Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction

Tessellated surfaces generated from point clouds typically show inaccurate and jagged boundaries. This can lead to tolerance errors and problems such as machine judder if the model is used for ongoing manufacturing applications. This paper introduces a novel boundary point detection algorithm and spatial FFT-based filtering approach, which together allow for direct generation of low noise tessellated surfaces from point cloud data, which are not based on pre-defined threshold values. Existing detection techniques are optimized to detect points belonging to sharp edges and creases. The new algorithm is targeted at the detection of boundary points and it is able to do this better than the existing methods. The FFT-based edge reconstruction eliminates the problem of defining a specific polynomial function order for optimum polynomial curve fitting. The algorithms were tested to analyse the results and measure the execution time for point clouds generated from laser scanned measurements on a turbofan engine turbine blade with varying numbers of member points. The reconstructed edges fit the boundary points with an improvement factor of 4.7 over a standard polynomial fitting approach. Furthermore, through adding artificial noise it has been demonstrated that the detection algorithm is very robust for out-of-plane noise lower than 25% of the cloud resolution and it can produce satisfactory results when the noise is lower than 75%

Practical constraints on real time Bayesian filtering for NDE applications

An experimental evaluation of Bayesian positional filtering algorithms applied to mobile robots for Non-Destructive Evaluation is presented using multiple positional sensing data – a real time, on-robot implementation of an Extended Kalman and Particle filter was used to control a robot performing representative raster scanning of a sample. Both absolute and relative positioning were employed – the absolute being an indoor acoustic GPS system that required careful calibration. The performance of the tracking algorithms are compared in terms of computational cost and the accuracy of trajectory estimates. It is demonstrated that for real time NDE scanning, the Extended Kalman Filter is a more sensible choice given the high computational overhead for the Particle filter

Off-line scan path planning for robotic NDT

This work presents computer-aided scan path generation for robotic non-destructive testing of complex shaped test-pieces. Off-line programmed scan path was used to robotically inspect an aluminium fixed leading edge skin panel of an aircraft wing by means of swept frequency eddy currents method. Eddy currents probe was deployed by means of a six-axis robotic arm KUKA KR5 arc. Reverse engineering of the test-piece was carried out to reconstruct CAD model of its surface. Positioning accuracy of the performed continuous scan was measured with a laser tracker in accordance with ISO 9283:1998 and is reported in the paper. The positional uncertainty of the NDT scan calculated as the standard deviation of the measured path coordinates from the command path coordinates does not exceed 0.5 mm which is rather moderate taking in account uncertainties associated with the off-line robot programming

Introducing a new method for efficient visualization of complex shape 3D ultrasonic phased-array C-scans

Automated robotic inspection systems allow the collection of large data volumes, compared to existing inspection systems. To maximize the throughput associated with the nondestructive evaluation phase, it is crucial that the reconstructed inspection data sets are generated and examined rapidly without a loss of detail. Data analysis often becomes the bottleneck of automated inspections. Therefore, new data visualization tools, suitable to screen the NDT information obtained through robotic systems, are urgently required. This paper presents a new approach, for the generation of three-dimensional ultrasonic C-scans of large and complex parts, suitable for application to high data throughput ultrasonic phased array inspection. This approach produces 3D C-scan presented as colored tessellated surfaces and the approach works efficiently on challenging geometry, with concave and convex regions. Qualitative and quantitative results show that the approach runs up to 500 times faster than other C-scan visualization techniques

Remote inspection of wind turbine blades using UAV with photogrammetry payload

Visual Inspection is regularly used as a method of non-destructive testing (NDT) to find defects in large component structures. Wind turbine blades, regularly located in isolated environments, are typically difficult to access. In order to reduce operational and maintenance costs and extend asset lifetime, a project for the remote inspection of blades to accurately assess surface integrity is being undertaken. The remote inspection solution combines an unmanned aerial vehicle (UAV) with a photogrammetry payload to provide visual reconstruction of a blade for a holistic condition overview. Photogrammetric software is used to process the captured images to generate a 3D blade profile. A waypoint guidance algorithm controls the UAV to complete a full blade surface capture at constant distance, minimising motion blur. The results provide an accurate 3D reconstruction of the used blade complete with defects, discontinuities and markings and hence visual inspection using UAV combined with photogrammetry has been successfully implemented

