• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.393-396
• /
• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.11 no.2
• /
• pp.1-5
• /
• 2015

A failure or degradation of reactor upper head penetration is a troublesome problem at Nuclear Power Plants. A flaw in the reactor upper head penetration can result in unplanned plant shutdown for repair, and cause serious economic losses on the plants. Consequently, a detection of flaws is a matter of more importance. Until now, only the base metal, not including J-groove weld, in reactor upper head penetration has been inspected in accordance with 10 CFR 50.55a and ASME code case N-729-1 requirements. Accordingly, it is rather difficult to detect manufacturing defects and repair defects in J-groove weld. This paper presents a case study on the application of Time of Flight Diffraction UT technique to examine the J-groove weld in reactor head penetration using reactor head penetration mockup with artificial flaws. We expect that this study result will offer a way to understand the non-destructive examination technology for J-groove weld in reactor upper head penetration.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.6 no.1
• /
• pp.29-36
• /
• 2010

Ultrasonic inspection of heavy walled cast austenitic stainless steel(CASS)welds is very difficult due to complex and coarse grained structure of CASS material. The large size of anisotropic grain strongly affects the propagation of ultrasound by severe attenuation, change in velocity, and scattering of ultrasonic energy. therefore, the signal patterns originated from flaws can be difficult to distinguish from scattered signals. To improve detection and sizing capability of ID connected defect for heavy walled CASS piping welds, the low frequency segmented TRL Pulse Echo and Phased Array probe has been developed. The experimental studies have been performed using CASS pipe mock-up block containing artificial reflectors(ID connected EDM notch). The automatic pulse echo and phase array technique is applied the detection and the length sizing of the ID connected artificial reflectors and the results for detection and sizing has been compared respectively. The goal of this study is to assess a newly developed ultrasonic probe to improve the detection ability and the sizing of the crack in coarse-grained CASS components.

• International Journal of Computer Science & Network Security
• /
• v.23 no.11
• /
• pp.149-161
• /
• 2023

Internet of Things (IoT) is a relatively new concept that has gained immense popularity in a short period of time due to its wide applicability in making human life more convenient and automated. As an illustration: the development of smart homes, smart cities, etc. However, it is also accompanied by a substantial number of risks and flaws. IoT makes use of low-powered devices, so secure, less time-consuming and energy-intensive transmission (routing) of messages due to the limited availability of energy is one of the many and most significant concerns for IoT developers. The following paper presents a trust-based routing scenario for the Internet of Things (IoT) that exploits the past transmission record from the cupcarbon simulator's log files. Artificial Neural Network is used to quantify knowledge of trust, calculate the value of trust, and share this information with other network devices. As a human behavioural pattern, trust provides a superior method for making routing decisions. If there is a tie in the trust values and no other path is available, the remaining battery power is used to break the tie and make a forwarding decision; this is also seen as a more efficient use of the available resources. The proposed algorithm is observed to have superior energy consumption and routing decisions compared to conventional routing algorithms, and it improves the communication pattern.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.4
• /
• pp.161-166
• /
• 2021

Errors in the semiconductor process are generated by a change in the state of the equipment, and errors usually arise when the state of the equipment changes or when parts that make up the equipment have flaws. In this investigation, we anticipated that aging of the mass flow controller in the plasma enhanced chemical vapor deposition SiO2 thin film deposition method caused a minute flow rate shift. In seven cases, fourier transformation infrared film quality analysis of the deposited thin film was used to characterize normal and pathological processes. The plasma condition was monitored using optical emission spectrometry data as the flow rate changed during the procedure. Preprocessing was used to apply the collected OES data to the artificial immune system algorithm, which was then used to process diagnosis. Through comparisons between datasets, the learning algorithm compared classification accuracy and improved the method. It has been confirmed that data characterized as a normal process and abnormal processes with differing flow rates may be discriminated by themselves using the artificial immune system data mining method.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.9 no.1
• /
• pp.22-29
• /
• 1989

The important point of MPI is the analysis of leakage field in the defective regions. The analysis of leakage field depends on many factors such like geometry and character of defect. In general the calculation of magnetic leakage fields arising from such defects presents an extremely complicated mathematical problem and is practically insoluable, since the inhomogeneities have complex geometrical shapes and may differ in physical nature. Therefore, this paper describes Hall probe measurements of residual leakage field around artificial flaws in alloy steel bar, and shows how the results to recent developments in 2D dipole and analytic models of the magnetic field defect interaction.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.7 no.2
• /
• pp.21-25
• /
• 2011

Although many defects in PZR heater sleeve have been reported continually from operating experiences in oversea nuclear power plant, utilities get into difficulties in finding appropriate methods for diagnostics of the components due to the limited access or high radiation problems. Recently, as an alternative, diagnostics using Guided Wave Testing(GWT) are proposed and the attention of the methods has been growing gradually because of their long range inspection capability. This study is to investigate the effectiveness of GWT to detect PWSCC in welding points of PZR heater sleeve. Moreover, mode sensitivity analysis of GWT and optimal frequency for the diagnostics of PWSCC are presented by testing the mock-ups specimens that contain artificial flaws.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.6 no.1
• /
• pp.27-33
• /
• 1997

A neural network approach has been developed to determine the depth of a surface breaking crack in a steel plate from ultrasonic backscattering data. The network is trained by the use of feedforward three-layered network together with a back-scattering algorithm for error correction. The signal used for crack insonification is a mode converted 70$^{\circ}$transverse wave. A numerical analysis of back scattered field is carried out based on elastic wave theory, by the use of the boundary element method. The numerical data are calibrated by comparison with experimental data. The numerical analysis provides synthetic data for the training of the network. The training data have been calculated for cracks with specified increments of the crack depth. The performance of the network has been tested on other synthetic data and experimental data which are different from the training data.

• Journal of Welding and Joining
• /
• v.33 no.4
• /
• pp.63-67
• /
• 2015

Non-destructive techniques are used widely in the metal industry in order to control the quality of materials. Eddy current testing(ECT) is one of the most extensively used non-destructive techniques for inspecting electrically conductive materials at very high speeds that does not require any contact between the test piece and the sensor. The New ECT sensor which can detect inner defects was developed regardless the condition of surface. This sensor is verified to do experiment which measure the loss of induced electromotive force. The loss of induced electromotive force was measured in 5.4% and this low frequency ECT device can detect internal defects at depth 20 mm.

• Korean Journal of Materials Research
• /
• v.12 no.8
• /
• pp.682-687
• /
• 2002

The three-dimensional estimation on the depth and height of flaw by using the difference of radiographic contrast density was studied. First, the specimens having artificial flaws of various depths and heights were prepared and the radiographic testing was performed. The radiographic depth of flaw was investigated and estimated on the effect of the scattered radiation with the change of distance between flaw and film. The height of flaw was estimated from the radiographic test with the reference specimen. The radiographic contrast with flaw depth decreased with increasing the flaw depth. The scattered radiation increased with increasing flaw depth and varied with the location between flaw and film. However, in the case of flaw height, the contrast density increased with increasing flaw height. It is thought due to the change in volume generating the scattered radiation which reaches a film.