A novel smart caliper foam pig for low-cost pipeline inspection—Part A: Design and laboratory characterization

Canavese, Giancarlo; Scaltrito, Luciano; Ferrero, Sergio; Pirri, Candido Fabrizio; Cocuzza, Matteo; Pirola, Marco; Corbellini, Simone; Ghione, Giovanni; Ramella, Chiara; Verga, Francesca; Tasso, A.; Lullo, A. Di

doi:10.1016/j.petrol.2015.01.008

Cited by 33 publications

(13 citation statements)

References 7 publications

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“…Therefore, PIGs are applied for online monitoring of pipeline functionality in an operational condition. This online monitoring helps in taking corrective actions at the proper time and is useful for increasing the lifespan of pipelines (23). The most important identified risks in pigging process, such as high gas/liquid pressure in pipelines, excessive and uncontrolled speed of a PIG, the PIG striking equipment or operators and explosion, may lead to catastrophic accidents.…”

Section: Introductionmentioning

confidence: 99%

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

et al. 2019

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Background: Pigging operation is one of the maintenance activities that is used to check pipeline functionality in operational conditions using a PIG device and high pressure of liquid/gas, which is potentially hazardous. Objectives: The present study aimed at customizing SPAR-H methodology for the pigging operation using Bayesian networks (BNs). It also aimed at identifying and analyzing human errors in pigging operation in a gas transmission company. Methods: The current article was composed of two main steps. In the first step, the SPAR-H BN model was developed using expertelicited prior probabilities of pigging operation applied to Bayesian network. In this step, CPTs of PSF nodes are constructed using prior probabilities, which are achieved from expert opinion. The CPT of error node is developed using coding process of SPAR-H formula in a simulation node. In the second step, a descriptive study was carried out to estimate the probability of human errors in pigging operation in a gas transmission plant in Iran. First, hierarchical task analysis (HTA) was conducted by walking through the pigging operation and interviews with workers. Next, the SPAR-H BN model was utilized for estimation of human error probability. Results: The developed model was tested on the pigging operation subtasks. In the considered case study, the mean probability of human error was estimated as 0.184. The highest probability of human error was related to "opening the kicker valve for enhancing pressure" subtask. Conclusions: The BNs were helpful to adapt the SPAR-H methodology to the pigging operation using dedicated prior probabilities. Beside that, the probabilities of human error can be updated taking into account the more realistic operational and environmental conditions.

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Section: Introductionmentioning

confidence: 99%

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

et al. 2019

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“…For long-distance pipeline systems, the PIG must be able to collect data with a circumferential resolution (cr) of 8 mm at every axial displacement of 3 mm, according to international standards [4,5]. The PIG calculates its axial displacement using odometers, gyroscopes, and externally installed markers, which signalize specific locations [6,7]. For long-distance pipeline systems, ultrasound, magnetic flux leakage, and eddy current are the most common technologies used for the automatic inspection [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Design and Validation of an Articulated Sensor Carrier to Improve the Automatic Pipeline Inspection

MARTINEZ

Rodríguez-Olivares

Torres-Torres

et al. 2019

Sensors

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Pipeline inspection gauges (PIGs) carry out automatic pipeline inspection with nondestructive testing (NDT) technologies like ultrasound, magnetic flux leakage, and eddy current. The ultrasonic straight beam allows technicians to determine the wall thickness of the pipeline through the time of flight diffraction (TOFD), providing the pipeline reconstruction and allowing the detection of several defects like dents or corrosion. If the pipeline is of a long distance, then the inspection process is automatic, and the fluid pressure pushes the PIG through the pipeline system. In this case, the PIG velocity and its axial alignment with the pipeline cannot be controlled. The PIG geometry, the pipeline deformations, and the girth welds cause a continuous chattering when the PIG is running, removing the transducers perpendicularity with the inspection points, which means that some echoes cannot be received. To reduce this problem, we propose a novel method to design a sensor carrier that takes into account the angularity and distance effects to acquire the straight beam echoes. The main advantage of our sensor carrier is that it can be used in concave and convex pipeline sections through geometric adjustments, which ensure that it is in contact with the inner pipe wall. Our improvement of the method is the characterization of the misalignment between the internal wall of the pipeline and the transducer. Later, we analyzed the conditions of the automatic pipeline inspection, the existing recommendations in state-of-the-art technology, and the different mechanical scenarios that may occur. For the mechanical design, we developed all the equations and rules. At the signal processing level, we set a fixed gain in the filtering step to obtain the echoes in a defined distance range without saturating the acquisition channels. For the validation, we compared through the mean squared error (MSE) our sensor carrier in a straight pipe section and a pipe elbow of steel versus other sensor carrier configurations. Finally, we present the design parameters for the development of the sensor carrier for different pipeline diameters.

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“…PIGs check carbon-steel pipelines used for the distribution of oil and water [ 11 ]. If the pipeline is in the order of kilometers in length, the PIG carries out an automatic inspection, where the circumferential inspection is made based on external markers and measurements from odometers and gyroscopes that allow the determination of the displacement of the PIG [ 12 ]. The angle beam and straight beam are the ultrasonic nondestructive evaluation (NDE) technologies most commonly used in automatic inspection of pipelines [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Improvement of Ultrasonic Pulse Generator for Automatic Pipeline Inspection

Rodríguez-Olivares

Cruz-Cruz

Gómez-Hernández

et al. 2018

Sensors

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This paper presents the improvement of an ultrasonic pulse generator for a pipeline inspection gauge (PIG), which uses 64 transducers for inspecting distances up to 100 km with an axial resolution fixed at 3 mm and variable speeds between 0 and 2 m/s. An ultrasonic pulse generator is composed of a high-voltage (HV) MOSFETs, driver logic and an HV power supply. We used a DC-HV DC converter device as the HV power supply because it reduces the size of the ultrasound system considerably. However, pipeline geometry and inspection effects such as hammer and shock cause a variable pulse repetition frequency (PRF), producing voltage drops, poor quality of the HV pulse generated, failures in the dimensioning of defects and damage to devices by over-voltage. Our improvement is to implement a control scheme to maintain the high quality of the HV regardless of the variable PRF. To achieve this, we characterized three transfer functions of the DC-HV DC converter, varying the connected load to 10%, 45% and 80%. For the characterization, we used the least squares technique, considering an autoregressive exogenous (ARX) model. Later, we compared three control schemes: (1) proportional-integral-derivative (PID) tuned by simultaneous optimization of several responses (SOSR), (2) PID tuned by a neural network (NN) and (3) PI tuned by the analytical design method (ADM). The metrics used to compare the control schemes were the recovery time, the maximum over-voltage and the excess energy when the shock and hammer effects happen to occur. Finally, to verify the improvement of the HV pulser, we compared the ultrasonic pulses generated for various frequencies and amplitudes using the pulse generator with and without the control scheme.

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A novel smart caliper foam pig for low-cost pipeline inspection—Part A: Design and laboratory characterization

Cited by 33 publications

References 7 publications

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

Design and Validation of an Articulated Sensor Carrier to Improve the Automatic Pipeline Inspection

Improvement of Ultrasonic Pulse Generator for Automatic Pipeline Inspection

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