interference could also influence the performance of the WSNs. When sensor nodes become faulty, they may have died which means they cannot communicate with other members in the wireless network, they may be still alive but produce incorrect data, they may be unstable jumping between normal state and faulty state. To improve data quality, shorten response time, strengthen network security, and prolong network lifespan, many studies have focused on fault diagnosis. This survey paper classifies fault diagnosis methods in recent five years into three categories based on decision centers and key attributes of employed algorithms: centralized approaches, distributed approaches, and hybrid approaches. As all these studies have specific goals and limitations, this paper tries to compare them, lists their merits and limits, and propose potential research directions based on established methods and theories

MAHIVE: Modular Analysis Hierarchical Intrusion Detection System Visualization Event Cybersecurity Engine for Cyber-Physical Systems and Internet of Things Devices

Cyber-Physical Systems (CPS), including Industrial Control Systems (ICS) and Industrial Internet of Things (IIoT) networks, have become critical to our national infrastructure. The increased occurrence of cyber-attacks on these systems and the potential for catastrophic losses illustrates the critical need to ensure our CPS and ICS are properly monitored and secured with a multi-pronged approach of prevention, detection, deterrence, and recovery. Traditional Intrusion Detection Systems (IDS) and Intrusion Detection and Prevention Systems (IDPS) lack features that would make them well-suited for CPS and ICS environments. We report on the initial results for MAHIVE: Modular Analysis Hierarchical IDS Visualization Event cybersecurity engine. MAHIVE differs from traditional IDS in that it was specifically designed and developed for CPS, ICS, a IIoT systems and networks. We describe the MAHIVE architecture, the design, and the results of our evaluation using two ICS testbed penetration testing experiments

Gafor : Genetic algorithm based fuzzy optimized re-clustering in wireless sensor networks

Acknowledgments: The authors are grateful to the Deanship of Scientific Research at King Saud University for funding this work through Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing. Funding: This research was funded by King Saud University in 2020.Peer reviewedPublisher PD

EVALUATION OF DYNAMIC AD-HOC UWB INDOOR POSITIONING SYSTEM

Ultra-wideband (UWB) technology has witnessed tremendous development and advancement in the past few years. Currently available UWB transceivers can provide high-precision time-of-flight measurements which corresponds to range measurements with theoretical accuracy of few centimetres. Position estimation using range measurement is determined by measuring the ranges from a rover or a dynamic node, to a set of anchor points with known positions. However, building a flexible and accurate indoor positioning system requires more than just accurate range measurements. The performance of indoor positioning system is affected by the number and the configuration of the anchor points used, along with the accuracy of the anchor positions.This paper introduces LocSpeck, a dynamic ad-hoc positioning system based on the DW1000 UWB transceiver from Decawave. LocSpeck is composed of a set of identical nodes communicating on a common RF channel, forming a fully or partially connected network where the positioning algorithm run on each node. Each LocSpeck node could act as an anchor or a rover, and the role could change dynamically during the same session. The number of nodes in the network could change dynamically, since the firmware of LocSpeck supports adding and removing nodes on-the-fly. The paper compares the performance of the LocSpeck system with commercially available off-the-shelf UWB positioning system. Different operating scenarios are considered when evaluating the performance of the system, including cases where collaboration between the two systems is considered.</p

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer