Experimental study on the simulated defects detection in submerged transmission pipeline

doi:10.21203/rs.3.rs-1524501/v1

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Experimental study on the simulated defects detection in submerged transmission pipeline

https://doi.org/10.21203/rs.3.rs-1524501/v1

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Long-distance pipelines are commonly used to transport oil, natural gas, water, etc. However, long-term uses without maintenance cause the residue of deposits in the pipeline to gradually adhere to the inside of the pipeline by physical or chemical action, it causing the pipeline to become clogged. And it makes overpressure and leaks in the pipeline, which further impacts the safety of industry and people`s lives. The purpose of this study is to establish a non-destructive inspection to measure the defects in a pipe by ultrasonic technique. The material of the simulated pipe is SCH80 carbon steel pipe with a thickness of about 11mm as standard, and defects were designed such as holes and grooves inside and outside the pipe. The carrier mechanism design is printed by a 3D printer. A submerged ultrasonic transducer is used to evaluate the simulated pipeline and establish that data in an imaging system through LabVIEW and Origin software. Thereby, thickness and defect locations are clearly evaluated. In addition, ultrasonic detection error was calculated within 6.5%. It helps to apply this technique and equipment for underground pipeline inspections to prevent pollution.

Pipeline system

Loss of metal removal

Ultrasound

Surface analysis

In industry, pipeline transportation is an unavoidable medium for transporting energy fluids from one region to another (Reber et al. 2002; Qin et al. 2020; Durai et al. 2022; Jiang et al. 2018). Because it is an effective and efficient method of transporting the fluids in a fast manner with continuous flow over long distances. In addition, pipeline transportations have some good advantages such as cost, environmental impact, energy consumption, land consumption, etc. (Zelmati et al. 2017; Wang et al. 2021; Pluvinage et al. 2018; Hadj Meliani et al. 2017). In general, carbon steel pipes are widely used to supply fluids such as oil, gas, and water in homes and hazardous environments. It has excellent mechanical properties, such as good hardness, high strength, good resistance to wear, better fabricability, the economic, acceptable limit of corrosion, and it withstands elevated pressure conditions compared to other materials in the pipe (Zelmati et al. 2022). According to the statistics report of transportation distance of oil and natural gas pipelines in Taiwan in the year, 2018 is about 15,700 kilometers, and most of them are buried underground. Which is based on the substance they carry, it can be either buried under the ground or kept exposed to the atmosphere. So these kinds of pipelines are prone to more damage than the exposed pipe due to the prevailing environmental conditions and transferring materials (Psyrras et al. 2018 and Rahman et al 2012). It causes defects such as corrosion and siltation of the pipeline, resulting in accidental leakage in the pipeline correspondingly stopping the materials supply and environmental pollution (Rajani et al. 2004 and O’Day et al. 1986). In addition, when transporting water via a pipe, 35–60 percent of the water was wasted due to a pipeline failure (Doglione et al. 1998). And any other type of transportation like petrochemical substances and gas are extremely costly, including repair costs (Colombo et al. 2002). Therefore, if the defect was not detected early, it will cause more economic losses and pollution to the environment.

Non-destructive testing method (NDT) is a modern engineering technology that uses light, sound, electricity, magnetism, etc., to detect internal and external defects without destroying the structural materials or components (McCann et al. 2001 and Krause et al. 1997). After detection, the relevant signals, images, and parameters are collected and followed by appropriate processing such as analysis, judgment, and evaluation (Kim et al. 2102). Every specific application of the NDT method of ultrasonic technique can detect the parameters by the development of a wave generator. Thereby, ultrasonic technique has been used for a wide range of applications in the fields of machinery and civil engineering to measure the thickness and internal defects of metal blocks, which includes the thickness of concrete slabs, depth of concrete surface cracks, and inaccessible regions and so on (Watanabe et al. 2014 and Ma et al. 2022). A simple piezoelectric transducer was used in pipeline inspection gauges (PIGs) for the analysis of automatic carbon steel pipeline due to its simple structure, cost, and sensitivity (Kumar et al. 2022). Because ultrasonic waves are more attractive efficient and more sensitive than the other traditional NDT methods. Ultrasound detection methods also have some limitations related to the material, environment, location, and aqueous solution (Galvagni et al. 2011 and jia et al. 2022). In most cases, the inner tube was heavily corroded due to the chemicals it carried. During this period, external assessments are less effective than internal inspections. Therefore, in this study, a submerged ultrasonic transducer is used to analyze defect depths with proper defect reflections in the internal pipe.

The purpose of this research is to establish an ultrasonic non-destructive inspection system, measure the thickness of the pipe wall, location, and depth of the simulated defects, and perform the inspection in an appropriate manner. This pipeline data is measured with a single underwater probe by measuring the time-of-flight (TOF) of ultrasonic waves between pipe surface and transducer. Then the LabVIEW software is used to analyze the location of metal losses on the pipeline surface from the acquired signal. Finally, a full-scale 3D surface map of the pipeline will be plotted.

