Tank Inspection Research Articles

Weld Seam Recognition and Tracking with Omnidirectional Wall-climbing Robot for Spherical Tank Inspection

Weld Seam Recognition and Tracking with Omnidirectional Wall-climbing Robot for Spherical Tank Inspection

Deep neural networks for external corrosion classification in industrial above-ground storage tanks

This paper uses transfer learning and fine-tuning approaches to explore EfficientNet smaller models for a multiclassification task of corrosion types in above-ground storage tanks. Data augmentation was used to increment the data an oil and gas company provided, reaching a dataset of around 5000 images. The images were stored in Google Drive and imported into Colab to train the models using TensorFlow and Keras. After the hyperparameters’ tuning a transfer learning model was selected and explored with fine-tuning. The EfficientNetB0 model delivered from fine-tuning accomplished 94 % performance. This work is the first attempt to deploy an artificial vision automatic tool for being implemented during tank inspection in the industrial sector. In further development, this model can be coupled with one based on object detection to remotely identify failures due to external corrosion issues, improving safety and reliability in oil and gas operations.

Single-Source VLCP System Based on Solar Cell Array Receiver and Right-Angled Tetrahedron Trilateration VLP (RATT-VLP) Algorithm

A significant deployment limitation for visible light communication and positioning (VLCP) systems in energy- and light-source-restricted scenarios is the reliance of photodetectors (PDs) on external power supplies, compromising sustainability and complicating receiver charging. Solar cells (SCs), capable of harvesting and converting environmental light into electrical energy, offer a promising alternative. Consequently, we first propose an indoor VLCP system that utilizes an SC array as the receiver, alongside a right-angled tetrahedron trilateration visible light positioning (RATT-VLP) algorithm based on a single light source and multiple receivers. The proposed system uses an SC array in place of PDs, utilizing binary phase shift keying (BPSK) signals for simultaneous communication and positioning. In experiments, we verified the system’s error-free communication rate of 1.21 kbps and average positioning error of 3.40 cm in a 30 cm × 30 cm area, indicating that the system can simultaneously satisfy low-speed communication and accurate positioning applications. This provides a viable foundation for further research on SC-based VLCP systems, facilitating potential applications in environments like underwater wireless communication, positioning, and storage tank inspection.

Risk-based performance assessment from fully manual to human-robot teaming in pressurized tank inspection operations

The use of robotics in the process industry has shown a stable, increasing trend, according to survey reports, reducing the exposure of operators to critical operations, mainly during maintenance. Moving from full manual (FM) to human-robot teaming (HRT) operations is expected to reduce the risks for operators and increase operational efficiency. The methods used to assess system performances require an adaptation. Traditional risk assessment techniques are no longer adapted to analyze the new way of working; the previous methods proposed for HRT systems have been criticized for their fragmentation, complexity, and lack of validation.This study proposed an integrated framework, including the qualitative and quantitative stages, to investigate the risk-based system performance and compare the full manual and human-robot teaming scenarios in pressurized tank inspection operations. The outputs demonstrated that the integrated framework worked for FM and HRT system performance assessment, considering multiple element types and their interdependencies, generating knowledge that can be exploited to reduce the system's risk and choose among different operational alternatives.

A dynamic risk assessment model based on multidimensional and quantitative inference theory

With the continuous increase in petroleum consumption and the trend towards more refined management, crude oil storage tanks are playing an increasingly crucial role in the petrochemical industry. However, the corrosion issue of crude oil storage tanks has consistently been a major factor limiting their service life, and leaks in crude oil tanks are often attributed to corrosion of the tank bottom. Due to the high cost and complexity associated with tank opening inspections, in this paper, directly observable information and physical quantities are utilized as indirect evidence, combined with Bayesian network, to indirectly determine the probability of tank corrosion. This approach allows for selective internal tank inspections, enabling effective risk assessment while also facilitating cost savings. Some parameters in the Bayesian network model are obtained through a probability estimation model combining expert experience and fuzzy set theory. Finally, the feasibility of the method is demonstrated by citing examples. The current model can offer a relatively reliable reference for evaluating the risks associated with tanks and their ancillary facilities, while also reducing the costs of tank inspections to some extent.

