Charles Norman MacLeod

Flexible integration of robotics, ultrasonics and metrology for the inspection of aerospace components

The performance of modern robotic manipulators has allowed research in recent years, for the development of fast automated non-destructive testing (NDT) of complex geometries. Contemporary robots are well suited for their accuracy and flexibility when adapting to new tasks. Several robotic inspection prototype systems and a number of commercial products have been created around the world. This paper describes the latest progress of a new phase of the research applied to a composite aerospace component of size 1 by 3 metres. A multi robot flexible inspection cell was used to take the fundamental research and the feasibility studies to higher technology readiness levels, all set for future industrial exploitation. The robot cell was equipped with high accuracy and high payload robots, mounted on 7 metre tracks, and an external rotary axis. A robotically delivered photogrammetry technique was first used to assess the position of the components placed within the robot working envelope and their deviation to CAD. Offline programming was used to generate a scan path for phased array ultrasonics testing (PAUT) which was implemented using high data rate acquisition from a conformable wheel probe. Real-time robot path-correction, based on force-torque control (FTC), was deployed to achieve the optimum ultrasonic coupling and repeatable data quality. New communication software was developed that enabled the simultaneous control of the multiple robots performing different tasks and the reception of accurate positional feedback positions. All aspects of the system were controlled through a purposely developed graphic user interface that enabled the flexible use of the unique set of hardware resources, the data acquisition, visualisation and analysis. This work was developed through the VIEWS project (Validation and Integration of Manufacturing Enablers for Future Wing Structures), part funded by the UK’s innovation agency (Innovate UK).

Quantifying and Improving Laser Range Data When Scanning Industrial Materials

This paper presents the procedure and results of a performance study of a miniature laser range scanner, along with a novel error correction calibration. Critically, this paper investigates the accuracy and performance of the ranger sensor when scanning large industrial materials over a range of distances. In addition, this paper investigated the effects of small orientation angle changes of the scanner, in a similar manner to which it would experience when being deployed on a mobile robotic platform. A detailed process of error measurement and visualization was undertaken on a number of parameters, not limited to traditional range data but also received intensity and amplifier gain. This paper highlights that significant range distance errors are introduced when optically laser scanning common industrial materials, such as aluminum and stainless steel. The specular reflective nature of some materials results in large deviation in range data from the true value, with mean root mean square error (RMSE) errors as high as 100.12 mm recorded. The correction algorithm was shown to reduce the RMSE error associated with range estimation on a planar aluminum surface from 6.48% to 1.39% of the true distance range.

Clinical monitoring of tooth wear progression in patients over a period of one year using CAD/CAM

PURPOSE The aim of this study was to clinically monitor the progression of tooth wear over a period of 1 year in a cohort of referred tooth wear patients through the use of a computer-aided design/computer-assisted manufacture (CAD/CAM) scanner and a standardized scanning/assessment methodology. MATERIALS AND METHODS Polyether impressions were made of 11 participants (130 teeth) at baseline and at 1 year. Impressions were poured in type IV dental stone and the anterior teeth were 3D scanned. A surface-matching software was used to compare 1-year and baseline scans and identify any dimensional differences. RESULTS Parafunctional habits were reported by all patients. All participants exhibited tooth wear ≥ 140 μm in depth and extending to ≥ 280 μm in at least one tooth. Maxillary central incisors were the most commonly and severely affected teeth. CONCLUSION The ability of the developed CAD/CAM scanning methodology in clinical monitoring of tooth wear was demonstrated. Further research is needed to assess its practicality in large-scale epidemiologic tooth wear studies.

Assessing the accuracy of industrial robots through metrology for the enhancement of automated non-destructive testing

This work presents the study of the accuracy of an industrial robot, KUKA KR5 arc HW, used to perform quality inspections of components with complex shapes. Laser tracking and large volume photo grammetry were deployed to quantify both pose and dynamic path accuracies of the robot in accordance with ISO 9283:1998. The overall positioning pose inaccuracy of the robot is found to be almost 1 mm and path inaccuracy at 100% of the robot rated velocity is 4.5 mm. The maximum pose orientation inaccuracy is found to be 14 degrees and the maximum path orientation inaccuracy is 5 degrees. Local positional errors manifest pronounced dependence on the position of the robot end effector in the working envelope. The uncertainties of the measurements are discussed and deemed to be caused by the tool centre point calibration, the reference coordinate system transformation and the low accuracy of the photogrammetry system.

Automated full matrix capture for industrial processes

Full matrix capture (FMC) ultrasound can be used to generate a permanent re-focusable record of data describing the geometry of a part; a valuable asset for an inspection process. FMC is a desirable acquisition mode for automated scanning of complex geometries, as it allows compensation for surface shape in post processing and application of the total focusing method. However, automating the delivery of such FMC inspection remains a significant challenge for real industrial processes due to the high data overhead associated with the ultrasonic acquisition. The benefits of NDE delivery using six-axis industrial robots are well versed when considering complex inspection geometries, but such an approach brings additional challenges to scanning speed and positional accuracy when combined with FMC inspection. This study outlines steps taken to optimize the scanning speed and data management of a process to scan the diffusion bonded membrane of a titanium test plate. A system combining a KUKA robotic arm and a reconfigurable FMC phased array controller is presented. The speed and data implications of different scanning methods are compared, and the impacts on data visualization quality are discussed with reference to this study. For the 0.5 m2 sample considered, typical acquisitions of 18 TB/m2 were measured for a triple back wall FMC acquisition, illustrating the challenge of combining high data throughput with acceptable scanning speeds.

