Synthetic aperture guided wave imaging using a mobile sensor platform

This oral session at conference looks at synthetic aperture guided wave imaging using a mobile sensor platfor

A noncontact ultrasonic platform for structural inspection

Miniature robotic vehicles are receiving increasing attention for use in nondestructive testing (NDE) due to their attractiveness in terms of cost, safety, and their accessibility to areas where manual inspection is not practical. Conventional ultrasonic inspection requires the provision of a suitable coupling liquid between the probe and the structure under test. This necessitates either an on board reservoir or umbilical providing a constant flow of coupling fluid, neither of which are practical for a fleet of miniature robotic inspection vehicles. Air-coupled ultrasound offers the possibility of couplant-free ultrasonic inspection. This paper describes the sensing methodology, hardware platform and algorithms used to integrate an air-coupled ultrasonic inspection payload into a miniature robotic vehicle platform. The work takes account of the robot's inherent positional uncertainty when constructing an image of the test specimen from aggregated sensor measurements. This paper concludes with the results of an automatic inspection of a aluminium sample

Error Model of Misalignment Error in a Radial 3D Scanner

A radial 3D, structured light scanner, was developed from a laser projector and a wide field of view machine vision camera to inspect two - four inch diameter pipers, primarily in the nuclear industry. For identifying the nature and the spatial extent of defective regions, the system constructs a surface point cloud. A dominant source of error in the system is caused by manufacturing tolerances which leads to misalignment between the laser projector and the camera. This causes a triangulation error, reducing the accuracy of the result. In this paper, the error model of the misalignment of the laser and image plane. For a given target distance, we derive an almost linear relationship between angular error in degrees and the error in reported radius (distance from the probe to the surface) in mm and found that for the target 0.1 mm accuracy on a 4 inch pipe, the misalignment needs to be controlled to less than 0.05 degrees. Future work will consider a post manufacturing calibration routine to compensate for this misalignment

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, the study investigates the accuracy and performance of the ranger sensor when scanning large industrial materials over a range of distances. Additionally, the study 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 visualisation was undertaken on a number of parameters, not limited to traditional range data but also received intensity and amplifier gain. This work 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 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 aluminium surface from 6.48% to 1.39% of the true distance range

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 non-destructive 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

Index based triangulation method for efficient generation of large three-dimensional ultrasonic C-scans

The demand for high speed ultrasonic scanning of large and complex components is driven by a desire to reduce production bottlenecks during the non-destructive evaluation of critical parts. Emerging systems (including robotic inspection) allow the collection of large data volumes in short time spans, compared to existing inspection systems. To maximize throughput, it is crucial that the reconstructed inspection data sets are generated and evaluated rapidly without a loss of detail. This requires new data visualization and analysis tools capable of mapping complex geometries whilst guaranteeing full part coverage. This paper presents an entirely new approach for the visualization of three-dimensional ultrasonic C-scans, suitable for application to high data throughput ultrasonic phased array inspection of large and complex parts. Existing reconstruction approaches are discussed and compared with the new Index Based Triangulation (IBT) method presented. The IBT method produces 3D C-scan representation, presented as coloured tessellated surfaces, and the approach is shown to work efficiently even on challenging geometry. An additional differentiating characteristic of the IBT method is that it allows easy detection of lack of coverage (an essential feature to ensure that inspection coverage can be guaranteed on critical components). Results demonstrate that the IBT C-scan generation approach runs over 60 times faster than a C-scan display based on Delaunay triangulation and over 500 times faster than surface reconstruction C-scans. In summary the main benefits of the new IBT technique are: • High speed generation of C-scans on large ultrasonic data sets (orders of magnitude improvement over surface reconstruction C-Scans) • Ability to operate efficiently on 3D mapped data sets (allowing 3D interpretation of C scans on complex geometry components) • Intrinsic indication of lack of inspection coverag

Development of a novel probe for remote visual inspection of pipework

The interior visual inspection of 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 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 paper describes the development of a new visual inspection system designed for inspecting 3 - 6 inch diameter pipes. The system uses a high resolution camera and structure from motion (SFM) algorithm to compute the trajectory of the probe through the pipe. In addition a laser profiler is used to measure the inner surface of the pipe and generate a meshed point cloud. The camera images are projected onto the mesh and the final output of the system is a photorealistic 3-D model of the internal surface of the pipework

The influence of the spatial distribution of 2D 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 2D 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 tend 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 dataset are also provided

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

A novel visual pipework inspection system

The interior visual inspection of pipelines in the nuclear industry is a safety critical activity conducted during outages to ensure the continued safe and reliable operation of plant. Typically, the video output by a manually deployed probe is viewed by an operator looking to identify and localise surface defects such as corrosion, erosion and pitting. However, it is very challenging to estimate the nature and extent of defects by viewing a large structure through a relatively small field of view. This work describes a new visual inspection system employing photogrammetry using a fisheye camera and a structured light system to map the internal geometry of pipelines by generating a photorealistic, geometrically accurate surface model. The error of the system output was evaluated through comparison to a ground truth laser scan (ATOS GOM Triple Scan) of a nuclear grade split pipe sample (stainless steel 304L, 80mm internal diameter) containing defects representative of the application – the error was found to be submillimetre across the sample