Search Results (232)

This study assessed the status of water, sanitation, and hygiene (WASH) services at (49) selected primary schools in uMfolozi Local Municipality, which is situated in the province of Kwa-Zulu Natal in South Africa. Data were collected using an observational checklist tool and by conducting a walk-through survey to inspect the conditions of sanitary facilities, observe the hand-washing practices of the school learners, and analyse the accessibility to safe drinking water in school premises. The data were analysed with the Statistical Package for Social Science Version 29. This study revealed that there is easy access to safe drinking water in all but one school. The dependability of the water supply seemed to be one of the most urgent problems in every school, even though all of them have some kind of drinking water infrastructure on their grounds. Municipal water (n = 25, 36%) and rainwater (n = 25, 36%) were the most common type of water used in schools compared to borehole (n = 15, 22%) and tanker truck water (n = 4, 6%). Schools must have a reserved water supply because of the inconsistent supply of municipal water, and because rainwater is a seasonal harvest while borehole water may be affected by factors like load-shedding. The UNICEF-described ratio of one tap or disperser per fifty learners suggests that the water taps in the schoolyard were insufficient in some schools (n = 25, 36%). Rainwater is collected through a gutter system in the school building roofs and stored in 5000–10,000 Jojo tanks. Borehole water is pumped into Jojo tanks at an elevated position where it is stored, and learners receive the water through taps connected to the borehole tanks. During an emergency when there is no water supply from other sources, tanker trucks are hired to fill tanks that are also used to store rainwater. The borehole and rainwater quality appeared to be clear, but water treatment had not been performed, and the microbial quality was unknown. This shows that the Sustainable Development Goal (SGD) 6, clean water and sanitation, is still far from being met. According to national norms and standards for domestic water and sanitation services, people who do not use water treatment or purification techniques fall in the ‘no service’ category and contribute to the water backlog. Pit latrines (n = 46, 94%) and flush toilet (n = 3, 6%) were found to be the only convenient toilet systems used. The number of toilets is not sufficient according to the guidelines. There are (n = 46, 94%) of the schools in the study area using pit latrine due to insufficient or no water supply. In 89.8% of primary schools, sanitation facilities are in working condition in terms of repair and hygiene, while 10.2% are not usable in terms of hygiene, and these are mostly boy’s toilets. All schools (n = 46, 94%) that have flush toilets is because they received sponsorship from non-government stakeholders that funded them in achieving piped water systems that permit the functionality of flush toilets. For the purposes of this study, hygiene was evaluate based on the items found in toilets and handwashing practices. The hygiene aspects of toilets included tissues, cleanness, and toilet seat. For handwashing practices we looked the number of washing basins, the colour of water, and having soaps to use. In the schools that did provide handwashing facilities, some of the toilets were broken, there was no water, or there was no drainage system in place to allow them to function. However, according to the school act, the handwash basins should be inside the facilities. A total of (n = 7, 14%) of handwash basins were inside the toilets. Only (n = 2, 4%) of schools had handwashing facilities which were Jojo tanks with taps near toilets, which were outside of the toilet, with no soap provided. Additionally, (n = 40, 82%) of learners used drinking points for handwashing, which can possibly transmit microbes among them. The findings revealed that, in general, (n = 32, 64%) of school toilets were clean, while, in general, the girls’ toilets were cleaner than the boys’ toilets. In all the schools, the cleaning services were from the people who were involved in school nutrition. In conclusion, there were water sources available for access to water inside schools; however, the situation can be improved by increasing the number of water source points. Pit latrines were the main used toilets, which were in a majority of the schools, and did not have the necessary terms for hygiene such as handwashing basin, tissues, and others. The lack of the main aspect, i.e., access to water and sanitation items, results in an impact on hygiene to learners as they will fail to practice proper hygiene. However, improvement can still be made by keeping the boys’ toilets clean while increasing the number of handwashing basins inside the toilets, so that they do not use taps outside the toilets. Schools should work towards meeting the required number of handwashing basins to increase access to handwashing facilities. Full article

