Fumio Kojima

Identification of crack profiles using genetic programming and fuzzy inference

Abstract This paper deals with a quantitative nondestructive evaluation in eddy current testing for steam generator tubes of nuclear power plants by using genetic programming (GP) and fuzzy inference system. Defects can be detected as a probe impedance trajectory by scanning a pancake type probe coil. An inference system is proposed for identifying the defect shape inside and/or outside tubes. GP is applied to extract and select effective features from a probe impedance trajectory. Using the extracted features, a fuzzy inference system detects presence, position, and size of a defect of test sample. The effectiveness of the proposed method is demonstrated through computer simulation studies.

Boundary shape identification in two-dimensional electrostatic problems using SQUIDs

Abstract - This paper is concerned with a quantitative nondestructive evaluation of conductors using superconducting quantum interference devices (SQUIDs). A measurement system is described for an electrical potential problem with an unknown boundary. Domain identification is discussed within the theoretical framework of parameter estimation problem for the electrostatic field analysis. Applying the method of mappings to the problem considered here, we present computational methods, including theoretical convergence results for the associated finite dimensional problem identification techniques.

Detection of internal cracks and delamination in carbon-fiber-reinforced plastics using SQUID-NDI system

Recently, thick boards of carbon-fiber-reinforced plastic (CFRP) are often used in space crafts and space structures. Nondestructive inspection (NDI) using superconducting quantum interference device (SQUID) is a prospective NDI method for the thick CFRP materials. To estimate the potential of SQUID-NDI for detection of deep-lying defects in CFRP, the skin effect must be clarified. So we applied a SQUID-NDI method to hidden slots and delaminations at various depths in thick CFRP boards to obtain the dependence of the peak amplitude of the magnetic response to the defects on the defect depth. Magnetic field response due to slots of up to 15 mm depth was detected. The response peak amplitude exponentially reduced as the depth increased. We estimated the depth dependence by a simple calculation assuming the same skin effect in CFRP as in metals. The estimated dependence differs a little from the experimental one. The difference suggests that a more accurate calculation is necessary.

Information transformation by virus-evolutionary genetic programming

This paper deals with genetic programming (GP) for information translation. The GP can generate a structured computer program, but it is difficult to define recursive functions automatically. Therefore, we propose a virus-evolutionary genetic programming (VE-GP) composed of two populations; host and virus. Here, a virus plays the role of an automatically defined function. First, the VE-GP is applied to a function approximation problem, and the simulation result shows that the VE-GP can generate a function to approximate the given function with small errors. Next, the VE-GP is applied to the information transformation for a classification task, and the simulation result shows that the VE-GP can generate a function to classify a given data set.

Development of an NDE method using SQUIDs for the reconstruction of defect shapes

The widespread use of the SQUID-NDE requires the visualization of defects. We have developed a method to obtain depth information by monitoring the SQUID output while changing the frequency of the current flowing in a sample. The effectiveness of this method was verified by experiment and simulation.

Defect profiles identification of conducting materials using HTS-SQUID gradiometer with multiple frequencies

This paper is concerned with a quantitative nondestructive evaluation of conducting materials using high temperature superconducting quantum interference devices (HTS-SQUIDs). A mathematical model of the nondestructive evaluation system is described by a three dimensional eddy current model. The forward analyses using the finite element model are implemented for conducting materials with a depth-varying crack. A computational method based on the genetic algorithm is proposed for recovering internal defect profiles with HTS-SQUID data.

Detection and characterization of flaws in CFRP by SQUID gradiometer using evolutionary computation

This paper is concerned with a quantitative nondestructive evaluation of a carbon fiberglass reinforced plastic (CFRP) using the low temperature superconductor (LTS) SQUID gradiometer. The evaluation can be implemented by applying the alternative current injection to the CFRP with a defect. A 3D finite element code is developed for analyzing the SQUID based nondestructive system. Using the evolutionary programming, an efficient inverse scheme is proposed for recovering flaws in CFRP. The proposed algorithm is tested for the detection and characterization of flaws in the CFRP samples.

Quantitative nondestructive evaluation of material defect using GP-based fuzzy inference system

This paper deals with a quantitative nondestructive evaluation in eddy current testing for steam generator tubes of nuclear power plants by using genetic programming (GP) and fuzzy inference system. Defects can be detected as a probe impedance trajectory by scanning a pancake type probe coil. An inference system is proposed for identifying the defect shape inside and/or outside tubes. GP is applied to extract and select effective features from a probe impedance trajectory. Using the extracted features a fuzzy inference system detects presence, position, and size of a defect of a test sample. The effectiveness of the proposed method is demonstrated through computer simulation studies.

Fast recovering algorithm for crack shape of steam generator tubes using geometric approach

Publisher Summary The demand for quantitative nondestructive evaluation (QNDE) of nuclear power plants has grown. The detection of a crack on steam generator tubes is a critical issue for the structural integrity of the plants. In QNDE, the objective is not only to find out flaws but also to determine the size, shape, and orientation of the flaw. Eddy current testing (ECT) is used for inservice inspection of tubes in steam generators because of high detectability and rapid scanning process. This chapter is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear power plants. The crack shape is detected as voltage trajectories by scanning a transmitter-receiver pancake type probe coil. First, a mathematical model of the inspection process is derived from the Maxwells equations. Second, the input and output relation is given by the approximate model by means of the finite element method. Numerical experiments for characterizing outer crack of tubes are also demonstrated. Finally, the chapter proposes a parameter estimation technique for recovering the crack shape using data from the probe coil.

- Defect shape recovering for electromagnetic problem using HTS-SQUID gradiometer

Publisher Summary Quantitative nondestructive evaluation is a critical issue for the structural integrity of material system used in airplanes and aerospace planes. Various types of alternative evaluation methods are developed, including ultrasound analyses, thermal tomographies, and electrical impedance techniques. These methods involve an attempt to characterize structural defects, which may not be detectable by visual inspection. Although those methods are well-known practical techniques, there exists a growing interest of developing the new and improved methods for evaluating the more accurate defect profiles of material systems. SQUIDs have the potential to detect material defects in conductors due to their extremely high magnetic flux sensitivity for magnetic fields. A mathematical model of the nondestructive evaluation system is described by electromagnetic potential problems. The forward analyses using finite element model are implemented for the conductor with a crack. A computational method using a genetic algorithm is proposed for recovering internal defect profiles with HTS-SQUID data.