Ultrasonic signal processing techniques for Pipeline: A review

Naqiuddin, M. S. M; Leong, M. Salman; Hee, Lim Meng; Azrieasrie, M. A. M.

doi:10.1051/matecconf/201925506006

Cited by 10 publications

(6 citation statements)

References 62 publications

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“…In order to identify the defect from the ultrasonic echo signal, there are some methods should be used to process ultrasonic signals. There are many existing methods of ultrasonic body wave and guided wave signal processing [ 13 , 14 ], such as split spectrum processing (SSP) [ 15 , 16 ], wavelet transform [ 17 , 18 ], Hilbert–Huang transform [ 19 ] and S-transform [ 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic Technique and Signal Correlation Algorithm

Cao

Jiang

et al. 2020

Materials

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This paper presents a method based on signal correlation to detect delamination defects of widely used carbon fiber reinforced plastic with high precision and a convenient process. The objective of it consists in distinguishing defect and non-defect signals and presenting the depth and size of defects by image. A necessary reference signal is generated from the non-defect area by using autocorrelation theory firstly. Through the correlation calculation results, the defect signal and non-defect signal are distinguished by using Euclidean distance. In order to get more accurate time-of-flight, cubic spline interpolation is introduced. In practical automatic ultrasonic A-scan signal processing, signal correlation provide a new way to avoid problems such as signal peak tracking and complex gate setting. Finally, the detection results of a carbon fiber laminate with artificial delamination through ultrasonic phased array C-scan acquired from Olympus OmniScan MX2 and this proposed algorithm are compared, which showing that this proposed algorithm performs well in defect shape presentation and location calculation. The experiment shows that the defect size error is less than 4%, the depth error less than 3%. Compared with ultrasonic C-scan method, this proposed method needs less inspector’s prior-knowledge, which can lead to advantages in automatic ultrasonic testing.

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Section: Introductionmentioning

confidence: 99%

High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic Technique and Signal Correlation Algorithm

Cao

Jiang

et al. 2020

Materials

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“…Recently, the development of NDT automation with high reliability has emerged as an active research area [58] because of the needs of avoiding the dependence on the skills and experience of the operators [57]. Therefore, signal processing with intelligent classifier can provide reliable and fast inspection [59] which could increase the sensibility of defect detection and automate the monitoring procedure [60]. The nonlinearity of inspection data is another reason to use AI due to its capability to solve the complexity of the acquired data by nonlinear classification [61].…”

Section: Artificial Intelligence Applications In Conventional Ndtmentioning

confidence: 99%

“…The false pixel classification is due to the absence of signal processing to eliminate the diffraction noise. Therefore, the integration between signal processing and AI model has been proven to provide reliable inspection as well as better resolution [59]. However, this technique is limited to evaluate only the defect location and size, while the defect depth cannot be estimated which is important to estimate the damage level.…”

Section: Artificial Intelligence Applications In Microwave Ndtmentioning

confidence: 99%

Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

2019

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The development in materials technology has produced stronger, lighter, stiffer, and more durable electrically insulating composites which are replacing metals in many applications. These composites require alternative inspection techniques because the conventional nondestructive testing (NDT) techniques such as thermography, eddy currents, ultrasonic, X-ray and magnetic particles have limitations of inspecting them. Microwave NDT technique employing open-ended rectangular waveguides (OERW) has emerged as a promising approach to detect the defects in both metal and composite materials. Despite its promising results over conventional NDT techniques, OERW microwave NDT technique has shown numerous limitations in terms of poor spatial resolution due to the stand-off distance variations, inspection area irregularities and quantitative estimation in imaging the size of defects. Microwave NDT employing OERW in conjunction with robust artificial intelligence approaches have tremendous potential and viability for evaluating composite structures for the purpose mentioned here. Artificial intelligence techniques with signal processing techniques are highly possible to enhance the efficiency and resolution of microwave NDT technique because the impact of artificial intelligence approaches is proven in various conventional NDT techniques. This paper provides a comprehensive review of NDT techniques as well as the prospect of using artificial intelligence approaches in microwave NDT technique with regards to other conventional NDT techniques. INDEX TERMS Microwave nondestructive testing, open-ended rectangular waveguides, artificial intelligence.

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“…The detection and characterization of surface steel defects such as corrosion defects, cracking, etc., as well as locating them identifying and determining their size and type is the phase to consider in order to define the maintenance methods. According to studies [14][15][16][17][18][19][20][21][22][23][24][25][26], steel surface defects have been detected and determined using non-destructive methods such as ultrasonic methods, which provide very precise real-time information on the position and size of the detected defect [14]. It can be used in line using the ultrasonic intelligent tool as an autonomous machine containing several ultrasonic probes to check the hydrocarbon transport pipeline [15].…”

Section: Introductionmentioning

confidence: 99%

Corrosion of API 5L X60 Pipeline Steel in Soil and Surface Defects Detection by Ultrasonic Analysis

Benkhedda,

Bensaid,

Benmoussat

et al. 2024

Metals

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The corrosion steels phenomenon is one of the main problems in the oil industry, such as in buried transmission pipelines used for high gas pressure for long distances. Steels are protected from the external soil corrosion through a bituminous coating, whose action is coupled with a cathodic protection system, which aims to maintain steel in its protection field and thus to avoid any corrosion risk. However, steels in service may experience external surface defects like corrosion pitting and cracking due to electrochemical or mechanical interactions of bare steel with an aggressive soil solution after steel protection failure. These are concerning phenomena and are the major threats of the pipeline transmission system’s reliability and ecological safety. Corrosion mechanisms are varied and can be evaluated by different methods, such as electrochemical measurements, which are influenced by various factors like temperature, pH, soil characteristics, resistivity, water content, and as well mechanical stresses. Corrosion results from simulated artificial soil solutions showed that steel is sensitive to corrosion by soil. Surface defects detection was carried out using an ultrasonic non-destructive method such as C-Scan Emission testing and the time of flight diffraction technique (TOFD) ultrasonic non-contact testing method. After propagation of the ultrasonic waves, the diffracted ultrasonic reflected wave occurring at the edges of the defects appears due to the presence of a corrosion defect by generating defect echoes. The C-Scan ultrasonic image shows surface reflection, including corrosion defects on interfaces with varying acoustic impedances. The cross-transverse speed ultrasonic propagation through the plate including defect is modified, revealing more surface defects, and cross-transverse speed is shown to increase ultrasonic detection presents some advantages, such as precision and speed of detection without alteration to the structure. This method can be used in the industrial context as an intelligent industrial robotics technique.

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Ultrasonic signal processing techniques for Pipeline: A review

Cited by 10 publications

References 62 publications

High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic Technique and Signal Correlation Algorithm

High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic Technique and Signal Correlation Algorithm

Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

Corrosion of API 5L X60 Pipeline Steel in Soil and Surface Defects Detection by Ultrasonic Analysis

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