Ultrasonic testing technology is used to inspect pipe welds in nuclear and thermal power plants. This paper proposes a new method to measure weld defects in thick-walled pipes of about 100 mm using ultrasonic phased array technology. The effectiveness of annular arrays is confirmed by numerical simulations, and element arrangements that enable point focusing and sector scanning are considered. The energy concentration of annular arrays is 7% higher than that of linear arrays and 3% higher than that of matrix arrays. Similarly, the sound pressure ratio of grating lobes is equivalent to that of linear arrays and 20% lower than that of matrix arrays. This array probe is driven by 64 channels by dividing the ring of an 8-element annular array probe in parallel and shorting the elements at symmetrical positions. The effectiveness is examined by measuring specimens with flat-bottom holes and simulated spherical defects. The authors confirmed peaks in the echo intensity of a φ1 mm flat-bottom hole and a φ3 mm pseudo-spherical defect arranged at 5 mm intervals. Comparing the measured results with a conventional linear array transducer, the results from the proposed method show that the number and size of defects can be accurately measured. Full article

The estimation of robot pose and pipe diameter is an essential task for reliable in-line inspection (ILI) operations and the accurate assessment of pipeline attributes. This paper addresses the problem of robot pose and pipe diameter estimation for natural gas pipelines based on 3D time-of-flight (ToF) sensors. To tackle this challenge, we model the problem as a non-linear least-squares optimization that fits 3D ToF sensor measurements in its local coordinates to an elliptic cylindrical model of the pipe inner surface. We identify and prove that the canonical ellipse-based estimation method (C-EPD), which uses a canonical residual function, suffers from bias in diameter estimation due to its asymmetry to depth errors. To overcome this limitation, we propose the robust and unbiased estimation of pose and diameter (RU-EPD) approach, which employs a novel error-based residual function. The proposed function is symmetric to depth errors, effectively reducing estimation bias. Extensive numerical simulations and prototype pipeline experiments demonstrate that RU-EPD outperforms C-EPD, achieving an at least six times lower estimation bias and a 2.5 times smaller estimation error range in pipe diameter and about a 2 times smaller estimation error range in pose estimation. Full article

The main steam pipe elbow is a critical metallic component in thermal power plants. Due to prolonged exposure to high temperatures and pressures, it experiences microstructural degradation and creep damage, thereby affecting its service life. Currently, there is debate regarding the location of the weakest region within the elbow, with uncertainty over whether it lies in the inner arc or neutral plane area. This study investigates the microstructure and creep properties of both the inner arc and neutral surface regions of an elbow that has been in operation for 183,088 h, aiming to identify the actual weak region and explore the underlying creep damage mechanisms. The results indicate that under identical temperature and stress conditions, samples from the neutral plane region exhibit significantly higher creep rates and shorter creep rupture times compared to those from the inner arc region. This suggests that the creep life in the vicinity of the inner surface in the neutral plane is markedly lower than that in the inner arc region. Microstructural analysis before and after creep fracture reveals that key factors influencing the creep performance of 12Cr1MoV elbows include carbide size, precipitation amount and distribution, grain size and morphology, as well as the stability and uniformity of grain orientation. Specifically, the growth of intragranular precipitates, the accumulation and non-uniform distribution of grain boundary carbides, and the non-uniform distribution of grain sizes all contribute to the rapid formation of creep cracks and premature material failure. This study concludes that the weakest region in the elbow is located at the inner surfaces of the neutral plane. Future inspections and life assessments of thermal power plant elbows should therefore focus on this area to enhance the accuracy of life evaluations and ensure the safety of thermal power plants. Full article

