Self-Calibrating Virtual Sensor

The technology presents an on-board estimation, navigation and control architecture for multi-rotor drones flying in an urban environment. It consists of adaptive algorithms to estimate the vehicle's aerodynamic drag coefficients with respect to still air and urban wind components along the flight trajectory, with guaranteed fast and reliable convergence to the true values. Navigation algorithms generate feasible trajectories between given way-points that take into account the estimated wind. Control algorithms track the generated trajectories as long as the vehicle retains a sufficient number of functioning rotors that are capable of compensating for the estimated wind. The technology provides a method of measuring wind profiles on a drone using existing motion sensors, like the inertial measurement unit (IMU), rate gyroscope, etc., that are observably necessary for any drone to operate. The algorithms are used to estimate wind around the drone. They can be used for stability or trajectory calculations, and are adaptable for use with any UAV regardless of the knowledge of weight and inertia. They further provide real-time calculations without additional sensors. The estimation method is implemented using onboard computing power. It rapidly converges to true values, is computationally inexpensive, and does not require any specific hardware or specific vehicle maneuvers for the convergence. All components of this on-board system are computationally effective and are intended for a real time implementation. The method's software is developed in a Matlab/Simulink environment, and has executable versions, which are suitable for majority of existing onboard controllers. The algorithms were tested in simulations.

Traditionally, unsteady pressure transducers have been the instrumentation of choice for investigating unsteady flow phenomena which can be time-consuming and expensive. The ability to measure and compute these flows has been a long-term challenge for aerospace vehicle designers and manufacturers. Results using only the pressure transducers are prone to inaccuracies, providing overly conservative load predictions in some cases and underestimating load predictions in other areas depending on the flow characteristics. NASA Ames has developed a new state-of-the-art method for measuring fluctuating aerodynamic-induced pressures on wind tunnel models using unsteady Pressure Sensitive Paint (uPSP). The technology couples recent advances in high-speed cameras, high-powered energy sources, and fast response pressure-sensitive paint. The unsteady pressure-sensitive paint (uPSP) technique has emerged as a powerful tool to measure flow, enabling time-resolved measurements of unsteady pressure fluctuations within a dense grid of spatial points on a wind tunnel model. The invention includes details surrounding uPSP processing. This technique enables time-resolved measurements of unsteady pressure fluctuations within a dense grid of spatial points representing the wind tunnel model. Since uPSP is applied by a spray gun, it is continuously distributed. With this approach, if the model geometry can be painted, viewed from a camera, and excited by a lamp source, uPSP data can be collected. Unsteady PSP (uPSP) has the ability to determine more accurate integrated unsteady loads.

How It Works The FOSS technology employs efficient, real-time, data driven algorithms for interpreting strain data. The fiber Bragg grating sensors respond to strain due to stress or pressure on the substrate. The sensors feed these strain measurements into the systems algorithms to determine shape, stress, temperature, pressure, strength, and operational load in real time. Why It Is Better Conventional strain gauges are heavy, bulky, spaced at distant intervals (which leads to lower resolution imaging), and unable to provide real-time measurements. Armstrong's system is virtually weightless, and thousands of sensors can be placed at quarter-inch intervals along an optical fiber the size of a human hair. Because these sensors can be placed at such close intervals and in previously inaccessible regions (for example, within bolted joints, embedded in a composite structure), the high-resolution strain measurements are more precise than ever before. The fiber optic sensors are non-intrusive and easy to install—thousands of sensors can be installed in less time than conventional strain sensors and the system is capable of processing information at the unprecedented rate of 100 samples per second. This critical, real-time monitoring capability enables an immediate and informed response in the event of an emergency and allows for precise, controlled monitoring to help avoid such scenarios. For more information about the full portfolio of FOSS technologies, see DRC-TOPS-37 or visit https://technology-afrc.ndc.nasa.gov/featurestory/fiber-optic-sensing

Langley has developed various technologies to enable the portable detection system, including: - 3-inch electret condenser microphone - unprecedented sensitivity of -45 dB/Hz - compact nonporous windscreen - suitable for replacing spatially demanding soaker hoses in current use - infrasonic calibrator for field use - piston phone with a test signal of 110 dB at 14Hz. - laboratory calibration apparatus - to very low frequencies - vacuum isolation vessel - sufficiently anechoic to permit measurement of background noise in microphones at frequencies down to a few Hz - mobile source for reference - a Helmholtz resonator that provides pure tone at 19 Hz The NASA system uses a three-element array in the field to locate sources of infrasound and their direction. This information has been correlated with PIREPs available in real time via the Internet, with 10 examples of good correlation.

This invention is an imaging method that requires very simple optics on an airborne vehicle, a camera with an appropriate lens, and an area on the ground that provides visual texture. The complexity with this method is in the image processing and not as much with the hardware or positioning, making Background Oriented Schlieren (BOS) an attractive candidate for obtaining high spatial resolution imaging of shock waves and vortices in flight. First, images are obtained of a visually textured background pattern from an appropriate altitude. Next, a series of images are collected of a vehicle in flight below the observer vehicle and over the same spot on the ground that serves as a background pattern. Shock waves are deduced from distortions of the background pattern resulting from the change in refractive index due to density gradients. The invention requires special software to create the schlieren images. The schlieren image is a contour plot of a two-dimensional data array of measured distortions, in pixel units. The results are used by researchers to help understand the flow phenomenon and compare to computational models. The BOS method also yields measured deflection distances, which can be used to determine the strength of a given density gradient. The system design and flight planning were based on the camera characteristics, airplane coordination, and airspace limitations.