Tomographic image reconstruction of monitoring flaws on gas pipeline based on reverse ultrasonic tomography

Abstract

The capability of a technique to reconstruct a tomographic image of flaws existence on gas pipeline via reverse ultrasonic tomography is presented. The ultrasonic tomography system is developed to monitor flaws circumferentially on pipeline with contactless measurement of distance from sensors to the pipe. In oil and gas industry, the applications of ultrasonic tomography technique for flaw detection in pipeline are limited as this technology is still in its infancy. The design of the ultrasonic tomography system consists of ultrasonic sensing system, data acquisition and image reconstruction system. A reflection mode of ultrasonic sensor is used where the output ultrasonic signal reflected from the pipe to the sensor is acquired. The collected data will be used in image reconstruction system to visualize the image. In image reconstruction process, a linear back projection algorithm is used in order to reconstruct the image of the pipe profile with flaws existence. The back projection algorithm is derived by the mathematical relationship of forward and inverse problem. This reconstruction algorithm is implemented in Matlab software to analyze the performance of the technique for different projection and arrays. Through the simulated result, the reconstructed image based on four projections is found to be less smeared compared to the image based on two projections. The effect of aliasing on the image is also reduced as the number of projection is increased. Several images of pipe with flaws existence are reconstructed based on four projections, with 7 x 7 arrays of pixels and twenty-eight of ultrasonic sensors.

Logistic Regression for Machine Learning in Process Tomography

“…UST is associated with some forms of medical research, while in industry this method is still not widely used. This is confirmed by the quotation from [36], in which the authors write “in oil and gas industry, the applications of ultrasonic tomography technique for flaw detection in pipeline are limited as this technology is still in its infancy”. When comparing electrical, magnetic and ultrasound tomography, it can be noted that the most innovation is in the field of electrical impedance tomography (EIT) [35], electrical capacitance tomography (ECT) [26] and magnetic resonance [37,38].…”

“…Among the existing problems of process tomography, the following topics can be mentioned: corrosion control of wall loss in places of pipe support [39], imaging of hidden defects inside metal elements [40], reinforced concrete inspection [23,41], detection of cracks or voids in nonmetallic materials [42], monitoring flaws of gas pipelines [36], bubble detection for two-phase liquid and gas [15,20,43], monitoring of flood embankments [11,34,44] and others.…”

Modified algebraic reconstruction technique based on circular scanning geometry to improve processing time in photoacoustic tomography

“…As we know, the amplitude of the signal received by a piezoelectric sensor has a direct relationship with the size of the tumor $$(p\propto r)$$ and an inverse relationship with the distance of the tumor from the sensor $$\left(p\propto \frac{1}{d}\right)$$. The relationship of the attenuation of acoustic pressure shows that with increasing distance, the acoustic pressure in the environment decreases 31,32 $$${P}_{z}={P}_{0}{e}^{-\alpha z}$$$in which $$\alpha $$ is the amount of attenuation inside the environment.We can calculate the radius of the tumor by the following equation: $$$r=\frac{p(1,{target})}{{Probe}\,{pointer}(1,{target})}\times {constant}$$$in which, p (1, target ) is the amplitude of the signal received by the sensor that has the fastest peak among the received signals, and Probe pointer (1, target ) is the time interval of receiving the signal by the same sensor in microseconds.…”

“…As we know, the amplitude of the signal received by a piezoelectric sensor has a direct relationship with the size of the tumor $$(p\propto r)$$ and an inverse relationship with the distance of the tumor from the sensor $$\left(p\propto \frac{1}{d}\right)$$. The relationship of the attenuation of acoustic pressure shows that with increasing distance, the acoustic pressure in the environment decreases 31,32 $$${P}_{z}={P}_{0}{e}^{-\alpha z}$$$in which $$\alpha $$ is the amount of attenuation inside the environment.…”

“…The relationship of the attenuation of acoustic pressure shows that with increasing distance, the acoustic pressure in the environment decreases. 31,32 P P e =…”