The failure accidents of prestressed concrete cylinder pipe (PCCP) seriously affect the economic feasibility of the construction site. The traditional method of needing to stop construction for pipe inspection is time-consuming and laborious. This paper studies the PCCP broken wire identification algorithm based on deep learning. A PCCP wire-breaking test platform was built; the Distributed Fiber Acoustic Sensing Monitoring System (DAS) monitors wire-breakage events in DN4000mm PCCPs buried underground. The collected broken wire signal creates a time-frequency spectrum diagram dataset of the simulated broken wire signal through continuous wavelet transform (CWT). Considering the location of equipment limitations, based on the YOLOv5 algorithm, a lightweight algorithm, YOLOv5-Break is proposed for broken wire monitoring. Firstly, MobileNetV3 is used to replace the YOLOv5 network backbone, and Dynamic Conv is used to replace Conv in C3 to reduce redundant computation and memory access; the coordinate attention mechanism is integrated into the C3 module to make the algorithm pay more attention to location information; at the same time, CIOU is replaced by Focal_EIoU to make the algorithm pay more attention to high-quality samples and balance the uneven problem of complex and easy examples. The YOLOv5-Break algorithm achieves a mAP of 97.72% on the self-built broken wire dataset, outperforming YOLOv8, YOLOv9, and YOLOv10. Notably, YOLOv5-Break reduces the model weight to 7.74 MB, 46.25% smaller than YOLOv5 and significantly lighter than YOLOv8s and YOLOv9s. With a computational cost of 8.3 GFLOPs, YOLOv5-Break is 71.0% and 78.5% more efficient than YOLOv8s and YOLOv9s. It can be seen that the lightweight algorithm YOLOv5-Break proposed in this article simplifies the algorithm without losing accuracy. Moreover, the lightweight algorithm does not require high hardware computing power and can be better arranged in the PCCP broken wire monitoring system. Full article

This paper presents the design, kinematics, and development of a tendon-driven continuum robot for surgical applications. The continuum robot has a flexible and adaptable construction that imitates the movements of natural organisms. The robot’s unique structure comprises disk members, springs, and a continuum backbone member, enabling it to bend, contract, and deform in complex ways. The robot is operated by pulling tendons, giving it the agility and flexibility necessary to bend in confined spaces. This study discusses the main design considerations and challenges in creating a tendon-driven continuum robot, including the kinematics of the four-tendon mechanism. The developed tendon-driven continuum robot is categorized into two modules: the distal end and the proximal end. The distal end consists of the continuum robot structure, whereas the proximal module consists of the actuating unit that actuates the distal end. The experimental results demonstrate the continuum robot’s ability to be used in medical fields and pipe inspections because of the miniaturized design of the distal end, which allows it to enter confined spaces. This paper provides valuable insights into the design, kinematics, and appropriate materials to build a tendon-driven continuum robot; its bending and deformation capabilities can be used in many fields, especially surgical applications and confined space explorations. Full article

Regular inspection of urban drainage pipes can effectively maintain the reliable operation of the drainage system and the production safety of residents. Aiming at the shortcomings of the CCTV inspection method used in the drainage pipe defect detection task, a PDS-YOLO algorithm that can be deployed in the pipe defect detection system is proposed to overcome the problems of inefficiency of manual inspection and the possibility of errors and omissions. First, the C2f-PCN module was introduced to decrease the model sophistication and decrease the model weight file size. Second, to enhance the model’s capability in detecting pipe defect edges, we incorporate the SPDSC structure within the neck network. Introducing a hybrid local channel MLCA attention mechanism and Wise-IoU loss function based on a dynamic focusing mechanism, the model improves the precision of segmentation without adding extra computational cost, and enhances the extraction and expression of pipeline defect features in the model. The experimental outcomes indicate that the mAP, F1-score, precision, and recall of the PDS-YOLO algorithm are improved by 3.4%, 4%, 4.8%, and 4.0%, respectively, compared to the original algorithm. Additionally, the model achieves a reduction in both the model’s parameter and GFLOPs by 8.6% and 12.3%, respectively. It saves computational resources while improving the detection accuracy, and provides a more lightweight model for the defect detection system with tight computing power. Finally, the PDS-YOLOv8n model is deployed to the NVIDIA Jetson Nano, the central console of the mobile embedded system, and the weight files are optimized using TensorRT. The test results show that the velocity of the model’s inference capabilities in the embedded device is improved from 5.4 FPS to 19.3 FPS, which can basically satisfy the requirements of real-time pipeline defect detection assignments in mobile scenarios. Full article

In this study, the challenge of teleoperating robots in harsh environments such as underwater or in tunnels is addressed. In these environments, wireless communication networks are prone to congestion, leading to potential mission failures. Our approach integrates a Human–Robot Interface (HRI) with a network congestion control algorithm at the application level for conservative transmission of images using the Robot Operating System (ROS) framework. The system was designed to avoid network congestion by adjusting the image compression parameters and the transmission rate depending on the real-time network conditions. To evaluate its performance, the algorithm was tested in two wireless underwater use cases: pipe inspection and an intervention task. An Autonomous Underwater Vehicle for Intervention (I-AUV) equipped with a Visual Light Communication (VLC) modem was used. Characterization of the VLC network was performed while the robot performed trajectories in the tank. The results demonstrate that our approach allows an operator to perform wireless missions where teleoperation requires images and the network conditions are variable. This solution provides a robust framework for image transmission and network control in the application layer, which allows for integration with any ROS-based system. Full article

