Environmental and commercial drivers are leading to a circular economy, where systems and components are routinely recycled or remanufactured. Unlike traditional manufacturing, where components typically have a high degree of tolerance, components in the remanufacturing process may have seen decades of wear, resulting in a wider variation of geometries. This makes it difficult to translate existing automation techniques to perform Non-Destructive Testing (NDT) for such components autonomously. The challenge of performing automated inspections, with off-line tool-paths developed from Computer Aided Design (CAD) models, typically arises from the fact that those paths do not have the required level of accuracy. Beside the fact that CAD models are less available for old parts, these parts often differ from their respective virtual models. This paper considers flexible automation by combining part geometry reconstruction with ultrasonic tool-path generation, to perform Ultrasonic NDT. This paper presents an approach to perform custom vision-guided ultrasonic inspection of components, which is achieved through integrating an automated vision system and a purposely developed graphic user interface with a robotic work-cell. The vision system, based on structure from motion, allows creating 3D models of the parts. Also, this work compares four different tool-paths for optimum image capture. The resulting optimum 3D models are used in a virtual twin environment of the robotic inspection cell, to enable the user to select any points of interest for ultrasonic inspection. This removes the need of offline robot path-planning and part orientation for assessing specific locations on a part, which is typically a very time-consuming phase.

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.

The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

Non-destructive inspection of multi-pass welds for defects is traditionally performed once all layers have been deposited and the sample is at ambient temperature and therefore can lead to complicated and expensive rework, reduced throughput and higher lead times. By performing inspection either as the weld is deposited, or between weld passes, it is possible to identify defects earlier in the process and rectify them. Traditional ultrasonic inspection is severely limited in this application due to the high temperatures associated with the welding process and therefore, the authors describe a novel high-temperature ultrasound phased array roller probe to perform robotically delivered in-process inspection of multipass welds. The new roller probe is able to operate at temperatures up to 350 °C and perform angled weld inspection using 55° transverse waves. The wheel probe's endless rotation enables continuous inspection and makes it well suited to integrate within automated environments commonly employed for high integrity multipass welding applications. The probe demonstrated capability to detect calibration side drilled holes at room temperature and artificial defects embedded into a real weld at high temperature. The experimental results indicate potential to industrialise this prototype in the future.

The automation of robotically delivered nondestructive evaluation inspection shares many aims with traditional manufacture machining. This paper presents a new hardware and software system for automated thickness mapping of largescale areas, with multiple obstacles, by employing computer-aided drawing (CAD)/computer-aided manufacturing (CAM)-inspired path planning to implement control of a novel mobile robotic thickness mapping inspection vehicle. A custom postprocessor provides the necessary translation from CAM numeric code through robotic kinematic control to combine and automate the overall process. The generalized steps to implement this approach for any mobile robotic platform are presented herein and applied, in this instance, to a novel thickness mapping crawler. The inspection capabilities of the system were evaluated on an indoor mock-inspection scenario, within a motion tracking cell, to provide quantitative performance figures for positional accuracy. Multiple thickness defects simulating corrosion features on a steel sample plate were combined with obstacles to be avoided during the inspection. A minimum thickness mapping error of 0.21 mm and a mean path error of 4.41 mm were observed for a 2 m ² carbon steel sample of 10-mm nominal thickness. The potential of this automated approach has benefits in terms of repeatability of area coverage, obstacle avoidance, and reduced path overlap, all of which directly lead to increased task efficiency and reduced inspection time of large structural assets.

Acoustic metamaterials have recently become of interest for their ability to attenuate sound by breaking the mass-density law. In this paper, acoustic metamaterials based on Helmholtz resonators and capable of attenuating sound up to 30 dB are fabricated for sound absorption applications in the small scale. The proposed metamaterials are subwavelength at a factor of λ/12 with respect to the lateral dimension of the units. The directional response due to the position of the acoustic source on the sound attenuation provided by the metamaterial is investigated by controlling the location of a loudspeaker with a robot arm. To enhance and broaden the absorption bands, structural modifications are added such that overtones are tuned to selected frequencies and membranes are included at the base of the resonators. This design is made possible by innovative 3-D printing techniques based on stereolithography and on the use of specific UV-curable resins. These results show that these designs could be used for sound control in small-scale electroacoustic devices and sensors.