In this research, we used nondestructive test based on ultrasonic test as inspection method, and made up inspection robot in order to control of ultrasonic probe on the SWP surface, and programmed to signal processing code and pattern classifying code by user made programming code. For evaluation of flaw signal is reflected on welding flaw, user-made program codes are composed of signal processing and probability neural network (PNN) and backpropagation neural network (BPNN). And then, we actually confirmed to the theoretical advantage of each neural network method compared probability neural network with backpropagation neural network for classification and recognition rate. For the application of classifier to SWP inspection system, BPNN classifier is adequate in the first stage. And then, the application of PNN classifier is adequate as the next stage. Because of PNN application need enough sample data that is due to probabilistic density function.
In the present study, a Nd;YAG Laser (pulse type) was used to emit ultrasonic signals to a test material. In addition, a total ultrasonic investigation system was designed by adopting a Fabry-Perot interferometer, which receives ultrasonic signals without any contact. For non-destructive test SM45C, which contains some flaws was used as a test material. Because it is easy to align light beam in receiver, and the length of the light beam does not change much even if convex mirror leans towards one side, confocal Fabry-Perot interferometer, which has stable frequency, and PI control are used to correct interfered and unstable signals from temperature, fluctuation and time shift of laser frequency. Stable signals are always obtained by the feedback of PI circuit signals in the confocal Fabry-Perot interferometer. The type, size and position of flaws inside the test material were examined by achieving the stabilization of an interferometer. This study presented a useful method, which could quantitatively investigate the fault of objects by using a Fabry-Perot interferometer.
Importance on the detection of corrosion-related defect is undeniable from the fact that it
can prevent significant economic loss and enhanced safety in mechanical equipments, pipes, ships,
bridges, and other applications. Conventionally researched measurement methods for defect and
thinning from corrosion are acoustic emission, EMAT using ultrasound, laser induced ultrasound, etc.
However, these non-destructive testing methods have the shortcoming of accessibility to on-site. For
instance, EMAT should be close to several millimeters to generate magnetic field in structure. For
laser application, it can be applied to remote non-destructive testing, but some defect might not be
possible to be detected by the surface condition of structure. In this study, infrared thermography
camera is utilized to determine the degree of corrosion on paint-coated metal. In addition,
fundamental researches to develop corrosion detection system for on-site metallic structure are
conducted to provide the applicability of IR camera and possibility of thermal analysis method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.