Screen systems are often neglected in practice. This can lead to local flooding, pollution of receiving watercourses, blockages of channels by debris, and safety problems for children playing. The aim of this case study is therefore to protect below-ground channels and people, prevent flooding, improve water quality, and save personnel costs through a new screen system maintenance, repair, and upgrade methodology. The results show that repairing or enlarging the screens optimizes their functionality and reduces the risk of flooding. A particular focus is on increasing the screen dimension from one- and two-dimensional to three-dimensional screens. The new variable safety priority and the bar spacing increase with the passage area. Screens at large discharges should therefore be prioritized. Cleaning sand traps reduces the risk of pipe blockages and improves the water quality of receiving waters. Fine particles often have too high nutrient and oxygen demand values. The installation of pre-screens can increase the efficiency of the main screens. Optimization of travel routes for maintenance teams can be achieved by better planning maintenance routes. Adapting and maintaining screens to climate change by applying the novel prioritization method is likely to be successful. This should include prioritized inspections, repairs, and adjustments to screen structures. Full article

The maintenance and inspection of sewer pipes are essential to urban infrastructure but remain predominantly manual, resource-intensive, and prone to human error. Advancements in artificial intelligence (AI) and computer vision offer significant potential to automate sewer inspections, improving reliability and reducing costs. However, the existing vision-based inspection robots fail to provide data quality sufficient for training reliable deep learning (DL) models. To address these limitations, we propose a novel multi-sensor robotic system coupled with a DL integration concept. Following a comprehensive review of the current 2D (image) and 3D (point cloud) sewage pipe inspection methods, we identify key limitations and propose a system incorporating a camera array, front camera, and LiDAR sensor to optimise surface capture and enhance data quality. Damage types are assigned to the sensor best suited for their detection and quantification, while tailored DL models are proposed for each sensor type to maximise performance. This approach enables the optimal detection and processing of relevant damage types, achieving higher accuracy for each compared to single-sensor systems. Full article

The anti-corrosion layer of the pipe provides corrosion resistance and extends the lifespan of the whole pipeline. Heat-shrinkable tape is primarily used as the pipeline joint coating material bonded to the pipeline weld connection position after heating. Delineating the bonding strength and assessing the quality of the bonded structure is crucial for pipeline safety. A detection technology based on nonlinear ultrasound is presented to quantitatively evaluate the bonding strength of a steel-EVA-polyethylene three-layer annulus bonding structure. Using the Floquet boundary condition, the dispersion curves of phase velocity and group velocity for a three-layer annulus bonding structure are obtained. Additionally, wave structure analysis is employed in theoretical study to choose guided wave modes that are appropriate for detection. In this paper, guided wave amplitude, frequency attenuation, and nonlinear harmonics are used to evaluate the structural bonding strength. The results reveal that the detection method based on amplitude and frequency attenuation can be used to preliminarily screen the poor bonding, while the acoustic nonlinear coefficient is sensitive to bonding strength changes. This study introduces a comprehensive and precise pipeline joint bonding strength detection system leveraging ultrasonic-guided wave technology for pipeline coating applications. The detection system determines the bonding strength of bonded structures with greater precision than conventional ultrasonic inspection methods. Full article

This paper describes experiments on finned tube heat exchangers, focusing on reducing the thermal contact resistance at the contact between the pipe and the lamella. Various contact materials, such as solders and adhesives, were investigated. Several methods of establishing contact were tested, including blowtorch soldering, brazing, and furnace soldering. Thermal camera measurements were carried out to assess the performance of the contact materials. Moreover, finite element analysis was performed to evaluate the contact materials and establish guidelines in the fin–tube connection modeling by comparing simplified models with the realistic model. Blowtorch brazing tests were successful while soldering attempts failed. During the thermographic measurements, reflective surfaces could be measured after applying a thin layer of paint with high emissivity. These measurements did not provide valuable results; thus, the contact materials were assessed using a finite element analysis. The results from the finite element analysis showed that all the inspected contact materials provided better heat transfer than not using a contact material. The heat transfer rate of the tight-fit realistic model was found to be 33.65 for air and 34.9 for the Zn-22Al contact material. This finding could be utilized in developing heat exchangers with higher heat transfer with the same size. Full article

