Accurate Estimation of a Coil Magnetic Dipole Moment

In this paper, a technique for accurate estimation of the moment of magnetic dipole is proposed. The achievable accuracy is investigated, as a function of measurement noise affecting estimation of magnetic field cartesian components. The proposed technique is validated both via simulations and experimentally.Comment: Preprin

Advanced Sensors for Real-Time Monitoring Applications

It is impossible to imagine the modern world without sensors, or without real-time information about almost everything—from local temperature to material composition and health parameters. We sense, measure, and process data and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future. To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users have established an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This book documents some of the results of such a dialogue and reports on advances in sensors and sensor systems for existing and emerging real-time monitoring applications

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Design of autonomous sustainable unmanned aerial vehicle - A novel approach to its dynamic wireless power transfer

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Electric UAVs are presently being used widely in civilian duties such as security, surveillance, and disaster relief. The use of Unmanned Aerial Vehicle (UAV) has increased dramatically over the past years in different areas/fields such as marines, mountains, wild environments. Nowadays, there are many electric UAVs development with fast computational speed and autonomous flying has been a reality by fusing many sensors such as camera tracking sensor, obstacle avoiding sensor, radar sensor, etc. But there is one main problem still not able to overcome which is power requirement for continuous autonomous operation. When the operation needs more power, but batteries can only give for 20 to 30 mins of flight time. These types of system are not reliable for long term civilian operation because we need to recharge or replace batteries by landing the craft every time when we want to continue the operation. The large batteries also take more loads on the UAV which is also not a reliable system. To eliminate these obstacles, there should a recharging wireless power station in ground which can transmit power to these small UAVs wirelessly for long term operation. There will be camera attached in the drone to detect and hover above the Wireless Power Transfer device which got receiving and transmitting station can be use with deep learning and sensor fusion techniques for more reliable flight operations. This thesis explores the use of dynamic wireless power to transfer energy using novel rotating WPT charging technique to the UAV with improved range, endurance, and average speed by giving extra hours in the air. The hypothesis that was created has a broad application beyond UAVs. The drone autonomous charging was mostly done by detecting a rotating WPT receiver connected to main power outlet that served as a recharging platform using deep neural vision capabilities. It was the purpose of the thesis to provide an alternative to traditional self-charging systems that relies purely on static WPT method and requires little distance between the vehicle and receiver. When the UAV camera detect the WPT receiving station, it will try to align and hover using onboard sensors for best power transfer efficiency. Since this strategy relied on traditional automatic drone landing technique, but the target is rotating all the time which needs smart approaches like deep learning and sensor fusion. The simulation environment was created and tested using robot operating system on a Linux operating system using a model of the custom-made drone. Experiments on the charging of the drone confirmed that the intelligent dynamic wireless power transfer (DWPT) method worked successfully while flying on air

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Magnetic sensors and gradiometers for detection of objects

Disertační práce popisuje vývoj nových detekčních zařízení s anizotropními magnetorezistoryThis thesis describes development of innovative sensor systems based on anisotropi

iMag+: An Accurate and Rapidly Deployable Inertial Magneto-Inductive SLAM System

Localisation is an important part of many applications. Our motivating scenarios are short-term construction work and emergency rescue. These scenarios also require rapid setup and robustness to environmental conditions additional to localisation accuracy. These requirements preclude the use of many traditional high-performance methods, e.g. vision-based, laser-based, Ultra-wide band (UWB) and Global Positioning System (GPS)-based localisation systems. To overcome these challenges, we introduce iMag+, an accurate and rapidly deployable inertial magneto-inductive (MI) mapping and localisation system, which only requires monitored workers to carry a single MI transmitter and an inertial measurement unit in order to localise themselves with minimal setup effort. However, one major challenge is to use distorted and ambiguous MI location estimates for localisation. To solve this challenge, we propose a novel method to use MI devices for sensing environmental distortions for accurate closing inertial loops. We also suggest a robust and efficient first quadrant estimator to sanitise the ambiguous MI estimates. By applying robust simultaneous localisation and mapping (SLAM), our proposed localisation method achieves excellent tracking accuracy and can improve performance significantly compared with only using a Magneto-inductive device or inertial measurement unit (IMU) for localisation

Micromachined Magnetoelastic Sensors and Actuators for Biomedical Devices and Other Applications.

Magnetoelastic materials exhibit coupling between material strain and magnetization; this coupling provides the basis for a number of wireless transducers. This thesis extends past work on microfabricated magnetoelastic sensors in three ways. First, a new class of strain sensors based on the ΔE effect are presented. Two sensor types are described – single and differential. The single sensor has an active area of 7×2 mm2 and operates at a resonant frequency of 230.8 kHz with a sensitivity of 13×103 ppm/mstrain and a dynamic range of 0.05-1.05 mstrain. The differential sensor includes a strain-independent 2×0.5 mm2 reference resonator in addition to a 2.5×0.5 mm2 sensing element. The sensor resonance is at 266.4 kHz and reference resonance is at 492.75 kHz. The differential sensor has a dynamic range of 0-1.85 mstrain, a sensitivity of 12.5×103¬¬ ppm/mstrain, and is temperature compensated in the 23-60°C range. Second, fluidic actuation by resonant magnetoelastic devices is presented. This transduction is performed in the context of an implantable device, specifically the Ahmed glaucoma drainage device (AGDD). Aspherical 3D wireless magnetoelastic actuators with small form factors and low surface profiles are integrated with the AGDD; the fluid flow generated by the actuators is intended to limit cellular adhesion to the implant surface that ultimately leads to implant encapsulation and failure. The actuators measure 10.3×5.6 mm2 with resonant frequencies varying from 520 Hz to 4.7 kHz for the different actuator designs. Flow velocities up to 266 μm/s are recorded at a wireless activation range of 25-30 mm, with peak actuator vibration amplitudes of 1.5 μm. Finally, detection techniques for improving the measurement performance of wireless magnetoelastic systems are presented. The techniques focus on decoupling of the excitation magnetic signal from the sensor response to improve measurement sensitivity and noise immunity. Three domains – temporal, frequency, and spatial – are investigated for signal feedthrough. Quantitative results are presented for temporal and frequency domain decoupling. Temporal decoupling is used to measure strain sensors with resonant frequencies in the 125 kHz range, whereas frequency domain decoupling is implemented to measure 44 kHz magnetoelastic resonators.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116647/1/venkatp_1.pd