# Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method
###### Abstract  
Ferromagnetic pipes are widely used for fluid transportation in various industries. The failure of these ferromagnetic pipes due to surface defects can generate industrial accidents, economic losses, and environmental pollution. Non-destructive testing techniques are required to detect these surface defects. An alternative is the metal magnetic memory (MMM) method, which can be employed to detect surface flaws in ferromagnetic structures. Based on this method, we present an analysis of experimental results of the magnetic field variations around five different surface semi-elliptical defects of an ASTM A36 steel pipe. A measurement system of MMM signals is implemented with a rotatory mechanism, a magnetoresistive sensor, a data processing unit, and a control digital unit. The MMM method does not require expensive equipment or special treatment of the ferromagnetic structures. In order to research a potential relationship between the defect sample size and the measured MMM signals, variable defect dimensions are experimentally considered. According to these results, the shape and magnitude of the normal and tangential MMM signals are altered by the superficial semi-elliptical defects. In particular, the maximum and mean tangential components and the maximum and minimum normal components are related to the defect dimensions. The proposed measurement system can be used to study the behavior of magnetic field variations around surface defects of ferromagnetic pipes. This system can be adapted to measure the position and damage level of small defects on the surface of ferromagnetic pipes[PERSON]  
ferromagnetic structure; surface magnetic defects; magnetic field sensor; metal magnetic memory method; non-destructive testing; magnetic field variation; semi-elliptic defect +
Footnote †: journal: Applied  
**Citation:** [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method  
**Citation:** [PERSON] [PERSON]; [PERSON]. For instance, the US has approximately 170,000 miles of hazardous liquid pipelines [1]. According to current regulations, hazardous liquids include petroleum, petroleum products, and anhydrous ammonia. About 66% of domestic petroleum moves through these pipelines [2]. The types of costs due to accidents involving US hazardous liquid pipeline infrastructure include the following: (i) the value of the product lost; (ii) public, private, and operator property damage; and (iii) cleanup, recovery, and other costs [3]. Damage detection in steel pipes is an essential challenge for non-destructive testing (NDT). Different NDT techniques have been employed for damage monitoring on ferromagnetic pipes, including liquid penetrant tests [4], ultrasonic tests [5], dynamic permeability testing [6], corrosion monitoring techniques [7], visual inspection and assessment techniques [8], eddy current testing [9], magnetic flux leakage testing [10], and X-ray inspection [11]. Defects in ferromagnetic pipes can be detected using liquid-penetrant testing based on the accumulation of a liquid around the defect on the sample surface. However, this NDT technique requires smooth and contaminant-free surfaces [12]. In ultrasonic testing, small defects in ferromagnetic pipes can be detected using ultrasonic pulses. Nonetheless, ultrasonic testing requires highly trained and experienced operators [13; 14; 15]. On the other hand, visual inspection NDT techniques can be employed to monitor pipe surface flaws [16; 17]. Nevertheless, visual inspection is suitable for detecting relatively large ferromagnetic defects. In another NDT technique, the ferromagnetic pipe cracks can be detected using small magnetic particles through a dry or wet suspension of iron filings. However, this NDT technique has a low sensitivity of the inspection of cracks parallel to the applied magnetic field [18; 19].