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Defect site prediction based upon statistical analysis of fault signaturesTrinka, Michael Robert 30 September 2004 (has links)
Good failure analysis is the ability to determine the site of a circuit defect quickly and accurately. We propose a method for defect site prediction that is based on a site's probability of excitation, making no assumptions about the type of defect being analyzed. We do this by analyzing fault signatures and comparing them to the defect signature. We use this information to construct an ordered list of sites that are likely to be the site of the defect.
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A dynamic circuit-based model for ferromagnetic materialsWicks, Kenneth 05 1900 (has links)
In recent years there has been increased interest in the development of sensorless switched reluctance machine drives. The proper operation of a switched reluctance machine (SRM) requires knowledge of the position of the rotor of the machine. The inclusion of a physical position sensor compromises the inherent robustness of this type of machine. Thus, there has been a need to develop techniques to estimate the position of the rotor in SRM drives.
Switched reluctance machines are able to operate over a large range in speed. A fully loaded SRM is typically designed to saturate the ferromagnetic material that comprises the stator and rotor of the machine whereas a lightly loaded machine does not. Therefore, the model of the machine should be able to handle both a large range in frequency and input excitation levels of the magnetic material in the machine.
The development of a new dynamic circuit-based ferromagnetic model is described in this thesis. The investigation of the behaviour of 24 gauge M19 silicon steel led to the conclusion that, for this material, a circuit model that has static parameters is unable to accurately reproduce the behaviour of the actual material over a large range of input frequencies and excitation levels without resorting to retuning the parameters of the model.
This thesis provides two new mechanisms that dynamically adjust the resistance values of the flux tubes of the model. Comparisons using a normalized vertical least-squares metric between the newly proposed dynamic model and a model that has static resistance values clearly show the improvement that is gained by using these mechanisms.
A practical implementation of the new model is also given. Timing using a general purpose CPU shows that this implementation of the model will most likely be able to be used as part of a multi-phase lumped parameter model for a SRM in realtime.
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A study of the effects on output of industrial workers when closed circuit television is used to permit remote observation of worker performanceEberhart, John Muth 05 1900 (has links)
No description available.
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Active equivalent network generation and sensitivity studyPrice, Burt Lee 05 1900 (has links)
No description available.
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High-Integration-Density Neural Interfaces for High-Spatial-Rrsolution Intracranial EEG MonitoringBagheri, Arezu 21 November 2013 (has links)
This thesis presents two experimental microelectronic prototypes for neurophysiological
applications. Both systems target diagnostics and treatment of neurological disorders,
and they are experimentally validated in vivo by online intracranial EEG recording
in freely moving rats.
The first prototype is a 56-channel chopper-stabilized low-noise neural recording
interface IC with programmable mixed-signal DC cancellation feedback, fabricated in
a 0.13μm CMOS process. Each recording channel has a low-noise fully-differential
amplifier, and a digital integrator and a delta-sigma DAC in the feedback to cancel DC
offsets of up to ±50mV. Chopper stabilization technique is used to reduce the amplifier
flicker noise. The recorded signals are digitized by 7 column-parallel SAR ADCs.
The second prototype is a compact headset for multi-site neuromonitoring and neurostimulation
in rodent brain. A stack of 2 mini-PCBs was designed and experimentally
validated. It includes a previously fabricated 0.35μm CMOS recording and stimulation
IC, a low-power FPGA, and the IC peripherals.
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High-Integration-Density Neural Interfaces for High-Spatial-Rrsolution Intracranial EEG MonitoringBagheri, Arezu 21 November 2013 (has links)
This thesis presents two experimental microelectronic prototypes for neurophysiological
applications. Both systems target diagnostics and treatment of neurological disorders,
and they are experimentally validated in vivo by online intracranial EEG recording
in freely moving rats.
The first prototype is a 56-channel chopper-stabilized low-noise neural recording
interface IC with programmable mixed-signal DC cancellation feedback, fabricated in
a 0.13μm CMOS process. Each recording channel has a low-noise fully-differential
amplifier, and a digital integrator and a delta-sigma DAC in the feedback to cancel DC
offsets of up to ±50mV. Chopper stabilization technique is used to reduce the amplifier
flicker noise. The recorded signals are digitized by 7 column-parallel SAR ADCs.
The second prototype is a compact headset for multi-site neuromonitoring and neurostimulation
in rodent brain. A stack of 2 mini-PCBs was designed and experimentally
validated. It includes a previously fabricated 0.35μm CMOS recording and stimulation
IC, a low-power FPGA, and the IC peripherals.
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Noise models of A/D and D/A converters for determination of fundamental noise limitationsTaylor, Katherine P. 08 1900 (has links)
No description available.
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Spectroscopic investigation of current zero arc propertiesEl-Kholy, S. M. January 1988 (has links)
No description available.
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Self-adaptive methods for computer-aided design of electromagnetic systemsGrieve, M. D. January 1985 (has links)
No description available.
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A computer algorithm for the optimal layout of uncommitted logic arraysMoussa, M. A. A. El.-K. January 1984 (has links)
No description available.
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