At present, researchers in the field of pipeline inspection focus on pipe wall defects while neglecting pipeline defects in special situations such as welds. This poses a threat to the safe operation of projects. In this paper, a multi-node fusion and modal projection algorithm of steel pipes based on guided wave technology is proposed. Through an ANSYS numerical simulation, research is conducted to achieve the identification, localization, and quantification of axial cracks on the surface of straight pipelines and internal cracks in circumferential welds. The propagation characteristics and vibration law of ultrasonic guided waves are theoretically solved by the semi-analytical finite element method in the pipeline. The model section is discretized in one-dimensional polar coordinates to obtain the dispersion curve of the steel pipe. The T(0,1) mode, which is modulated by the Hanning window, is selected to simulate the axial crack of the pipeline and the L(0,2) mode to simulate the crack in the weld, and the correctness of the dispersion curve is verified. The results show that the T(0,1) and L(0,2) modes are successfully excited, and they are sensitive to axial and circumferential cracks. The time–frequency diagram of wavelet transform and the time domain diagram of the crack signal of Hilbert transform are used to identify the echo signal. The first wave packet peak point and group velocity are used to locate the crack. The pure signal of the crack is extracted from the simulation data, and the variation law between the reflection coefficient and the circumferential and radial dimensions of the defect is calculated to evaluate the size of the defect. This provides a new and feasible method for steel pipe defect detection. Full article

Detecting faulty pipelines in water management systems is crucial for ensuring a reliable supply of clean water. Traditional inspection methods are often time-consuming, costly, and prone to errors. This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. The YOLOv8 model is employed for object detection due to its exceptional performance in detecting objects, segmentation, pose estimation, tracking, and classification. By training on a large dataset of labeled images, the model effectively learns to identify visual patterns associated with pipeline faults. Experiments conducted on a real-world dataset demonstrate that the AI-based model significantly outperforms traditional methods in detection accuracy. The model also exhibits robustness to various environmental conditions such as lighting changes, camera angles, and occlusions, ensuring reliable performance in diverse scenarios. The efficient processing time of the model enables real-time fault detection in large-scale water distribution networks implementing this AI-based model offers numerous advantages for water management systems. It reduces dependence on manual inspections, thereby saving costs and enhancing operational efficiency. Additionally, the model facilitates proactive maintenance through the early detection of faults, preventing water loss, contamination, and infrastructure damage. The results from the three conducted experiments indicate that the model from Experiment 1 achieves a commendable mAP50 of 90% in detecting faulty pipes, with an overall mAP50 of 74.7%. In contrast, the model from Experiment 3 exhibits superior overall performance, achieving a mAP50 of 76.1%. This research presents a promising approach to improving the reliability and sustainability of water management systems through AI-based fault detection using image analysis. Full article

As a technological advantage of ultrasonic non-destructive testing, fully focused imaging can accurately feedback the defective characteristics of the inspected object, greatly improving the detection efficiency. This article aims to address the challenges of outdated and low detection rates in the detection technology of branch pipe fillet welds. The full matrix acquisition (FMC) and total focus method (TFM) ultrasonic detection technology are used for detection and defect image feature analysis. Firstly, a multi-mode, fully focused real-time imaging software system was developed to address the specificity of the detection object; secondly, a phased array detection system based on 64 elements was constructed; finally, a region wavelet denoising method based on TFM images was proposed to solve the problem of artifacts caused by poor coupling; and based on the feature extraction method for a minimum rectangle, we analyzed the size, position, angle, and other information regarding defects. Through experiments, it has been found that this technology can effectively improve the detection efficiency of branch pipe weld defects, with a detection rate of 100%. Based on the partition fusion denoising method, the defect imaging quality can be further improved; at the same time, based on the feature extraction method, the error is 0.1 mm, the length range of various defects is 2.3 mm–6.3 mm, the width range is 0.6 mm–0.8 mm, and the angle range is 52°–75°, which can provide an application basis for the localization, classification, and risk assessment of corner weld defects in branch pipes. Full article