The NDE industry is under constant pressure to increase inspection speeds, while simultaneously reducing costs to keep up with the ever-expanding demands of providing robust inspection for new infrastructure as well as ongoing inspections for currently operating facilities, and the increasing rise in the need for extensions in the planned life of existing plants.
Currently, setting up an automated phased array ultrasonic inspection requires significant manpower, especially on components with complex geometry, this often exposes operators to hazardous environments. This is a particular problem with conventional ultrasonic NDT where operators must regularly exchange probes (an ‘intervention’). Furthermore, inspections are often carried out during planned outages, and the necessary installation time of rigging can represent a significant part of the inspection cost.
To alleviate these challenges, several specialised robotic systems have been developed in industry for performing NDE in areas with well-defined geometries. However, these systems are often limited by a high degree of manual intervention, a lack of general-purpose design, and unsophisticated brute-force data acquisition with little to no data interpretation.
The development of next generation, automated NDE solutions present considerable improvements to the current state of design such as reduced inspection time, greater separation of data capture and analysis, data localization – data are intrinsically encoded with the position they were captured. These benefits lead to a reduction in plant downtime & operator dosage.
The platform presented will achieve these improvements through a set of universal automated deployment tools, implemented through hardware and software advances. By creating a platform consisting of a motorised magnetic base paired with a miniature robotic arm, a very capable and adaptable system is formed. This allows for different sensing modalities with an initial focus on phased array ultrasonics to be delivered accurately and repeatably to the target inspection site. Furthermore, by introducing additional perceptual sensors such as cameras, laser scanners, & a force-torque sensor the system can understand the environment in which it is operating. Through these sensors the user may guide the robot through the plant remotely in a safe and controlled manner. In addition to this these sensors may be used to generate scan paths of critical areas with unknown geometry on the fly as well as adapt the path in a conformable manner.
This paper presents an update on the progress of developing a crawler-based automated non-contact ultrasonic inspection system for the evaluation of large structural assets. The system presented is a significant improvement on current robotic NDT crawlers and aims to greatly reduce the time of inspection by creating an internal feature map of the subject in a Simultaneous Localisation And Mapping (SLAM) style method instead of using a lawnmower scanning style where all areas are scanned regardless if they contain features or are featureless. This map will be generated through rapid automated path planning and scanning and will show the location of potential areas of interest, where then, the appropriate method of inspection can be used for a high detailed evaluation. Current and ongoing work presented is as follows; the use of guided waves as the sensory input of an occupancy grid map; evaluating guided wave modes to find the mode most appropriate for this system; minimum thickness estimation using machine learning; improving the transducer setup using a unidirectional transmitter.
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