INVESTIGATION OF THE EFFECT OF CLAPS ON THE STRESS-STRAIN STATE OF TANK STRUCTURES

The need to study the problems of reliable operation of the reservoir system is relevant. Special attention should be paid to the specifics of the operation of oil storage tanks and their equipment. The Russian tank farm was formed in the 1970s, a significant part of it has a service life of more than 50 years. The experience of examining such structures with a long service life indicates the presence, in most cases, of the physical aging of their structural elements.
 The article presents the results of processing a cloud of points created using a ground laser scanner to determine the actual geometric deviations of the reservoir and their combined effect on the reliability of the reservoir.
 During the survey, a method of work was used that differs from the standard. In the field, a laser scanner was used instead of a theodolite; in office processing, software systems were used that simplify the tasks.
 In the process of research in the 3DR software package, a triangulation mesh model was created from a cloud of points from a set of finite elements to identify defects located on the wall. The data obtained can be compared with previous and future survey results. Also, the model can be used to create a calculation scheme in PC LIRA 10.
 We set the actual characteristics of the tank wall to the finite elements (the thickness of the first belt is 12 mm, the next ones 10 mm). The main load combinations were applied to the tank. The calculations were carried out for a combination of loads, including the own weight of the structures, the pressure of the stored product and the overpressure in the gas space. Circular and equivalent stresses according to the 4 (energy) theory of strength were analyzed.
 The use of a laser scanner and software systems reduces labor costs for tank inspection, improves the quality of work performed, makes it possible to see the real surface of the tank and take into account defects in the aggregate.
 This method is of practical importance and is currently used by the Department of Inspection of Buildings and Structures.

Tracking Sensor Location by Video Analysis in Double-Shell Tank Inspections

Double-shell tanks (DSTs) are a critical part of the infrastructure for nuclear waste management at the U.S. Department of Energy’s Hanford site. They are expected to be used for the interim storage of partially liquid nuclear waste until 2050, which is the target date for completing the immobilization process for all Hanford nuclear waste. At that time, DSTs will have been used about 15 years beyond their original projected lifetime. Consequently, for the next approximately 30 years, Hanford DSTs will undergo periodic nondestructive evaluation (NDE) to ensure their integrity. One approach to perform NDE is to use ultrasonic data from a robot moving through air slots, originally designed for cooling, in the confined space between primary and secondary tanks. Interpreting ultrasonic sensor output requires knowing where measurements were taken with a precision of approximately one inch. Analyzing video acquired during inspection is one approach to tracking sensor location. The top edge of an air slot is easily detected due to the difference in color and texture between the primary tank bottom and the air slot walls. A line fit to this edge is used in a model to calculate the apparent width of the air slot in pixels at targets near the top edge that can be recognized in video images. The apparent width of the air slot at the chosen target in a later video frame determines how far the robot has moved between those frames. Algorithms have been developed that automate target selection and matching in later frames. Tests in a laboratory mockup demonstrated that the method tracks the location of the ultrasonic sensor with the required precision.

Sizing-Based Flaw Acceptability in Weldments Using Phased Array Ultrasonic Testing and Neural Networks

Liquefied Natural Gas (LNG) is one of the major renewable energy sources and is stored and carried in a storage tank that is designed following international standards. Since LNG becomes highly unstable when it encounters oxygen in the air, a leakage from an LNG storage tank can cause a catastrophic industrial accident. Thus, the inspection of LNG storage tanks is one of the priorities to be completed before LNG is stored in a storage tank. Recently, the usage of Phased Array Ultrasonic Testing (PAUT) has been gradually increasing as the risks of RT emerge. PAUT has some obstacles to overcome in order to substitute RT, such as efficiency and accuracy. Specifically, the cost issue must be addressed. Therefore, many attempts to combine PAUT with Artificial Neural Networks (ANN) have been made. PAUT provides many types of 2D images of the inspected weldment. The S-scan is one of the 2D images provided by PAUT, and it displays the cross-sectional view of the specimen with a single transducer. The inspectors examine the S-scan image and other provided images of PAUT to detect, classify and size the flaw that exists in the weldment so that the decision of whether the inspected weldment with the flaw is acceptable can be made. Nowadays, most of the previous research on PAUT and ANN focuses on detecting and classifying the flaws in B-scan or S-scan images. However, the last step to determine the flaws’ acceptability is not yet covered. In this study, the flaw acceptance criteria of PAUT in various international standards are listed. EXTENDE CIVA is used to create the PAUT S-scan images. The S-scan images are labeled with the listed acceptance criteria. Then, they are used in Mask R-CNN training. After the training, some new S-scan images with flaws are used to test the performance, and this showed 96% precision and 87% recall. With the algorithm, the acceptability of a flaw in a weldment can be determined efficiently and it will reduce the burden of PAUT usage and reduce the time required for a full-length inspection.

