Non-Contact Real-time Nondestructive Evaluation Technology for NDE 4.0

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Nondestructive evaluation (NDE) is crucial for various manufacturing sectors, but its current practices require human operators to be involved in all aspects of data collection, transfer and analysis, causing many issues on safety, speed and accuracy. With the advent of Industry 4.0, NDE technology needs to be upgraded to “NDE 4.0” comprising essential aspects such as automatic and autonomous NDE, interconnectivity for data communication, and real-time data analytics using AI, which cannot be achieved with current technology. In this program, we will advance a new hybrid NDE approach that can address these aspects to realize NDE 4.0. Currently various NDE methods are used, including X-ray, electromagnetic, ultrasound, acoustic emission, thermography and laser ultrasonics; however, all have critical limitations. The greatest limitation is human involvement; all the methods rely on inspectors to conduct the inspection and interpret the data; thus they are slow, cannot be applied to hazardous environment and the results are subjective and vulnerable to human errors. In this program, we will develop a new hybrid AI-based NDE method that can perform non-contact, in-line, remote and automatic inspections, with real-time data interpretation capability using embedded AI. This program consists of three inter-related objectives: 1) to develop a phased-laser ultrasonic technology that can focus and steer the ultrasound waves to the region of interest with a high signal strength. This can achieve a non-contact and couplant-free NDE, enabling remote and automatic NDE suitable for hazardous environments and geometrically complex components. 2) to develop a noble graphene-based ultrasonic receiver to receive the reflected ultrasonic waves. Utilizing the ultra-low mass and high mechanical strength of graphene, we will develop a wideband receiver that is much smaller and more sensitive than existing ultrasonic receivers. 3) to develop a FPGA-based NDE controller that controls the NDE process, interprets the data using AI algorithm, and communicates with the cloud server in real-time. Owing to its fast computation speed and powerful parallelism capability, a FPGA-based controller is able to achieve real-time data analytics using AI. Each objective is cutting-edge and innovative, while the achievement of all objectives as a whole will develop the novel NDE technology, that can be immediately applicable to the in-line, automatic and safe NDE, which would lead technological development for the progression toward and through the Industry 4.0. The proposed research will give Canada a competitive edge in the study of NDE, structural health monitoring and the integration of NDE with real-time AI. This integration will enable a higher level of NDE technology, allowing Canadian industry to gain momentum in emerging NDT service and equipment markets, while ensuring the safety of the products, structures, and infrastructure.