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 KR5 arc HW, used to perform quality inspections of components with complex shapes. Metrology techniques such as laser tracking and large volume photogrammetry 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. Despite of the significant maximum inaccuracies, uncertainty of a robotic scanning application is estimated to be 0.5mm. 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 center point calibration, the reference coordinate system transformation and the low accuracy of the photogrammetry system

A new probe concept for internal pipework inspection

The interior visual inspection of nuclear pipework is a critical inspection activity required to ensure the continued safe, reliable operation of plant and thus avoid costly outages. Typically, the video output from a manually deployed probe is viewed by an operator online with the task of identifying and estimating the location of surface defects such as cracks, corrosion and pitting. However, it is very difficult to estimate the nature and spatial extent of defects from the often disorientating small field of view video of a relatively large structure. This work describes a new visual inspection system incorporating a wide field of view machine vision camera and additional sensors designed for inspecting 3 - 6 inch diameter pipes. The output of the system is a photorealistic model of the internal surface of the pipework. The generation of this model relies upon a core component of the system in the form of image feature extraction which estimates camera location. This paper considers the accuracy of this estimation as a function of the number and configuration of the extracted image features

Spatial calibration of large volume photogrammetry based metrology systems

Photogrammetry systems are used extensively as volumetric measurement tools in a diverse range of applications including gait analysis, robotics and computer generated animation. For precision applications the spatial inaccuracies of these systems are of interest. In this paper, an experimental characterisation of a six camera Vicon T160 photogrammetry system using a high accuracy laser tracker is presented. The study was motivated by empirical observations of the accuracy of the photogrammetry system varying as a function of location within a measurement volume of approximately 100 m3. Error quantification was implemented through simultaneously tracking a target scanned through a sub-volume (27 m3) using both systems. The position of the target was measured at each point of a grid in four planes at different heights. In addition, the effect of the use of passive and active calibration artefacts upon system accuracy was investigated. A convex surface was obtained when considering error as a function of position for a fixed height setting confirming the empirical observations when using either calibration artefact. Average errors of 1.48 mm and 3.95 mm were obtained for the active and passive calibration artefacts respectively. However, it was found that through estimating and applying an unknown scale factor relating measurements, the overall accuracy could be improved with average errors reducing to 0.51 mm and 0.59 mm for the active and passive datasets respectively. The precision in the measurements was found to be less than 10 μm for each axis

Bipartite guidance, navigation and control architecture for autonomous aerial inspections under safety constraints

In this work the autonomous flight of a drone for inspection of sensitive environments is considered. Continuous monitoring, the possibility of override and the minimisation of the on-board computational load are prioritized. The drone is programmed with a Lyapunov vector guidance and nonlinear control to fly a trajectory passed, leg after leg, by a remote ground station. GPS is the main navigation tool used. Computational duties are split between the ground station and the drone’s on board computer, with the latter dealing with the most time critical tasks. This bipartite autonomous system marries recent advancements in autonomous flight with the need for safe and reliable robotic systems to be used for tasks such as inspection or structural health monitoring in industrial environments. A test case and inspection data from a test over flat lead roof structure are presented

Fast ultrasonic phased array inspection of complex geometries delivered through robotic manipulators and high speed data acquisition instrumentation

Performance of modern robotic manipulators has enabled research and development of fast automated non-destructive testing (NDT) systems for complex geometries. This paper presents recent outcomes of work aimed at removing the bottleneck due to data acquisition rates, to fully exploit the scanning speed of modern 6-DoF manipulators. State of the art ultrasonic instrumentation has been integrated into a large robot cell to enable fast data acquisition, high scan resolutions and accurate positional encoding. A fibre optic connection between the ultrasonic instrument and the server computer enables data transfer rates up to 1.6GB/s. Multiple data collection methods are compared. Performance of the integrated system allows traditional ultrasonic phased array scanning as well as full matrix capture (FMC). In FMC configuration, linear scan speeds up to 156mm/s with 64 pulses per frame are achieved - this speed is only constrained by the acoustic wave propagation in the component. An 8x increase of the speed (up to 1.25m/s) can be achieved using multiple transmission elements, reaching the physical limits for acceptable acoustic alignment of transmission and reception paths. Scan results, relative to a 1.2m × 3m carbon fibre sample, are presented