Spatial Trajectory Tracking of Wall-Climbing Robot on Cylindrical Tank Surface Using Backstepping Sliding-Mode Control

Wall-climbing robots have been well-developed for storage tank inspection. This work presents a backstepping sliding-mode control (BSMC) strategy for the spatial trajectory tracking control of a wall-climbing robot, which is specially designed to inspect inside and outside of cylindrical storage tanks. The inspection robot is designed with four magnetic wheels, which are driven by two DC motors. In order to achieve an accurate spatial position of the robot, a multisensor-data-fusion positioning method is developed. The new control method is proposed with kinematics based on a cylindrical coordinate system as the robot is moving on a cylindrical surface. The main purpose is to promote a smooth and stable tracking performance during inspection tasks, under the consideration of the robot's kinematic constraints and the magnetic restrictions of the adhesion system. The simulation results indicate that the proposed sliding mode controller can quickly correct the errors and global asymptotic stability is achieved. The prototype experimental results further validate the advancement of the proposed method; the wall-climbing robot can track both longitudinal and horizontal spatial trajectories stably with high precision.

An Automatic Visual Inspection of Oil Tanks Exterior Surface Using Unmanned Aerial Vehicle with Image Processing and Cascading Fuzzy Logic Algorithms

This paper presents an automatic visual inspection of exterior surface defects of oil tanks using unmanned aerial vehicles (UAVs) and image processing with two cascading fuzzy logic algorithms. Corrosion is one of the defects that has a serious effect on the safety of the surface of oil and gas tanks. At present, human inspection, and climbing robots inspection are the dominant approach for rust detection in oil and gas tanks. However, there are many shortcomings to this approach, such as taking longer, high cost, and covering less surface area inspection of the tank. The purpose of this research is to detect the rust in oil tanks by localizing visual inspection technology using UAVs, as well as to develop algorithms to distinguish between defects and noise. The study focuses on two basic aspects of oil tank inspection through the images captured by the UAV, namely, the detection of defects and the distinction between defects and noise. For the former, an image processing algorithm was developed to improve or remove noise, adjust the brightness of the captured image, and extract features to identify defects in oil tanks. Meanwhile, for the latter aspect, a cascading fuzzy logic algorithm and threshold algorithm were developed to distinguish between defects and noise levels and reduce their impact through three stages of processing: The first stage of fuzzy logic aims to distinguish between defects and low noise generated by the appearance of objects on the surface of the tank, such as trees or stairs, and reduce their impact. The second stage aims to distinguish between defects and medium noise generated by shadows or the presence of small objects on the surface of the tank and reduce their impact. The third stage of the thresholding algorithm aims to distinguish between defects and high noise generated by sedimentation on the surface of the tank and reduce its impact. The samples were classified based on the output of the third stage of the threshold process into defective or non-defective samples. The proposed algorithms were tested on 180 samples and the results show its superiority in the inspection and detection of defects with an accuracy of 83%.

TCS-YOLO model for global oil storage tank inspection

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Failure analysis of local settlement induced Q345R bottom plate cracking of crude oil storage tank

A 5000m3 single deck floating roof crude oil storage tank was found to have a cracked Q345R bottom plate during an open tank inspection. To analyze the cause of the failure, a series of experiments were carried out. The results showed that the chemical composition of the failed crude oil storage tank bottom plate material Q345R had a slight excess of S, V, and Ti which causes the material to form a bainite structure, resulting in a hard and brittle material with poor toughness. Q345R is susceptive to H2S stress corrosion cracking according to SCC test. Based on the working condition investigation, the cracked plate was subjected to the local settlement and H2S contained corrosive medium. With the stress concentration induced by local settlement, the bottom plate cracked. In order to avoid such incidents, Q345R material should be avoided in H2S containing environment, and online monitoring should be carried out regularly to assess the overall condition of the tanks.

