Short Circuit and Broken Rotor Faults Severity Discrimination in Induction Machines Using Non-invasive Optical Fiber Technology

Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having various machine fault-detection techniques is useful in allowing the ability to combine two or more in a manner that will provide a more comprehensive application-dependent condition-monitoring solution; especially, given the increasing role these machines are expected to play in man’s transition to a more sustainable environment, where many more electric machines will be required. This paper presents a novel non-invasive optical fiber using a stray flux technique for the condition monitoring and fault detection of induction machines. A giant magnetostrictive transducer, made of terfenol-D, was bonded onto a fiber Bragg grating, to form a composite FBG-T sensor, which utilizes the machines’ stray flux to determine the internal condition of the machine. Three machine conditions were investigated: healthy, broken rotor, and short circuit inter-turn fault. A tri-axial auto-data-logging flux meter was used to obtain stray magnetic flux measurements, and the numerical results obtained with LabView were analyzed in MATLAB. The optimal positioning and sensitivity of the FBG-T sensor were found to be transverse and 19.3810 pm/μT, respectively. The experimental results showed that the FBG-T sensor accurately distinguished each of the three machine conditions using a different order of magnitude of Bragg wavelength shifts, with the most severe fault reaching wavelength shifts of hundreds of picometres (pm) compared to the healthy and broken rotor conditions, which were in the low-to-mid-hundred and high-hundred picometre (pm) range, respectively. A fast Fourier transform (FFT) analysis, performed on the measured stray flux, revealed that the spectral content of the stray flux affected the magnetostrictive behavior of the magnetic dipoles of the terfenol-D transducer, which translated into strain on the fiber gratings.

Battery-Free Shape Memory Alloy Antennas for Detection and Recording of Peak Temperature Activity

Economical sensing and recording of temperatures are important for monitoring the supply chain. Existing approaches measure the entire temperature profile over time using electronic devices running on a battery. This paper presents a simple, intelligent, battery-free solution for capturing key temperature events using the natural thermo-mechanical state of a Shape Memory Alloy (SMA). This approach utilizes the temperature-induced irreversible mechanical deformation of the SMA as a natural way to capture the temperature history without the need for electronic data logging. In this article, two-way SMA is used to record both high-temperature and low-temperature peak events. Precise thermo-mechanically trained SMA are employed as arms of the dipole antenna for Radio Frequency (RF) readout. The fabricated antenna sensor works at 1 GHz and achieves a sensitivity of 0.24 dB/°C and −0.16 dB/°C for recording temperature maxima and minima, respectively.

Prestack Seismic Inversion via Nonconvex L1-2 Regularization

Using seismic data, logging information, geological interpretation data, and petrophysical data, it is possible to estimate the stratigraphic texture and elastic parameters of a study area via a seismic inversion. As such, a seismic inversion is an indispensable tool in the field of oil and gas exploration and development. However, due to unknown natural factors, seismic inversions are often ill-conditioned problems. One way to work around this unknowable information is to determine the solution to the seismic inversion using regularization methods after adding further a priori constraints. In this study, the nonconvex L1−2 regularization method is innovatively applied to the three-parameter prestack amplitude variation angle (AVA) inversion. A forward model is first derived based on the Fatti approximate formula and then low-frequency models for P impedance, S impedance, and density are established using logging and horizon data. In the Bayesian inversion framework, we derive the objective function of the prestack AVA inversion. To further improve the accuracy and stability of the inversion results, we remove the correlations between the elastic parameters that act as initial constraints in the inversion. Then, the objective function is solved by the nonconvex L1−2 regularization method. Finally, we validate our inversion method by applying it to synthetic and observational data sets. The results show that our nonconvex L1−2 regularization seismic inversion method yields results that are highly accurate, laterally continuous, and can be used to identify and locate reservoir formation boundaries. Overall, our method will be a useful tool in future work focused on predicting the location of reservoirs.

Multi-Domain Dynamic Modelling of a Low-Cost Upper Limb Rehabilitation Robot

Tracking patient progress through a course of robotic tele-rehabilitation requires constant position data logging and comparison, alongside periodic testing with no powered assistance. The test data must be compared with previous test attempts and an ideal baseline, for which a good understanding of the dynamics of the robot is required. The traditional dynamic modelling techniques for serial chain robotics, which involve forming and solving equations of motion, do not adequately describe the multi-domain phenomena that affect the movement of the rehabilitation robot. In this study, a multi-domain dynamic model for an upper limb rehabilitation robot is described. The model, built using a combination of MATLAB, SimScape, and SimScape Multibody, comprises the mechanical electro-mechanical and control domains. The performance of the model was validated against the performance of the robot when unloaded and when loaded with a human arm proxy. It is shown that this combination of software is appropriate for building a dynamic model of the robot and provides advantages over the traditional modelling approach. It is demonstrated that the responses of the model match the responses of the robot with acceptable accuracy, though the inability to model backlash was a limitation.