Automatic ultrasonic robotic array

A novel, autonomous reconfigurable ultrasonic phased array inspection robot for non-destructive evaluation (NDE) is presented. The robotic system significantly will reduce manual labor over current inspection regimes, as well as enabling inspection of inaccessible/hazardous areas such as those found in the nuclear and petrochemical industries. It will offer three quantitative benefits: improved inspection accuracy, improved safety and reduced inspection costs. The current major innovation is in embedding ultrasonic phased array technology into a small form-factor robotic vehicle, overcoming issues in ultrasonic coupling, miniaturized electronics and robot positioning. This paper presents an overview of the robot specification and system architecture along with details of a specific inspection scenario where the robot is required to inspect a saddle weld found in reheat bifurcation. This weld is formed from the intersection of two 60 mm thick steel pipes with diameters 500 and 300 mm. The robot will be capable of tracking the weld from either pipe, projecting an ultrasonic beam normal to the direction of travel. The design of a 2 MHz, 16 element embedded phased array controller is presented. A timing model of the controller details the throughput required to enable the robot to perform ultrasonic inspection while tracking the weld at 20 mm/s. The paper also considers robot positional estimation. The nature of the inspection prohibits the use of external positioning systems so the system is limited to on-board sensors, namely wheels encoders, a six axis inertial sensor and a surface feature tracking camera. The results section focuses on the characterization of inspection performance, driven in part by the ultrasonic phased array controller and robot positional estimation. A-Scans are presented to show the SNR of each array channel which was approximately 24 dB when measuring the back wall echo. It is shown that ultrasonic scan rate is limited by 802.11g wireless transmission from the robot to the host computer.

Active Whisking-Based Remotely Deployable NDE Sensor

The fundamental sensitivity characterization of a novel whisking sensor for applications in nondestructive evaluation is presented. The whisking sensors, originally developed for proximity detection applications in autonomous robotics are evaluated for measurements of surface roughness and surface form change. These surface parameters are the representatives of the typical changes associated with corrosion and surface breaking defects in real structures. The authors demonstrate that the whisking sensor can be used to accurately quantify surface roughness in the range 14-53 μm with excellent correlation to a standard reference. Furthermore, it is shown that that the sensor can detect 14 mm diameter flat bottomed holes with depths ranging from 0.4 to 1.0 mm. In contrast to conventional ultrasonic and eddy current techniques, the sensor is insensitive to surface liftoff, producing an error of only 1.2% for liftoffs of several mm. This liftoff insensitivity is a highly desirable characteristic for real-world deployment of the sensors, and the authors describe how the sensor can be incorporated into autonomous inspection robots.

Machining-Based Coverage Path Planning for Automated Structural Inspection

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 large-scale 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 m2 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.Note to Practitioners—Current industrial robotic inspection approaches largely consist of a manual control of robotic platform motion to desired points, with the aim of producing a number of straight scans for larger areas, often spaced meters apart. The structures featuring large surface area and multiple obstacles are routinely inspected with such manual approaches, which are both labor intensive and error prone, and do not guarantee acquisition of full area coverage. The presented system addresses these limitations through a combined hardware and software approach. Core to the operation of the system is a fully wireless, differential drive crawler with integrated active ultrasonic wheel probe, to provide remote thickness mapping. Automation of the path generation algorithms is produced using the commercial CAD/CAM software algorithms, and this paper sets out an adaptable methodology for producing a custom postprocessor to convert the exported G-codes to suitable kinematic commands for mobile robotic platforms. The differential drive crawler is used in this paper to demonstrate the process. This approach has benefits in terms of improved industrial standardization and operational repeatability. The inspection capabilities of the system were documented on an indoor mock-inspection scenario, within a motion tracking cell to provide quantitative performance figures for the approach. Future work is required to integrate the on-board positioning strategies, removing the dependence on global systems, for full automated deployment capability.

Autonomous and scalable control for remote inspection with multiple aerial vehicles

A novel approach to the autonomous generation of trajectories for multiple aerial vehicles is presented, whereby an artificial kinematic field provides autonomous control in a distributed and highly scalable manner. The kinematic field is generated relative to a central target and is modified when a vehicle is in close proximity of another to avoid collisions. This control scheme is then applied to the mock visual inspection of a nuclear intermediate level waste storage drum. The inspection is completed using two commercially available quadcopters, in a laboratory environment, with the acquired visual inspection data processed and photogrammetrically meshed to generate a three-dimensional surface-meshed model of the drum. This paper contributes to the field of multi-agent coverage path planning for structural inspection and provides experimental validation of the control and inspection results.

The Influence of the Spatial Distribution of 2-D Features on Pose Estimation for a Visual Pipe Mapping Sensor

This paper considers factors which influence the visual motion estimation of a sensor system designed for visually mapping the internal surface of pipework using omnidirectional lenses. In particular, a systematic investigation of the error caused by a non-uniform 2-D spatial distribution of features on the resultant estimate of camera pose is presented. The effect of non-uniformity is known to cause issue and is commonly mitigated using techniques, such as bucketing; however, a rigorous analysis of this problem has not been carried out in the literature. The pipe’s inner surface tends to be uniform and texture poor driving the need to understand and quantify the feature matching process. A simulation environment is described in which the investigation was conducted in a controlled manner. Pose error and uncertainty is considered as a function of the number of correspondences and feature coverage pattern in the form of contiguous and equiangular coverage around a circular image acquired by a fisheye lens. It is established that beyond 16 feature matches between the images, that coverage is the most influential variable, with the equiangular coverage pattern leading to a greater rate of reduction in pose error with increasing coverage. The application of the results of the simulation to a real world data set is also provided.