Unmanned aerial vehicles (UAVs) are seeing increasing adoption to automated remote and in situ inspection of industrial assets, removing the need for hazardous manned access. Aerial manipulator architectures supporting pose-decoupled exertion of force and torque would further enable UAV deployment of contact-based transducers for sub-surface structural health assessment. Herein, for the first time, we introduce an over-actuated multirotor deploying a dry-coupled ultrasonic wheel probe as a novel means of wall thickness mapping. Using bi-axial tilting propellers in a unique tricopter layout, this system performs direct thrust vectoring for efficient omnidirectional flight and application of interaction forces. In laboratory testing, we demonstrate stable and repeatable probe deployment in a variety of representative asset inspection operations. We obtain a mean absolute error (MAE) in measured thickness of under 0.10 mm when measuring an aluminum sample with varying wall thickness. This is maintained over repeated exit and reentry of surface contact and when the sample is mounted vertically or on the underside of a 45° overhang. Furthermore, when rolling the probe dynamically across the sample surface in an area scanning modality, an MAE in wall thickness below 0.28 mm is recorded. Multi-modal operational confidence bounds of the system are thereby quantitatively defined. Note to Practitioners—Motivation for this article stems from the desire to enhance the speed and level of insight into structural health currently offered through remote aerial inspection processes. We approach this by integration of a thrust vectoring multirotor platform with a dry-coupling wheel probe for aerial ultrasonic thickness measurement. This system reliably presses the probe into the target surface and obtains point measurements across various surface orientations without a stabilizing frame. This broadens applicability and permits novel inspections where couplant gel would otherwise contaminate the surface and require manual cleaning. We profile thickness along a scanned linear section, a mode suited to corrosion mapping of large surface areas such as petrochemical storage tanks, pipework, or similar assets. We also make detailed consideration toward measurement accuracy, repeatability, and localization, an aspect commonly overlooked in literature. Future work to characterize variable friction effects currently limiting rolling scan speed and measurement coverage density may be beneficial. Quantitative study of the effectiveness of dry-couplant in the presence of any uncommon surface contaminants specific to a desired use-case is also advised.

In terms of safety and convenience, an Unmanned Aerial Vehicle (UAV) offers significant benefits when conducting remote NDT evaluations by mitigating hazards and inefficiencies associated with manned access. Traditionally, UAV remote inspections rely on high-resolution cameras, providing a visual overview of surface condition. This photogrammetric inspection, however, cannot distinguish minute discontinuities or deformations beneath a surface coating. Ultrasonic inspection is a Non-Destructive Testing (NDT) method conventionally used in corrosion mapping. Surface contacting ultrasonic transducers offer the potential for internal inspection of an industrial asset, providing enhanced structural integrity information. However, manually piloting a UAV with sufficient surface proximity to perform a detailed, contact-based examination requires a highly developed skillset and intense concentration. Limitations of payload mass and electronic interference also represent significant challenges to be overcome. Addressing such issues, this paper demonstrates the implementation of an autonomous UAV system with an integrated ultrasonic contact measurement payload. The prototype is autonomously guided and undertakes the contact thickness measurement process without manual intervention.

The mobility of an Unmanned Aerial Vehicle (UAV) offers significant benefits when deploying remote Non-Destructive Testing (NDT) inspections of large-scale assets. Ultrasonic inspection is primarily a contact-based NDT method, that grants the opportunity to remotely monitor the structural health of an industrial asset with enhanced internal integrity information. Presented in this paper is an implementation of an autonomous UAV system, equipped with an ultrasonic thickness measurement payload. This system is designed to conduct ultrasonic inspections of non-magnetic facilities and industrial infrastructure where surface adhesion cannot be achieved magnetically. Operating within a laboratory environment, this system autonomously positioned the transducer on a vertically mounted, unpainted, aluminium sample and completed an ultrasonic thickness measurement without manual intervention. An onboard laser scanner provided instantaneous UAV alignment and standoff error measurements versus the sample’s surface normal vector. While inspecting a region of the aluminium sample with 12.92 mm nominal thickness, the UAV system demonstrated a measurement error of 0.03 mm. During this process, the standard deviation of the craft’s positional error was recorded to be below 63.26 mm, accompanied by an angular alignment error versus the surface normal vector of below 2.71°. The accuracy of the UAV deployed inspection, including thickness measurement accuracy and positional accuracy, depends on many factors. As such, transducer alignment constraints, electrical noise and UAV stability are investigated and discussed. Findings from this paper may be taken to inform future research regarding autonomous airborne ultrasonic inspection of constructed infrastructure and industrial facilities.

The creation of unwrapped stitched images of pipework internal surfaces is being increasingly used to augment routine visual inspection. A significant challenge to the creation of these stitched images is the need to estimate the pose and position of the camera for each frame, which is often alleviated through the use of a mechanical centralizer to ensure the camera is held in the center of the pipe. This article proposes a novel method for image centralization and pose estimation, which is particularly beneficial to circumstances where mechanical centralization is impractical. The approach involves post-inspection centralization of the captured video, by first estimating the probe’s position relative to the pipe, using an integrated laser ring projector combined with the camera sensor, and then using this position to unwrap the image, so it produces an undistorted view of the pipe interior (equivalent to unwrapping a centralized view). These unwrapped images are then stacked to produce a stitched image of the pipe interior. In this paper pose estimation was successfully demonstrated to have a 90% confidence interval of ±0.5 mm and ±0.5° in translation and rotation changes. This pose estimation is then used to create stitched images for both a visual test card image mounted inside a pipe and an aluminum pipe sample with artificial defects, in both cases demonstrating near equivalent results to those obtained using traditional mechanical centralization.