Experimentation

Figure 1 shows the working setup of the ultrasonic flaw detection system in this study. A six-inch carbon steel pipe was used for non-destructive inspection. This pipe is 1.5m long and 11mm thick. To evaluate the performance of the robot system, we created artificial defects on internal and external surfaces, such defects are holes and grooves. The test equipment is a submerged ultrasonic probe. The carrier device must be underwater to facilitate ultrasonic transmission. It is manufactured by 3D printing melt deposition modeling (FEM) technology using a Polylactic acid (PLA) filament material. It has excellent mechanical characteristics and reduces the total weight of the robot system compared to the metal chassis. The movement of the robot makes it freely inside the measured pipe by the arrangements of rolling wheels at end of both carrier systems. In this study, the carrier is designed a rectangular shape with a length of 160mm, a width of 40mm, and a height of 40mm. And 34mm hole was designed in the middle for the ultrasonic probe to be inserted, and 11mm is reserved for the water distance between the probe and the pipe wall. Later on, the developed defect will be measured, both internal and external environment to the pipe surface through a submerged ultrasonic probe. Once the transducer receives the signal from the reflection surfaces, the oscilloscope can collect the data. Then LABVIEW program was used to extract the results in the form of 2D and 3D images. Finally, the defects were clearly located by 3D images and waveform graphs.

Artificial Defects

The ultrasonic detection system of this study mainly evaluates carbon steel pipe for pressure piping of simulated petrochemical pipeline. The pressure grade of the selected pipe is SCH80 and the thickness is about 11mm. According to the national standard material, the corresponding pipe material is STPG370. In general, pipeline defects are complex and diverse. The internal and external pipeline defects are caused by external forces or corrosion. In order to simulate the environmental impact of long-distance underground pipelines, different sets of defects with various sizes are designed. Therefore, this research was designed with three different sets of defects, then processed for inspection. Aiming at a 6-inch carbon steel pipe with SOLIDWORKS drawing to design the pipeline defects, the diameter of the circular holes is 3mm, 6mm, 9mm, the internal groove length of the pipeline is 20mm, width is 15mm, and the depth is 1mm, 3mm, 5mm, 7mm, 9mm, the outer groove length of the pipe is 20mm, width is 15mm, and the depth is 1mm, 3mm, 5mm, 7mm, and 9mm of different depth was designed, as shown in Fig. 2.

The ultrasonic transducer will pass the signal at parts that were distorted in the pipeline by the external force. Then reflection signals were measured from the internal pipe, it’s namely called acquired signal and its display is a waveform display. The submerged water-coupled ultrasonic transducer was sent the frequency of 10 MHZ at the center to the straight direction. Because the perpendicular direction of the transducer receives the high reflection signals when comparing the angular direction to the pipe surface. The angular direction of the transducer mountain is not receiving the proper signal due to scattering, which is suitable for the analysis of crack (Barbian et al. 2011). After the measurement, the calculation of ultrasonic measurement data was obtained by judging the magnitude and return time of the wave type energy. The measured pipe has five sections, each section connected by welding.

Figure 3 shows the non-defect measured signal with the welded region. There are four welded joint regions, that were clearly observed by the ultrasonic transducer due to varying the thickness of the outer surface. Which was measured under normal conditions of pipe without surface defect. The average thickness of the weld region is about 17mm and the average thickness of a normal defect-free surface is about 11mm. Then two sets of defects were experimentally evaluated on the pipe surface such as holes and grooves on both sides. The distance between the probe and the inner wall of the pipe is about 11mm. Figure 4(a) shows the various structural defects signals on both sides of the pipe surface, at the size of the internal groove defect is 9mm and external groove defect map is 1mm and the diameter of the hole is 3mm. This figure shows the A-type imaging data of the measured surface, the length of the pipe is represented on the horizontal axis, and the depth (thickness) from the detection surface is represented on the vertical axis. When the immersed transducer sent out the sound signal to focus on the measuring surface, if there is a defect reflected signal will be varied (amplitude).

In this case, a 1mm external groove and a 9mm internal groove were observed as signals dropping down from the boundary to the middle. And these external and internal groove defects were found at approximately 200mm and 615mm in the X-axis position. In addition, there was a 3mm through-hole reflection was observed at the position of 495mm on the X-axis along with welding marks in the upward direction were seen. Here, changes can be observed in the depth of defects. It can be either drop downwards or increase upwards.

