Induction Motor Diagnosis in Variable Speed Drives

Several diagnostic techniques are presented for the detection of electrical fault in induction motor variable speed drives. These techinques are developed taking into account the impact of the control system on machine variables and non stationary operating conditions.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Towards a new test of time dilation: Laser spectroscopy on lithium ions stored at a velocity of 33.8 % of the speed of light

The subject of the presented thesis is the accurate measurement of time dilation, aiming at a quantitative test of special relativity. By means of laser spectroscopy, the relativistic Doppler shifts of a clock transition in the metastable triplet spectrum of ^7Li^+ are simultaneously measured with and against the direction of motion of the ions. By employing saturation or optical double resonance spectroscopy, the Doppler broadening as caused by the ions' velocity distribution is eliminated. From these shifts both time dilation as well as the ion velocity can be extracted with high accuracy allowing for a test of the predictions of special relativity. A diode laser and a frequency-doubled titanium sapphire laser were set up for antiparallel and parallel excitation of the ions, respectively. To achieve a robust control of the laser frequencies required for the beam times, a redundant system of frequency standards consisting of a rubidium spectrometer, an iodine spectrometer, and a frequency comb was developed. At the experimental section of the ESR, an automated laser beam guiding system for exact control of polarisation, beam profile, and overlap with the ion beam, as well as a fluorescence detection system were built up. During the first experiments, the production, acceleration and lifetime of the metastable ions at the GSI heavy ion facility were investigated for the first time. The characterisation of the ion beam allowed for the first time to measure its velocity directly via the Doppler effect, which resulted in a new improved calibration of the electron cooler. In the following step the first sub-Doppler spectroscopy signals from an ion beam at 33.8 %c could be recorded. The unprecedented accuracy in such experiments allowed to derive a new upper bound for possible higher-order deviations from special relativity. Moreover future measurements with the experimental setup developed in this thesis have the potential to improve the sensitivity to low-order deviations by at least one order of magnitude compared to previous experiments; and will thus lead to a further contribution to the test of the standard model.

High-Speed Laser Processing of Thin Single and Multi-Layer Films

Theoretical models are developed for the continuous-wave and pulsed laser incision and cut of thin single and multi-layer films. A one-dimensional steady-state model establishes the theoretical foundations of the problem by combining a power-balance integral with heat flow in the direction of laser motion. In this approach, classical modelling methods for laser processing are extended by introducing multi-layer optical absorption and thermal properties. The calculation domain is consequently divided in correspondence with the progressive removal of individual layers. A second, time-domain numerical model for the short-pulse laser ablation of metals accounts for changes in optical and thermal properties during a single laser pulse. With sufficient fluence, the target surface is heated towards its critical temperature and homogeneous boiling or "phase explosion" takes place. Improvements are seen over previous works with the more accurate calculation of optical absorption and shielding of the incident beam by the ablation products. A third, general time-domain numerical laser processing model combines ablation depth and energy absorption data from the short-pulse model with two-dimensional heat flow in an arbitrary multi-layer structure. Layer removal is the result of both progressive short-pulse ablation and classical vaporisation due to long-term heating of the sample. At low velocity, pulsed laser exposure of multi-layer films comprising aluminium-plastic and aluminium-paper are found to be characterised by short-pulse ablation of the metallic layer and vaporisation or degradation of the others due to thermal conduction from the former. At high velocity, all layers of the two films are ultimately removed by vaporisation or degradation as the average beam power is increased to achieve a complete cut. The transition velocity between the two characteristic removal types is shown to be a function of the pulse repetition rate. An experimental investigation validates the simulation results and provides new laser processing data for some typical packaging materials.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Energy harvesting from piezoelectric devices embedded in a 3D printed wing

This thesis work has been carried out at Clarkson University in Potsdam NY, USA and involved the design of a low elongation wing, consisting of parts made by polylactide (PLA) using the fused deposition model (FDM) technology of Rapid Prototyping, then assembled together in a thin aluminum spar. The aim of the research is to evaluate the feasibility of collecting electrical energy by converting mechanical energy from the vibration of the wing flutter. With this aim piezoelectric stripes were glued in the inner part of the wing, as well as on the aluminum spar, as monomorphic configuration. During the phases of the project, particular attention was given to the geometry and the materials used, in order to trigger the flutter for low flow velocity. The CAD software SolidWorks® was used for the design of the wing and then the drawings were sent to the Clarkson machine shop in order to to produce the parts required by the wing assembly. FEM simulations were performed, using software MSC NASTRAN/PATRAN®, to evaluate the stiffness of the whole wing as well as the natural vibration modes of the structure. These data, in a first approximation, were used to predict the flutter speed. Finally, experimental tests in the Clarkson wind tunnel facility were carried out in order to validate the results obtained from FEM analysis. The power collected by the piezoelectrics under flutter condition was addressed by tuning the resistors downstream the electronic circuit of the piezoelectrics.