Spatial positioning robotic system for autonomous inspection of LPG tanks

PurposeAutomatic robots can improve the efficiency of liquefied petroleum gas (LPG) tank inspection and maintenance, but it is difficult to achieve high-precision spatial positioning and navigation on tank surfaces. The purpose of this paper is to develop a spatial positioning robotic system for tank inspection. The robot can accurately identify and track weld paths. The positioning system can complete robot’s spatial positioning on tank surfaces.Design/methodology/approachA tank inspection robot with curvature-adaptive transmission mechanisms is designed in this study. A weld path recognition method based on deep learning is proposed to accurately identify and extract weld paths. Integrated multiple sensors, the positioning system is developed to improve the robot’s spatial positioning accuracy. Experiments are conducted on a cylindrical tank to test weld seam tracking accuracy and spatial positioning performance of the robotic system. The practicality of the robotic system is then verified in field tests.FindingsThe robot can accurately identify and track weld seams with a maximum drift angle of 4° and a maximum offset distance of ±30 mm. The positioning system has excellent positioning accuracy and stability. The maximum angle and height errors are 3° and 0.08 m, respectively.Originality/valueThe positioning system can improve the autonomous performance of inspection robots and solve the problems of weld path recognition and spatial positioning. Application of the robotic system can promote the automatic inspection and maintenance of LPG tanks.

Multi-Legged Inspection Robot with Twist-Based Crouching and Fine Adjustment Mechanism

The monitoring and inspection of buildings, towers, and large chemical tanks can be dangerous and costly. A wall climbing multi-legged robot can climb and crouch to move the inspection probe closer to the wall surface. The typical wall-sticking crouching motion of multi-legged robot is unable to achieve this without an additional actuator at the foot base. This limits the design of a magnetic leg that is bulky enough to keep the robot stable during inspections. This paper provides the concept and implementation details of a coarse-to-fine inspection using a novel twisting motion to crouch the robot towards the steel surface without the need for an additional actuator at the magnetized foot joint. The center position error of this method is reported as less than 1 cm in radius. Additionally, this paper suggests using a linear motor to provide fine-tuning capability for the gentle touch of the ultrasonic inspection probe to the steel surface, protecting the probe from a direct crash during the coarse twisting crouch movement. Experiments have been conducted to confirm the validity of this concept on horizontally flat steel plates. The robot successfully crouch towards the surface and gently touch it with the ultrasonic probe. The results were reliable and comparable to manual inspection. For the 2 mm and 3 mm sample plates, the average measurement error compared to the ground truth from a vernier caliper was less than 2%, which is better than the measurement error (3%) of humans. The total time used was 2.475 seconds per inspection spot, which is 5.6 times faster compared to the expected time used to cover the same distance with a typical probe extension using a lead screw drive.

Structural considerations to minimise the risk of horizontal cracks in the wall of circular concrete tanks

The inspection of on-ground circular concrete tanks by the authors has shown that the formation of horizontal cracks in tank walls is a common serviceability issue in Australia. These cracks often lead to leakage or durability-related issues that impact the service life of tanks. In this research, a harmonised design approach is provided for designers to consider the contribution of different parameters such as liquid pressure and volumetric changes of concrete, autogenous shrinkage, solar, seasonal and thermal process loads to the serviceability design. A practical model has been developed to predict the vertical serviceability bending moments and the width of horizontal cracks in the wall of tanks without the need to perform complex Finite Element (FE) modelling. This model has been developed by establishing a mathematical correlation between the design inputs and results of FE analysis of 320 tanks. In addition, risk factors in the formation of horizontal cracks on the internal and external faces of tanks were investigated, and recommendations for minimising the risk of horizontal cracks are provided.

Design and Development of a Mobile Robotic System for Aircraft Wing Fuel Tank Inspection

<div class="section abstract"><div class="htmlview paragraph">This paper presents the design concept behind a novel remote visual inspection robotic system for fighter jet aircraft wing fuel tank inspection. This work is part of a larger research project which focuses on design, simulation, physical prototyping and experimental validation of a robotic system. Whereas this paper specifically focuses on the development concept of locomotion design choice for the robot. Therefore without an effective mobility method the robot will not be able to fulfill its purpose to access the hazardous confined spaces of the fuel tank. Aircraft wing fuel tank inspection is a challenging area of maintenance which requires a considerable amount of preparation and involvement of several tasks in order to conduct effective Visual and Non Destructive Inspection. The environment of an aircraft wing fuel tank poses several challenges due to both physical and atmospheric constraints which can be detrimental to human personal. This paper introduces an effective locomotion design which should allow the robot to enter and maneuver within confined spaces. The robot is relatively small, approximately 70mm in height and width yet, flexible enough to move within the restricted spaces of the wing. The mobile robot platform is a combination of small track systems that articulate like a snake. An additional mobile platform deploys an inspection sensor to reach the spaces that are unreachable by the robot body. Like other proposed robotic systems this particular proposal differs as it allows the robot to enter from the root of the wing and reach the narrower spaces towards with the wing tip. This paper highlights the stakeholder requirements to illustrate the foundation of the robotic system design. An overview of current complications of wing fuel tank inspection is presented and the analysis of current proposed robotic systems for wing fuel tank inspection. An engineering design methodology approach is followed for this project. Several locomotion methods are evaluated and an innovative locomotion method is illustrated with the use of CAD models. The desired outcome of this research is to eliminate the entry or close contact with the fuel tank by human personal.</div></div>

