Fusion of multiprobe NDT data.

Non-destructive testing techniques (NDT) are commonly used by industry to check for faults, flaws and structural integrity of a component. Early detection and characterisation of defects can improve manufacturing quality and safety. The main advantage of NDT techniques is that the component inspected remains intact after examination. However, each NDT technique can only provide limited information about a defect, therefore the use of more than one inspection technique is required for its full characterisation. Each technique is usually applied on an individual basis and information from each NDT system is sometimes inconsistent or conflicting even between different instruments which are carrying out the same type of inspection. Therefore, the synergistic use of information from multiple instruments will provide a consensus assessment and help in decision making by providing a final output, with associated probabilities which may support or refute information from one or multiple sensors. The process used to combine information from multiple sources is called data fusion. The research work described in this thesis demonstrates that NDT data fusion can facilitate signal interpretation, defect quantification and provide a solution which may be implemented in the use of remotely operated multiple inspection techniques. Non-destructive testing data integration and fusion applied to the inspection of composite materials and to welds are described. Fusion of information from multiple similar techniques and from complimentary NDT techniques was performed which are presented in this thesis.

Grantor dc:publisher.institution

Robert Gordon University

Year dc:date.issued

1995

Author dc:creator

• Gros, Xavier E.

Advisor dc:contributor.advisor

• P. Strachan and D.W. Lowden

• Non-destructive testing
• Multi-probe
• Early detection
• Manufacturing quality
• Consensus assessment
• Data fusion
• Signal interpretation
• Defect quantification
• Composite materials
• Welds

Language dc:language

en

Identifier

oai:rgu-repository.worktribe.com:2807399
https://doi.org/10.48526/rgu-wt-2807399

OAI identifier oai:identifier

oai:rgu-repository.worktribe.com:2807399