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

Geometric facial comparisons in speed-check photographs

In many cases, it is not possible to call the motorists to account for their considerable excess in speeding, because they deny being the driver on the speed-check photograph. An anthropological comparison of facial features using a photo-to-photo comparison can be very difficult depending on the quality of the photographs. One difficulty of that analysis method is that the comparison photographs of the presumed driver are taken with a different camera or camera lens and from a different angle than for the speed-check photo. To take a comparison photograph with exactly the same camera setup is almost impossible. Therefore, only an imprecise comparison of the individual facial features is possible. The geometry and position of each facial feature, for example the distances between the eyes or the positions of the ears, etc., cannot be taken into consideration. We applied a new method using 3D laser scanning, optical surface digitalization, and photogrammetric calculation of the speed-check photo, which enables a geometric comparison. Thus, the influence of the focal length and the distortion of the objective lens are eliminated and the precise position and the viewing direction of the speed-check camera are calculated. Even in cases of low-quality images or when the face of the driver is partly hidden, good results are delivered using this method. This new method, Geometric Comparison, is evaluated and validated in a prepared study which is described in this article.

In vivo measurement of central corneal thickness in normal chicks (Gallus gallus domesticus) with the optical low-coherence reflectometer

OBJECTIVE To determine the practicability and accuracy of central corneal thickness (CCT) measurements in living chicks utilizing a noncontact, high-speed optical low-coherence reflectometer (OLCR) mounted on a slit lamp. ANIMALS STUDIED Twelve male chicks (Gallus gallus domesticus). Procedures  Measurements of CCT were obtained in triplicate in 24 eyes of twelve 1-day-old anaesthetized chicks using OLCR. Every single measurement taken by OLCR consisted of the average result of 20 scans obtained within seconds. Additionally, corneal thickness was determined histologically after immersion fixation in Karnovsky's solution alone (20 eyes) or with a previous injection of the fixative into the anterior chamber before enucleation (4 eyes). RESULTS Central corneal thickness measurements using OLCR in 1-day-old living chicks provide a rapid and feasible examination technique. Mean CCT measured with OLCR (189.7 ± 3.34 μm) was significantly lower than histological measurements (242.1 ± 47.27 μm) in eyes with fixation in Karnovsky's solution (P = 0.0005). In eyes with additional injection of Karnovsky's fixative into the anterior chamber, mean histologically determined CCT was 195.2 ± 8.25 μm vs. 191.9 ± 8.90 μm with OLCR. A trend for a lower variance was found compared to the eyes that had only been immersion fixed. CONCLUSION Optical low-coherence reflectometry is an accurate examination technique to measure in vivo CCT in the eye of newborn chicks. The knowledge of the thickness of the chick cornea and the ability to obtain noninvasive, noncontact measurements of CCT in the living animal may be of interest for research and development of eye diseases in chick models.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Full body low radiation radiography using Lodox Statscan

Lodox Statscan provides high-speed, high-quality, low radiation, full body imaging in a single scan, combined with three-dimensional reconstructive and zooming functionality. Several trauma centres have incorporated it into their advanced trauma life support protocol. This review gives a brief overview of the system.

Generalized eMC implementation for Monte Carlo dose calculation of electron beams from different machine types

The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.

Multi-stage ytterbium fiber-amplifier seeded by a gain-switched laser diode

We demonstrated all-fiber amplification of 11 ps pulses from a gain-switched laser diode at 1064 nm. The diode was driven at a repetition rate of 40 MHz and delivered 13 µW of fiber-coupled average output power. For the low output pulse energy of 325 fJ we have designed a multi-stage core pumped pre-amplifier in order to keep the contribution of undesired amplified spontaneous emission as low as possible. By using a novel time-domain approach for determining the power spectral density ratio (PSD) of signal to noise, we identified the optimal working point for our pre-amplifier. After the pre-amplifier we reduced the 40 MHz repetition rate to 1 MHz using a fiber coupled pulse-picker. The final amplification was done with a cladding pumped Yb-doped large mode area fiber and a subsequent Yb-doped rod-type fiber. With our setup we reached a total gain of 73 dB, resulting in pulse energies of >5.6 µJ and peak powers of >0.5 MW. The average PSD-ratio of signal to noise we determined to be 18/1 at the output of the final amplification stage.

Determinants of reduced walking speed in people with musculoskeletal pain

OBJECTIVE: Maintenance of good walking speed is essential to independent living. People with musculoskeletal disease often have reduced walking speed. We investigated determinants of slower walking, other than musculoskeletal disease, that might provide valuable additional targets for therapy. METHODS: We analyzed data from the Somerset and Avon Survey of Health, a community based survey of people aged over 35 years. A total of 2703 participants who reported hip or knee pain at baseline (1994/1995) were studied, and reassessed in 2002-2003; 1696 were available for followup, and walking speed was tested in 1074. Walking speed (m/s) was used as outcome measure. Baseline characteristics, including comorbidities and socioeconomic factors, were tested for their ability to predict reduced walking speed using multiple linear regression analysis. RESULTS: Age, female sex, and immobility at baseline were predictive of slower walking speed. Other independent risk factors included the presence of cataract, low socioeconomic status, intermittent claudication, and other cardiovascular conditions. Having a cataract was associated with a decrease of 0.10 m/s (95% CI 0.03, 0.16). Those in social class V had a walking speed 0.22 m/s (95% CI 0.126, 0.31) slower than those in social class I. CONCLUSION: Comorbidities, age, female sex, and lower socioeconomic position determine walking speed in people with joint pain. Issues such as poor vision and social-economic disadvantage may add to the effect of musculoskeletal disease, suggesting the need for a holistic approach to management of these patients.