Potential of Floating Photovoltaic Technology and Their Effects on Energy Output, Water Quality and Supply in Jordan

In this work, floating photovoltaic systems were experimentally studied under Jordan’s weather conditions to determine their effects on energy output, water quality and supply. A limited number of studies have addressed the effect of floating photovoltaic systems on water quality and evaporation reduction especially in a semi-arid region like Jordan. Energy measurements were taken from August 2020 to January 2021 using an Arduino board with data logging sensors. Water quality parameters were tested for collected samples on a monthly basis from August 2020 to February 2021 using a spectrophotometer. Results revealed that the floating panel temperature was lower than the ground-mounted counterpart. An average increase of 1.68% in voltage and 4.40% in current were observed for the floating panel compared to the ground-mounted panel which translates to an average increase of 5.33% in power generation over the ground-mounted panel. Furthermore, efficiency and fill factor increased by 4.89% and 5.51%, respectively. Evaporation results showed that covering water bodies with panels can save a considerable amount of water. Over a period of 30 days, the 30% coverage pan saved 31.2% (36 mm) of water while the 50% coverage pan saved 54.5% (63 mm) of water in the same period compared to the uncovered pan. Moreover, this study involved examining the effect of shading caused by the floating structure on water quality. Results showed a reduction in pH, improvement in transparency, and an increase in total organic carbon indicating water quality enhancement and algal biomass reduction. However, due to the respiration of algae, the dissolved oxygen declined significantly, accompanied by the release of phosphate due to algae decomposition. Overall, findings of this research provided better understanding of floating photovoltaic systems and their applicability in Jordan to provide a safe and reliable supply of water and energy. Additionally, such systems can help to diversify the energy mix and help Jordan to alleviate some of the problems associated with limited energy and water resources.

New Advances in Surface Data Logging Technologies for Comprehensive Real-Time Petrophysical Evaluation to Optimize Logging Programs in a Mature Field; A Case History, Onshore, Abu Dhabi

The challenges of drilling new wells are increasingly associated with minimizing HSE risks, that relate to chemical radioactive sources in the Bottom Hole Assembly for formation evaluation. Drilling risks such as differential sticking, also necessitates investigation of alternative petrophysical data gathering methodologies that can fulfil these requirements. Surface Data Logging presents a viable alternative in mature fields, satisfying petrophysical data gathering and interpretation in real-time as well, as traditional geological applications and offset well correlations in a way, to optimize well construction costs. During the planning phase, a fully integrated approach was adopted including advanced cutting and advanced gas analysis to be deployed, in this case study, well together with experienced well site personnel. A comprehensive pre-well study was conducted reviewing all offset nearby wells data. The workflow included provision of full real-time advanced cuttings and gas analysis for formation evaluation and reservoir fluid composition, lithology description, and addressing effective hole cleaning concerns. The advanced Mud Logging services was run in parallel to the Logging While Drilling services for a few pilot wells, in order to correlate downhole tool parameters, with respect to data quality control, to identify the petrophysical character of the formation markers for benchmarking future data gathering requirements. In addition to the potential use of standalone fully integrated advanced Mud Logging to reduce risks and minimize field development costs. With the help of experienced wellsite geologist on location and real time advanced gas detection utilizing high resolution mass spectrometer and X-Ray fluorescence (XRF) and X-Ray Diffraction (XRD) data, geological boundaries and formations tops were accurately identified across the whole drilled interval. Modern and advanced interpretation techniques for the integrated analysis were proven to be effective in determining sweet spots of the reservoir, fluid type, and overall reservoir quality. Deployment of fully integrated mud logging solutions with new interpretation methodologies can be effective in providing a better understanding of reservoir geological and petrophysical characteristics in real-time, offering viable alternative for minimizing formation evaluation sensors in the BHA, particularly eliminating radioactive sources, while reducing overall developments costs, without sacrificing formation evaluation requirements.

