Papers by Keyword: Magnetic Flux Leakage (MFL)

Abstract: Dealing with the relationship properly between the sensor scanning and signal acquisition is the base of hi-speed and hi-precision MFL (magnetic flux leakage) testing for steel pipe. Firstly, the MFL wave form characteristic was established using magnetic dipole theory. Further, on that basis, the relationship between signal frequency and sensor scanning was analyzed. Finally, sample frequency was designed according to the requirement of the automatic steel pipe MFL testing. Additionally, the MFL signal acquisition experiment was conducted to verify the influence of the signal sampling frequency. The signal acquisition analysis was of great significant to perform the MFL testing for steel pipe in hi-speed and hi-precision.

Abstract: Embedded CPU in traditional magnetic flux leakage detection system was used as the master controller. CPU is serial processor, which making it difficult to collect the large amounts of real-time data. While FPGA has the advantages of high integration, high speed processing, parallel processing. FPGA is applied to magnetic flux leakage acquisition system to solve data acquisition problem. It comes up with the designs of a multi-channel magnetic flux leakage signal selection control module, A/D conversion module and communication module in VHDL language on QuartusII. The experimental results show that each module of the magnetic flux leakage acquisition system based on FPGA can meet the requirements, and can correctly collect magnetic flux leakage signal, convert and transmit data. Design of FPGA-based is programmable in the field, magnetic flux leakage collection system can be flexibly designed for different occasions, and has independent intellectual property rights.

Abstract: In this study, a MFL (Magnetic Flux Leakage) based 3D inspection system which is incorporated into a cable climbing robot was investigated to monitor the healthy condition of steel cables. Firstly, a MFL sensor head prototype composed of two permanent magnets and eight hall sensors was designed and fabricated. A steel cable specimen with several types of damage, such as corrosion and cutting, was inflicted and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. The measured MFL signals were used to interpret the healthy condition of the steel cable. For improving the resolution and quantification of the damage level, digital signal processing techniques were performed. In addition, the measured MFL signals were visualized into a 3D MFL map for real-time and online cable monitoring. This visualized MFL map can provide the information about location, shape and size of damages very intuitively. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the MFL based cable inspection system.

Abstract: In this paper, a new method on quantitative analysis of magnetic flux leakage signal by ant colony neural network is proposed. Firstly, the parameters of the magnetic flux leakage signal which can reflect the various characteristics of cracked defects are determined by finite element method (FEM) simulation. Secondly, based on the study of the ant colony algorithm, the neural network model is established for the magnetic flux leakage signals processing. Finally, in the simulated working environment, the performance of the neural network is tested with the different signal features as input. The experimental results proved the feasibility of the ant colony neural network, verified the increases of the convergence rate and the accuracy of the neural network, and improved the efficiency as well as the quality of the quantitative analysis for the magnetic flux leakage signals.

Abstract: In this study, an automated cable monitoring system using a NDE technique and a cable climbing robot is proposed. MFL (Magnetic Flux Leakage- based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the measured magnetic flux signal was visualized into a 3D MFL map for convenient cable monitoring. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

Abstract: Based on the magnetic theory, the paper reviewed the factors of affecting the distribution of magnetic flux leakage (MFL) on the ferromagnetic material and analyzed the wire rope defects characters from MFL signal. A non-destructive testing (NDT) instrument of steel wire rope using magnetic flux leakage was presented in this paper. By using permanent magnets to magnetize wire rope and using Hall element arrays to test MFL, Intelligent signal processing was applied for effective discrimination of wire rope’s flaws. The experiment results show the degree and the width of defects, the annular distribution of localized flaws such as concentrated or dispersive broken wires can be well distinguished. The instrument can be used conveniently with good resolution and repeatability and can meet the requirement of real time.

Abstract: The new Electromagnetic Imaging Tool (EMIT) is introduced in this study. It is also described that the basic inspection theory, system structure and applications. The EMIT can determine whether metal loss or casing damage has occurred internally or externally. A 3D casing image can be supplied, including horizontal, vertical profile. The experimental results show that the EMIT has a “high-resolution” for MFL method in the casing well because of the steel brush structure. The minimal diameter of the inspection hole is 4 mm, and the thickness determination error of casing wall is 0.4 mm. A number of examples from oilfield are presented.

Abstract: The purpose of this paper is to present the results of observation of material degradation process in steel samples under combined conditions of static and cyclic dynamic loading, using selected electromagnetic NDT methods. To evaluate damages a Barkhausen noise observation, an AC magnetization, a magnetic flux leakage and eddy current method were used.

Abstract: The magnetic flux leakage (MFL) technique is widely used as a Non-Destructive Testing (NDT) method for welds [1]. Because of the specialty of fillet weld structure, the defect may not be in the location suitably detected, which is normally at the center of yoke poles, and the rate of detect-ability would decline. In this paper, we focus on the yoke-magnetization testing for a fillet weld, and it is studied the influences of air gap between magnetic poles and specimen surface on MFL density at an artificial flaw by Finite Element Method (FEM), and also the influences of distance between magnetic poles and fillet weld on MFL density. The results show that the MFL density observably decreases as the air gap and the distance increase.

Abstract: During bars manufacturing and using process, the use of bars with cracks influenced the service life and sustainable work, on the premise of certain detection system, the choose of signal de-noising method plays an important part in magnetic flux leakage testing process, for which determining the global performance of testing equipment. This paper studies on magnetic flux leakage signals characteristic of cracks on the bar, analyzed the advantages and disadvantages of wavelet analysis and wavelet packet threshold de-noising, and on this basis, in order to give consideration to both the low and high frequency interference signal removing, adopted an integration method that combines wavelet packet threshold de-noising, wavelet packet decomposition and wavelet reconstruction, which greatly improved signal processing results.