With deregulation, diagnosis and maintenance of power equipment, especially power transformers, become increasingly important to keep power systems in reliable operation. This dissertation systematically studied two kinds of transformer failure and abnormality cases, and then developed a new Internet based Virtual Hospital (VH) for power equipment to help power equipment diagnosis and maintenance. A practical case of generator-step-up (GSU) transformer failures in a pumped storage plant was extensively studied. Abnormal electrical phenomena associated with GSU transformers, including switching transients and very fast transients (VFT), and lightning, were analyzed. Simulation showed that circuit breaker restriking could be a major cause of transformer successive failures, and current surge arrester configuration did not provide enough lightning protection to GSU transformers. Mitigation of abnormal electrical phenomena effects on GSU transformers was proposed and discussed. The study can be a complete reference of troubleshooting of other similar transformer failures. Geomagnetically induced current (GIC) is another possible cause of transformer abnormality. A simplified method based on the equivalent magnetizing curve for transformers with different core design was developed and validated to estimate harmonic currents and MVar drawn by power transformers with a given GIC. An effective indicator was proposed using partial harmonic distortion, PHD, to show when the transformer begins saturating with the input GIC. The developed method has been applied to a real time GIC monitoring system last year for a large power network with thousands of transformers. A new Internet based Virtual Hospital (VH) for Power Equipment was conceptually developed to share experience of power equipment diagnosis and maintenance, and update the existing diagnostic techniques and maintenance strategies, and a comprehensive information model was developed for data organization, access, and archiving related to equipment diagnosis and maintenance. An Internet based interactive fault diagnostic tool has been launched for power transformers based on dissolved gas analysis (DGA). The above results and findings can help improving power equipment diagnosis and utility maintenance strategies. / Ph. D.

Clinical trials involving digital health technologies are complex and challenging deployments. The SMArTVIEW trial (n=800), underway, combines remote automated patient monitoring (RAM) in hospital and virtual hospital-to-home nursing support, up to 30-days post-discharge, for patients who have undergone cardiac and major vascular surgery. Cardiac and vascular surgery patients are at risk for postoperative complications, as well as hospital readmission; SMArTVIEW aims to reduce hospital readmissions and emergency department visits. The purpose of this work was to conduct a process monitoring evaluation of the first 100 patients enrolled in order to examine the implementation, mechanisms, context, and specialized nursing role of the SMArTVIEW intervention. Six data sources were used to examine patient recruitment, daily nursing intervention workflows, RAM technology compliance, technical troubleshooting, patient education, and virtual nursing care. A content analysis was used to identify nursing advice, recommendations, and corrective actions for patients requiring intervention recovering at home. Fifty patients were allocated to the SMArTVIEW intervention; of these, 34 engaged in all intervention components, both in-hospital and at home. In-hospital RAM technology generated 194 notifications, drawing nurses to the beside for patient reassessment. Forty-two daily nurse reports and 926 virtual nursing care records were audited to determine technology implementation issues and nursing actions to support patient recovery at home. Process monitoring uncovered strengths and limitations in the initial days of intervention deployment. Strengths included the functionality of RAM technology, facilitating nurse compliance with required workflows, as well as a high degree of patient engagement in the program. SMArTVIEW nurses addressed multiple health concerns for patients, resulting in 1,865 nursing actions over the 30-day intervention course. Patient withdrawals and lack of standardized communication practices were areas requiring improvement. Results were used to refine and standardize intervention workflows in order to scale the intervention for deployment at a second site (United Kingdom). / Thesis / Master of Science (MSc)