Analysis of 3Vs of Big Data from Fake News and Nigerians’ Consciousness towards National Unity in Times of Uncertainties

Fake news seems to be the monster of the century affecting continents of the world. From Africa to Asia, America to the Himalayas, the impact of fake news on national unity and regional cohesion remains debatable among scholars and experts. Like other countries on the African continent, Nigeria has tasted and is still having share of the consequences of fake news, especially politically-driven ones, which has been researched by scholars in the media and emerging technologies spaces. This study joins the conversation within the journalism and fake news discourse using big data that emerged from selected political, security, health and religious fake news reported by selected Nigerian newspapers. Adopting Computational and Quantitative Content Analyses with the specific use of Data Logging Approach for data collection, the study investigates the extent to which the Nigerian public consume and spread the select news at the expense of promoting national unity and regional cohesion expected of citizens, as established in the Nigerian constitution and existing rules guiding public communication in the country. The emerging results point towards the need for the establishment of Media Literacy Commission to complement the efforts of ministries saddled with the responsibility of re-orientating journalists, media establishments and citizens on national consciousness and unity. The outcomes of the study also indicate the need for overhauling of the National Orientation Agency (NOA) towards balanced and connected promotion of national values and norms.

Smart Textiles for Improved Quality of Life and Cognitive Assessment

Smart textiles can be used as innovative solutions to amuse, meaningfully engage, comfort, entertain, stimulate, and to overall improve the quality of life for people living in care homes with dementia or its precursor mild cognitive impairment (MCI). This concept paper presents a smart textile prototype to both entertain and monitor/assess the behavior of the relevant clients. The prototype includes physical computing components for music playing and simple interaction, but additionally games and data logging systems, to determine baselines of activity and interaction. Using microelectronics, light-emitting diodes (LEDs) and capacitive touch sensors woven into a fabric, the study demonstrates the kinds of augmentations possible over the normal manipulation of the traditional non-smart activity apron by incorporating light and sound effects as feedback when patients interact with different regions of the textile. A data logging system will record the patient’s behavioral patterns. This would include the location, frequency, and time of the patient’s activities within the different textile areas. The textile will be placed across the laps of the resident, which they then play with, permitting the development of a behavioral profile through the gamification of cognitive tests. This concept paper outlines the development of a prototype sensor system and highlights the challenges related to its use in a care home setting. The research implements a wide range of functionality through a novel architecture involving loosely coupling and concentrating artifacts on the top layer and technology on the bottom layer. Components in a loosely coupled system can be replaced with alternative implementations that provide the same services, and so this gives the solution the best flexibility. The literature shows that existing architectures that are strongly coupled result in difficulties modeling different individuals without incurring significant costs.

Implementation of Smart Street Light System with the Assistance of Cloud Based Online Access

This paper proposes a street lighting system utilizing minimal expense microcontroller-based Arduino. Since there is a need for the industry is to connect heterogeneous equipment parts to the cloud-based internet-based admittance framework for checking and figuring out their conduct from time to time. The principle objective is to plan energy effective keen streetlamp for energy protection in existing streetlamps and safeguarding from theft issue of batteries and sunlight-based chargers in the country and metropolitan region and only for brilliant urban areas, and this paper is to record and send the readings of the proposed module to IoT which building up the reasonable web application on the cloud for Data logging. Ordinarily, we see that streetlamps are remain turned ON during daytime, absence of upkeep of batteries prompts uses misfortune. So for decreasing the referred to issues a portion of the electrical gadgets can guide specific boundaries to the microcontroller which are taken care of with the assistance of Ethernet of Wi-Fi module and associated with the cloud-based framework. A test arrangement has been made to know the situation with gadgets through Laptop/Mobile/PC at any space while associated with the cloud.

HIGROTERM: An Open-Source and Low-Cost Temperature and Humidity Monitoring System for Laboratory Applications

Low-cost electronics developed on easy-to-use prototyping platforms, such as Arduino, are becoming increasingly popular in various fields of science. This article presents an open-source and low-cost eight-channel data-logging system for temperature and humidity monitoring based on DHT22 (AM2302) sensors, named HIGROTERM. The system was designed to solve real needs of the Laboratory of Material Testing of the Department of Civil and Environmental Engineering at the University of Brasília. The system design, functionalities, hardware components, source code, bill of materials, assemblage and enclosure are thoroughly described to enable complete reproduction by the interested reader. The terminologies and instructions presented were simplified as much as possible to make it accessible to the greatest extent to researchers from different areas, especially those without electronics background. The data-acquisition system has an estimated total cost of USD 96.00, or USD 136.00 if eight sensor nodes are included, with a considerable margin for cost reduction. The authors expect that the HIGROTERM system may both be a valuable low-cost and customizable tool for the readers, as well a source of innovation and interest in low-cost electronics for real problem-solving in various fields of science.