Company Filing History:
Years Active: 1998-1999
Title: Innovating Helicopter Airspeed Measurement: The Contributions of Kelly M. McCool
Introduction
Kelly M. McCool is an accomplished inventor based in University Park, MD, specializing in innovative technologies for aviation. With a distinct focus on enhancing helicopter performance, she has been granted three patents that highlight her contributions to the field.
Latest Patents
Among her notable inventions is the "Neural Network Based Helicopter Low Airspeed Indicator." This innovative system employs a neural network to estimate helicopter airspeed at low speeds, specifically under 50 knots, by utilizing fixed system parameters. The invention includes mechanisms for inputting initial parameters, measuring variable state parameters during flight, and generating airspeed information through a series of complex equations.
Another significant patent by Kelly is the "Neural Network Based Method for Estimating Helicopter Low Airspeed," which outlines a systematic approach for estimating airspeed in the low flight range. The method involves defining and measuring input parameters during flight, establishing learned relationships between these parameters and corresponding airspeed, and processing data to display real-time airspeed information.
Career Highlights
Kelly M. McCool currently works for the United States of America, as Represented by the Secretary of the Navy. Her expertise in neural network applications for aviation technology exemplifies her commitment to advancing safety and efficiency in helicopter operations.
Collaborations
Throughout her career, Kelly has collaborated with talented individuals such as Carl G. Schaefer, Jr. and David J. Haas. These partnerships have enabled her to expand her research and contribute to groundbreaking advancements in the aerospace sector.
Conclusion
With her innovative patents and a strong background in aviation technology, Kelly M. McCool continues to make significant strides in enhancing helicopter flight safety and efficiency. Her work demonstrates the immense potential of neural networks in revolutionizing how performance metrics are analyzed and presented in real time.
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