2 research outputs found
Recommended from our members
High frequency inverter-transformer-cycloconverter system for DC to AC (3-phase) power conversion
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis is concerned with a 3-phase multistage high frequency link DC to AC power conversion with a novel inverter-cycloconverter circuitry. The conversion system is composed of a high frequency PWM inverter, step-up high frequency transformer and cycloconverter with bidirectional switching devices. In first stage the DC voltage of the power source , say a submarine battery, is inverted to a system of 3-phase sinusoidally modulated I kHz alternative wave forms.
For this purpose a suggested optimized PWM technique for 3-phase inverter operation is adopted, in which harmonic components up to 17 th ( 17 kHz) are eliminated from the inverter output voltages. In the second stage, for DC input isolation from AC output and also for a voltage transformation ( here stepping-up )a high frequency ( size reduced ) transformer is employed. Generalized high frequency operation, influence and side effects of the transformer on overall system design & performance is investigated. In the final stage the 1 kHz -to- 50 Hz conversion process is accomplished by a 3-phase cycloconverter. The proposed "nonlinear modulation strategy" for cycloconverter output voltage and associated harmonic analysis is demonstrated, in which the harmonic components up to 38th (1.9 kHz ) are eliminated from the conversion system output voltage. To assess the suggested functioning principles for the inverter & cycloconverter , the prototype conversion system was developed.
Some design criteria and switching device selection are presented, together with different voltage & current wave forms of the prototype system under resistive & inductive load (induction motor) and their respective spectra
Towards Estimation of Emotions From Eye Pupillometry With Low-Cost Devices
Emotional care is important for some patients and their caregivers. Within a clinical or home care situation, technology can be employed to remotely monitor the emotional response of such people. This paper considers pupillometry as a non-invasive way of classifying an individual's emotions. Standardized audio signals were used to emotionally stimulate the test subjects. Eye pupil images of up to 32 subjects of different genders were captured as video images by low-cost, infrared, Raspberry Pi board cameras. By processing of the images, a dataset of pupil diameters according to gender and age characteristics was established. Appropriate statistical tests for inference of the emotional state were applied to that dataset to establish the subjects' emotional states in response to the audio stimuli. Results showed agreement between the test subjects' opinions of their emotional state and the classification of emotions according to the range of pupil diameters found using the described method