Miniature mobile sensor platforms for condition monitoring of structures

In this paper, a wireless, multisensor inspection system for nondestructive evaluation (NDE) of materials is described. The sensor configuration enables two inspection modes-magnetic (flux leakage and eddy current) and noncontact ultrasound. Each is designed to function in a complementary manner, maximizing the potential for detection of both surface and internal defects. Particular emphasis is placed on the generic architecture of a novel, intelligent sensor platform, and its positioning on the structure under test. The sensor units are capable of wireless communication with a remote host computer, which controls manipulation and data interpretation. Results are presented in the form of automatic scans with different NDE sensors in a series of experiments on thin plate structures. To highlight the advantage of utilizing multiple inspection modalities, data fusion approaches are employed to combine data collected by complementary sensor systems. Fusion of data is shown to demonstrate the potential for improved inspection reliability

An evaluation of the effectiveness of continuous thin film processing in a spinning disc reactor for bulk free-radical photo-copolymerisation

AbstractThis paper reports on UV-initiated free-radical copolymerisation of vinyl acetate with n-butyl acrylate (VAc-BA) under conditions of thin film flow in a spinning disc reactor (SDR). Almost 40% overall monomer conversion can be achieved in under 5s under optimised operating conditions in the SDR, with controlled molecular weight properties of the copolymer, highlighting the good levels of mixing in the film. Residence time on the SDR is a limiting factor in the extent of conversion achievable in a single pass. Comparison with a static film demonstrates the superiority of the SDR in maintaining a high overall rate of polymerisation. Composition of the copolymer formed in the SDR indicates that, due to its plug flow behaviour, the SDR cannot address the inherent problem of compositional drift.We have shown that efficiency of light absorption is dictated by conditions favouring longest UV exposure times, rather than thinner films on the disc. Initiator decomposition efficiency, an important consideration in the overall rate of the co-polymerisation, is enhanced by lower fluid flowrates. This study highlights the promising technology offered by the SDR in combination with UV irradiation for the exploitation of photo-copolymerisation as a viable method for bulk copolymer synthesis

Vision guided robotic inspection for parts in manufacturing and remanufacturing industry

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

Data-driven analysis of ultrasonic pressure tube inspection data

Pressure tubes are critical components of the CANDU reactors and other pressurized heavy water type reactors, as they contain the nuclear fuel and the coolant. Manufacturing flaws, as well as defects developed during the in-service operation, can lead to coolant leakage and can potentially damage the reactor. The current inspection process of these flaws is based on manually analyzing ultrasonic data received from multiple probes during planned, statutory outages. Recent advances on ultrasonic inspection tools enable the provision of high resolution data of significantly large volumes. This is highlighting the need for an efficient autonomous signal analysis process. Typically, the automation of ultrasonic inspection data analysis is approached by knowledge-based or supervised data-driven methods. This work proposes an unsupervised data-driven framework that requires no explicit rules, nor individually labeled signals. The framework follows a two-stage clustering procedure that utilizes the DBSCAN density-based clustering algorithm and aims to provide decision support for the assessment of potential defects in a robust and consistent way. Nevertheless, verified defect dimensions are essential in order to assess the results and train the framework for unseen defects. Initial results of the implementation are presented and discussed, with the method showing promise as a means of assessing ultrasonic inspection data

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

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

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