Advanced techniques in ultrasonic nondestructive evaluation

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Critical engineering components must be carefully inspected to minimize the danger of a catastrophic failure. This is particularly important in fields where a failure could lead to major financial loss, environmental damage, or personal injuries, e.g., industries such as aviation, nuclear power generation, oil s surface. This research program is focused on the development of new types of ultrasonic sensors, and mathematical algorithms to process the ultrasonic echo signals that yield flaw images. The final objective is then to obtain a much sharper, clearer “map” of the size, shape, and type of flaw(s) in an engineering component such that an accurate assessment can be made of its potential for causing a component failure. The sensor development component of this work is targeted at producing ultrasonic transducers that can operate for extended periods in harsh environments, in particular high temperature or elevated gamma radiation fields. One major application of such sensors would be for their permanent installation on any components in a petrochemical or electrical power generation plant that might be prone to corrosion or crack initiation. The probes could continually monitor the integrity of these key plant components at temperatures up to 700 C while the plant is in operation, and periodically send the information back to a centralized computer system for analysis and storage. Plant safety would be enhanced, and unexpected plant failures would be reduced. The improved probe hardware is to be complemented by development of advanced signal processing algorithms that can “sharpen” a blurry image of a flaw, or separate two blurry echoes originating from a pair of closely-spaced sub-surface flaws. There is a wealth of potential applications for such signal enhancement strategies, e.g., geophysics, telecommunications, astronomy, obstetrics, neurology, and micro-robotics. Some of the proposed techniques combine information contained in multiple types of signals with knowledge about the expected general form of a flaw echo, in a “data fusion” scheme. Combining all the key factors enables a more accurate estimate of a few key flaw parameters, such as flaw size or shape. The direct beneficiaries of this work will be Canadian industry, which will be able to reduce the number of unexpected failures during plant operations. This will help protect the environment, reduce injuries, and keep production costs low.