Direct real-time cavity mode assessment and optimization technique for fiber lasers

A simple technique for direct real-time assessment of a fiber laser cavity-mode condition during operation is demonstrated. Mode stabilization and optimization with this cavity-mode monitoring and conditioning feedback scheme shows significant improvements to the output performance.

An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

In-Motes EYE:a real time application for automobiles in wireless sensor networks

Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.

Respiratory function monitoring using a real-time three-dimensional fiber-optic shaping sensing scheme based upon fiber Bragg gratings

An array of in-line curvature sensors on a garment is used to monitor the thoracic and abdominal movements of a human during respiration. The results are used to obtain volumetric changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The array of 40 in-line fiber Bragg gratings is used to produce 20 curvature sensors at different locations, each sensor consisting of two fiber Bragg gratings. The 20 curvature sensors and adjoining fiber are encapsulated into a low-temperature-cured synthetic silicone. The sensors are wavelength interrogated by a commercially available system from Moog Insensys, and the wavelength changes are calibrated to recover curvature. A three-dimensional algorithm is used to generate shape changes during respiration that allow the measurement of absolute volume changes at various sections of the torso. It is shown that the sensing scheme yields a volumetric error of 6%. Comparing the volume data obtained from the spirometer with the volume estimated with the synchronous data from the shape-sensing array yielded a correlation value 0.86 with a Pearson's correlation coefficient p <0.01.

Real-time detection, tracking, and monitoring of automatically discovered events in social media

We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked, geolocated, summarised and visualised for the end-user. Furthermore, the system tracks changes in emotions over events, signalling possible flashpoints or abatement. We demonstrate the capabilities of ReDites using an extended use case from the September 2013 Westgate shooting incident. Through an evaluation of system latencies, we also show that enriched events are made available for users to explore within seconds of that event occurring.

Respiratory function monitoring using a real-time three-dimensional fiber-optic shaping sensing scheme based upon fiber Bragg gratings

An array of in-line curvature sensors on a garment is used to monitor the thoracic and abdominal movements of a human during respiration. The results are used to obtain volumetric changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The array of 40 in-line fiber Bragg gratings is used to produce 20 curvature sensors at different locations, each sensor consisting of two fiber Bragg gratings. The 20 curvature sensors and adjoining fiber are encapsulated into a low-temperature-cured synthetic silicone. The sensors are wavelength interrogated by a commercially available system from Moog Insensys, and the wavelength changes are calibrated to recover curvature. A three-dimensional algorithm is used to generate shape changes during respiration that allow the measurement of absolute volume changes at various sections of the torso. It is shown that the sensing scheme yields a volumetric error of 6%. Comparing the volume data obtained from the spirometer with the volume estimated with the synchronous data from the shape-sensing array yielded a correlation value 0.86 with a Pearson's correlation coefficient p <0.01.

Direct real-time cavity mode assessment and optimization technique for fiber lasers

A simple technique for direct real-time assessment of a fiber laser cavity-mode condition during operation is demonstrated. Mode stabilization and optimization with this cavity-mode monitoring and conditioning feedback scheme shows significant improvements to the output performance.

Quality assessment of video transmission in heterogeneous networks as applied to real-time telecare

This work looks into video quality assessment applied to the field of telecare and proposes an alternative metric to the more traditionally used PSNR based on the requirements of such an application. We show that the Pause Intensity metric introduced in [1] is also relevant and applicable to heterogeneous networks with a wireless last hop connected to a wired TCP backbone. We demonstrate through our emulation testbed that the impairments experienced in such a network architecture are dominated by continuity based impairments rather than artifacts, such as motion drift or blockiness. We also look into the implication of using Pause Intensity as a metric in terms of the overall video latency, which is potentially problematic should the video be sent and acted upon in real-time. We conclude that Pause Intensity may be used alongside the video characteristics which have been suggested as a measure of the overall video quality. © 2012 IEEE.

Real-time temperature estimation for power MOSFETs considering thermal ageing effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

Development of hardware in the loop real-time control techniques for hybrid power systems involving distributed demands and sustainable energy sources

The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. ^ To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. ^ Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.^ Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures. ^