Advancing Metrology at Mach Speed
Drone Mounted Inspection Breaks Barriers for F-35
The F-35 Lightning II is an all-weather stealth combat aircraft that is intended to perform warfare strike missions and electronic surveillance capabilities at speeds up to 1.6 Mach. Composites comprise 35% of the airframe weight, with the majority being bismaleimide, as well as some carbon nanotube-re-enforced epoxy, which has a tensile strength approximately 100-times greater than steel. Any deviations in external dimensions can interfere with stealth capabilities, and at supersonic speeds, prove catastrophic to both plane and pilot.
Therefore, it is critical that the “as-built” metrology is confirmed as “near perfect” to the design. Currently, inspection is done by hand at Lockheed Martin’s production facility in Fort Worth, Texas. Gantries are assembled above the craft and workers use handheld scanners extended at arm’s length. This manual process introduces variables and puts workers at risk as they attempt to straddle the smooth contoured surfaces of the aircraft.
In an attempt to generate faster results, while increasing accuracy and safety for all involved - factory worker, customer and user – the transition to digital inspection is required.
Many devices currently allow for digital measurement of assemblies on a small level. However, the problem is how to scale up existing commercial equipment to inspect large, completely constructed projects, such as a large-body aircraft, ships and even submarines, while still holding to tight tolerances.
“For 100 years in aviation we have been using humans for quality assurance, but roughly 75% of my costs come from inspection, and 66% of that requires humans to perform, which involves some degree of subjectivity,” notes Chris Colaw, Lockheed Fellow, Quality & Mission Success. “But in our digital future we need to embrace things in a different way.”
Lockheed Martin sought to find an automated metrology solution to confirm and document measurements to the tightest tolerances in a faster, more accurate, and more repeatable process.
“We were doing our own research on what a digital future would look like, but we opted to work with CAD/CAM since they presented an opportunity to partner with a scanner company and the University of Texas on drone control,” says Colaw. “That saved us from having to do all the work on our own. The collaboration was a natural fit.”
In the spring of 2021, CAD/CAM Services won a Small Business Technology Transfer Research (STTR) award to solve surface metrology issues for the F-35 fighter jet. Its job was to assemble a team of industry-leading suppliers that would deliver to Lockheed Martin a drone-mounted scanner that can accurately (± 0.025mm) measure large assemblies and transmit that data to a system that ultimately creates CAD files for first article inspection or maintenance purposes. The company, based in Celina, Texas, has provided 3D modeling and CAD conversion services worldwide since 1988. Its customers include Boeing, Litton-Ingalls Shipbuilding, the U.S. Navy and Air Force.
“We are taking various commercial, off-the-shelf components, slightly modifying them, and tying it all together to create a new system to solve a problem that is needed by industry,” says Scott Shuppert, CEO of CAD/CAM Services.
Integrating the Elements
The synergistic result started with the drone and the camera inspection software, which had to actively search for issues such as: dents, cracks, deformations, corrosion, and alignment issues, and then reconcile the measured results to the design model.
“Our team decided we needed to have both a drone and a robot to inspect on the assembly line,” continues Shuppert. “The drones will fly above and around the craft, while the wheel-mounted robot will work underneath the plane. For the drones, we went with Airgility because they had most of what we were looking for.”
Based in College Park, MD, Airgility, Inc. specializes in integrating AI and autonomy into their unmanned aerial vehicles (UAV). Their drones met the requirements for maneuverability (continuously adjustable tilt motors), control accuracy (ability to hold a flight path to ±6 mm), compliance (NDAA and TAA) and carrying capacity. The guidance and control (G&C) system utilizes a multi-loop architecture that computes the error between a desired reference position and the current drone position, and then synthesizes the desired 3-axis movements of the rotors at an 80 Hz sampling rate. This allows the drone to operate without the benefit of global positioning satellites.
“Since GPS signals can’t penetrate a heavily built aircraft hangar, the drone has to rely on the internal G&C system,” says Pramod Raheja, CEO and co-founder of Airgility. “This system regulates the angular orientation of the drone via an independent thrust vectoring system so it can follow a 3-D reference trajectory based on the physical dimensions of the aircraft.”
Raheja explained how situational awareness is achieved by an algorithm that incorporates data from numerous, redundant, sensors. This allows the craft to fly in narrow spaces, like over and under a gantry or aircraft wing. Also included in the intelligence is a self-contained onboard AI failsafe mechanism, so if the software crashes for any reason the drone will simply back away, avoid any obstacles, and land itself. Collision avoidance is extremely important, since in addition to the aircraft itself, the Lockheed Martin factory floor presents numerous physical obstacles including scaffolding, pilot ladders, auxiliary power units, tails, canopies, and people.
“Before we let a drone fly next to an $80 million jet, we wanted to test it within a lab environment,” notes Lockheed Martin’s Colaw.
This is where Animesh Chakravarthy, Ph.D., Professor of Mechanical and Aerospace Engineering and Flight Control at the University of Texas at Arlington, was brought in. Chakravarthy’s research in collision avoidance has been recognized by his receiving a prestigious CAREER award from the National Science Foundation (NSF).
“The goal is to have the drone performing multiple precise orbits around the aircraft, at just the right speed, while at the same time ensuring that the scanner is properly oriented towards the aircraft,” explains Chakravarthy. “The trick is not getting so close as to cause a collision, but not so far away as to distort the readings.”
Chakravarthy’s advanced students will develop the mechanical robot that carries the scanner under the plane along the plant floor. It will be equipped with its own G&C system— conceptually similar to that of the drone—that will autonomously track the reference trajectory while ensuring collision avoidance.
Expanding the Capability of Drone-Integrated Metrology
The current STTR award includes options for even further advancements. Of great importance to Lockheed Martin is identifying any delamination within the composite skin of the F-35. Since separation of the layers and voids cannot always be seen or measured from the surface, a non-destructive testing method is necessary. This is where highly sensitive IR cameras can be used to inspect beneath the composite surface of the craft to effectively visualize and identify any anomalies.
“The IR flash lamps act as an excitation source to transfer heat through the material,” says Desmond Lamont, Global Business Development Manager for Teledyne FLIR. “Since voids and gaps don’t transfer heat as efficiently as a solid does, the heat will build and the camera identifies these hot spots and points out the adjacent fault areas.”
Cutting the Cord
While there were a number of challenges the team encountered, the issue of removing the wiring tether from the scanner was considered one of the most significant. A wireless approach is much safer and more capable of dodging personnel and physical infrastructure on the factory floor. The Airgility team will solve this problem by utilizing AI drones that only transmit crucial data, thus greatly reducing bandwidth.
“Since the intelligent drone knows what anomalies to look for, it only sends that info and ignores the expected results,” points out Raheja. “Therefore, you don’t need to transmit a lot of data continuously.”
The ultimate result of this collaboration is a reliable, highly accurate (plus or minus 0.025 mm) inspection platform for large body craft that removes human error and safety risk from the manufacturing environment.
This article was written by Dr. David Rizzo for Lockheed Martin (Bethesda, MD). For more information, visit here .