Characterization of Thickness Loss in a Storage Tank Plate with Piezoelectric Wafer Active Sensors

In terms of the structural health inspection of storage tanks by ultrasonic guided wave technology, many scholars are currently focusing on the tanks’ floor and walls, while little research has been conducted on storage tank roofs. However, the roof of a storage tank is prone to corrosion because of its complex structure and unique working environment. For this purpose, this paper proposes a reflection/transmission signal amplitude ratio (RTAR) coefficient method for corrosion depth assessment. We studied the relationship between the RTAR coefficient, the corrosion depth, and the guided wave frequency to establish a depth assessment model. More importantly, unlike the traditional reflection coefficient method, the characteristics of guided wave signals, including the propagation and attenuation, are introduced in this model for accurate assessment. To eliminate the interference of residual vibration and improve the detection accuracy of defects, we built a corrosion detection system by using piezoelectric sensors and carried out field tests to verify the performance of the proposed method. We demonstrate that corrosion defects with a minimum depth of 0.2 mm can be quantitatively evaluated.

Design and Development of Tank Cleaning and Inspection Robot

Design and Development of Tank Cleaning and Inspection Robot

Structural Health and Condition Monitoring with Acoustic Emission and Guided Ultrasonic Waves: What about Long-Term Durability of Sensors, Sensor Coupling and Measurement Chain?

Acoustic Emission (AE) and Guided Ultrasonic Waves (GUWs) are non-destructive testing (NDT) methods in several industrial sectors for, e.g., proof testing and periodic inspection of pressure vessels, storage tanks, pipes or pipelines and leak or corrosion detection. In materials research, AE and GUW are useful for characterizing damage accumulation and microscopic damage mechanisms. AE and GUW also show potential for long-term Structural Health and Condition Monitoring (SHM and CM). With increasing computational power, even online monitoring of industrial manufacturing processes has become feasible. Combined with Artificial Intelligence (AI) for analysis this may soon allow for efficient, automated online process control. AI also plays a role in predictive maintenance and cost optimization. Long-term SHM, CM and process control require sensor integration together with data acquisition equipment and possibly data analysis. This raises the question of the long-term durability of all components of the measurement system. So far, only scant quantitative data are available. This paper presents and discusses selected aspects of the long-term durability of sensor behavior, sensor coupling and measurement hardware and software. The aim is to identify research and development needs for reliable, cost-effective, long-term SHM and CM with AE and GUW under combined mechanical and environmental service loads.

Raw Scanned Point Cloud Registration with Repetition for Aircraft Fuel Tank Inspection

The aircraft fuel tank, as the source of fuel supply, is one of the key components for an aircraft. It is fastened to the fuselage with thousands of rivets, in which each rivet is sealed carefully to prevent the leakage. Thus, the sealing quality of the aircraft fuel tank needs to be precisely measured to ensure its normal function. To achieve the measurement, the complete 3D point clouds captured by 3D scanning are usually utilized. Therefore, it is necessary to align the different views of the aircraft fuel tank point clouds, to obtain the complete data. However, the aircraft fuel tank consists of abundant repetitive structures, such as the regular-distributed rivets, which can lead to mismatches in the aircraft fuel tank point clouds if using the conventional registration methods. In order to address the challenges, we propose a new registration framework, which is able to handle the point cloud match under the repetitive and complex scenes. First, a novel 3D descriptor called LP-PPF is constructed with the point and line features from the aircraft fuel tank point clouds, so as to identify the repetitive structures correctly. Then, according to the proposed descriptor, the accurate registration can be achieved between the neighboring point cloud pairs. Finally, based on the results of pairwise registration, the complete aircraft fuel tank point cloud can be obtained via the multi-view registration method. Experiments demonstrate that our method achieves favorable results on both synthetic and raw scanned point cloud data.