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Donald M. Hepburn
Also published under:D. M. Hepburn, Donald Hepburn
Affiliation
School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow, U.K.
Topic
Types Of Defects,Online Monitoring,Partial Discharge,Pattern Recognition,Back Propagation Neural Network,Cable System,Fault Location,High Voltage Cables,Interference Signal,Load Current,Support Vector Machine,Artificial Defects,Coaxial Cable,Current Sensor,Data Feature Extraction,Fuzzy Logic,Insulator State,Major Sections,Neural Network,Open Voltage,Outer Conductor,Partial Discharge Pattern,Pattern Recognition Methods,Power Cables,Raw Data,Severe Defects,Short-circuit Fault,Transformative Power,ABC Model,AC Field,AC System,Abnormal Temperature Rise,Accurate Technique,Activation Function,Actual Diagnosis,Advanced Online,Alternating Current,Ant Colony Optimization,Application Of Voltage,Approach In Order,Artificial Neural Network,Average Accuracy,Average Pooling,Block A,Blue Phase,Cable Faults,Cable Surface,Capacitive Component,Cases Of Loss,Characteristic Signals,
Biography
Donald M. Hepburn received the B.A. (Hons.) degree from the Open University, Walton Hall, U.K., in 1987, and the Ph.D. degree from Glasgow Caledonian University (GCU), Glasgow, U.K., in 1994. He has many years of industrial research experience and has been involved in research into high-voltage insulation systems with GCU for more than 20 years. He is a Senior Lecturer with GCU and is involved in industrial and academic research projects. His research interests cover monitoring of chemical changes to insulation materials, application of electrical, acoustic, and RF monitoring equipment to HV components, and application of advanced digital signal processing to information from the monitoring techniques.