<p>This paper presents a review of state-of-art in the Magnetic Flux Leakage (MFL) sensor technology, which plays an important role in Nondestructive Testing (NDT) to detect crack and corrosion in ferromagnetic material. The demand of more reliable MFL tools and signal acquisition increase as it has a direct impact on structure integrity and can lead to be major catastrophic upon questionable signal analysis. This is because the size, cost, efficiency, and reliability of the extensive MFL system for NDT applications primarily depend on signal acquisition as a qualitative measure in producing a trustworthy analysis. Therefore, the selection of appropriate tools and methodology plays a major role in determining the comprehensive performance of the system. This paper also reviews an Artificial Neural Network (ANN) and Finite Element Method (FEM) in developing an optimum permeability standard on the test piece. </p>
This paper presents a comprehensive review of the development of magnetic flux leakage (MFL) applied by the researcher to improve existing methodology and evaluation techniques in MFL sensor development for corrosion detection in Above Storage Tanks (ASTs). MFL plays an important role in Non-Destructive (NDT) testing to detect crack and corrosion in ferromagnetic material. The demand for more reliable MFL tools and signal acquisition increase as it has a direct impact on structure integrity and can lead to major catastrophic upon questionable signal analysis. The accuracy of the MFL signal is crucial in validating the proposed method used in MFL sensor development. This is because the size, cost, efficiency, and reliability of the overall MFL system for NDT applications primarily depend on signal acquisition as a qualitative measure in producing a reliable analysis. Therefore, the selection of appropriate tools and methodology plays a major role in determining the overall performance of the system. This paper also discusses the advantages and disadvantages of major types of MFL sensors used in NDT based on the working principle and sensitivity on the abrupt signal acquisition. The application of the Artificial Neural Network (ANN) and Finite Element Method (FEM) also discussed to identify the impact on the credibility of the MFL signal.
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