Figure 4(b) shows the outer defect of a 3mm depth waveform graph, it gradually dropped down and a 1mm internal defect signal was completely decreased due to the size of the defect. And a circular hole of 6mm diameter was positioned at the center of the pipe. This signal was formed in the upward direction. By increasing the diameter of holes, the measured value exceeds the thickness of the actual defect-free pipe due to the through-hole of the defect. Figure 4(c) shows the result of a 9mm diameter through-hole defect along with weld marks. This signal is similar to the size of 6mm due to the saturation. The changes can be observed in band size. The size of the band was slightly increased than the other two hole defects. The 3mm and 5mm sizes of the internal and external defect grooves are plotted, these signals were formed as a drop-down signal, as shown in Fig. 4(d) (Barbian et al. 2011).

Figures 5(a) and (b) shows the response of the other two sets of defects on the inner and outer surfaces. Which is gradually increasing the drops value with an increase of defect size as well as with decreasing the wall size.

Tables 1 and 2 shows the percentage of error values while comparing the actual and measured defect size of internal and external defects. The distance between the probe and the internal surface of the pipe is 11mm. And internal and external defect depths are 1mm, 3mm, 5mm, 7mm, and 9mm. The actual thickness error values of depths 1mm, 3mm, and 5mm were less than 3%. When increasing the depth of the internal and external defects is 7mm and 9mm error percentage slightly increased. The actual thickness error of the internal and external defects depth of 9mm was calculated at around 5.5–6.5%, and the actual thickness error of the internal and external defect depth of 7mm was calculated at around 4%. Due to the thin wall thickness of these two defects, results were observed in more energy losses due to scattering when crossing the defect boundaries.

Table 1

Wall thickness error of external grooves
	No defect	External defect 1mm	External defect 3mm	External defect 5mm	External defect 7mm	External defect 9mm
Actual thickness (mm)	11	10	8	6	4	2
Measured thickness (mm)	11.10	10.07	8.21	6.17	4.17	2.12
Error (%)	0.90	0.78	2.64	2.84	4.07	5.76

Table 2

Wall thickness error of internal grooves
	No defect	Internal defect 1mm	Internal defect 3mm	Internal defect 5mm	Internal defect 7mm	Internal defect 9mm
Actual thickness (mm)	11	10	8	6	4	2
Measured thickness (mm)	11.10	10.10	8.23	6.18	4.18	2.13
Error (%)	0.90	0.99	2.88	2.91	4.30	6.10

Figure 6(a) shows the detection results for all defects such as internal and external grooves, holes, and welding marks in different geometries. This figure shows the different colors. When the ultrasonic signals reach the top surface of the defect-free pipe, there can be received higher reflections without scattering. As a result, it covered more area of single color due to defect-free surfaces, namely, it's called background color. Then the red color indicates that the signal passes through the defect without being reflected. In this study, holes were measured in red color. And reflection signals of grooves were gradually dropped down from the boundary to the middle, it's noted in blue color. This is due to the lower reflection of the signal due to scattering. In addition, four weld marks are also distinguished in green in this figure.

Figure 6(b) Displaying the 3D surface image of analyzed whole defects, in the lower image shows clearly the measured holes and grooves defects. The zero reflection of the signal of holes marks it upwards in red color, and the lower reflection causes the groove to exhibit blue color to the downwards. Then the upper image is a top view corresponding to the defects.

This research is mainly aimed at analyzing pipeline inspection through ultrasound and developing 3Dsurface image. The hardware part of the inspection includes the design of stable inspection vehicle and the integration of ultrasonic inspection systems; the software part is to transfer the inspection data to the computer for calculation and analysis and to develop defect images. The ultrasonic flaw detection system is placed underwater to inspect the surface of the pipe. It measured the defects in simulated carbon steel pipes such as internal and external defects and deep holes. The measurement process is from the left end to the right end of the pipe, and the data of that point was recorded accurately. A single ultrasound probe was used to present the 3D surface of metal losses. The fixed distance between the tube surface and the ultrasonic probe collects the data and the error value was calculated within 6.5%. Thus the result of this research promotes the analysis of the loss of metallic surface with less percentage of error and it makes it more suitable for the application of the petrochemical pipeline industry and avoiding the environmental pollution.

Author contributions Ho Chang: Conceptualization, supervision, resource, writing-reviewing and editing. Mathivanan Durai: Conceptualization, methodology, data curation, writing-review and editing. Chun-Wei Huang: software, data curation, investigation. Chi-Chuan Peng: Software, writing-review and editing. Chou-Wei Lan: Conceptualization, supervision, writing-review and editing.

Funding This research was supported by the Ministry of Science and Technology of Taiwan (Grant No. MOST 108-2637-E-027-001).

Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval Not applicable.

Consent to participate Not applicable.

Consent for publication Not applicable.

Conflict of interest The authors declare no competing interests.

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Experimental study on the simulated defects detection in submerged transmission pipeline

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Abstract

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Introduction

Experimentation

Artificial Defects

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