Search Results (10)

Motor vehicles emit a large amount of air pollutants. Inspection and Maintenance (I/M) systems serve as a pivotal strategy for mitigating emissions from operational diesel trucks. However, the prevalent issue of blind repairs persists due to insufficient diagnostic capabilities at maintenance stations (M stations). To address this challenge, a multi-source information fusion methodology is proposed, integrating load deceleration testing from inspection stations (I stations), on-board diagnostics (OBD) data, and manual measurements at M stations. Critical diagnostic parameters—including nitrogen oxides (NOx) and particulate matter (PM) emissions, the ratio of measured wheel-side power to rated power, intake volume, common rail pressure, and exhaust back pressure—are systematically selected through statistical analysis and expert evaluations. An adaptive membership function is developed to resolve ambiguities in emission thresholds, enabling the construction of a robust fault diagnosis framework. Validation using 800 National V diesel truck maintenance records from a provincial automotive electronic health platform (2022 data) demonstrates a diagnostic accuracy of 92.8% for 153 emission-exceeding vehicles, surpassing traditional machine learning approaches by over 20%. By minimizing unnecessary repairs and optimizing maintenance efficiency, this approach significantly reduces resource waste and the lifecycle environmental footprints of diesel fleets. The proposed fuzzy-logic-based model effectively detects latent faults during routine maintenance, directly contributing to sustainable transportation through reductions in NOx and PM emissions—critical for improving air quality and advancing global climate objectives. This establishes a scalable technical framework for the effective implementation of I/M systems in alignment with sustainable urban mobility policies. Full article

Image retrieval is the process of searching and retrieving images from a datastore based on their visual content and features. Recently, much attention has been directed towards the retrieval of irregular patterns within industrial or healthcare images by extracting features from the images, such as deep features, colour-based features, shape-based features, and local features. This has applications across a spectrum of industries, including fault inspection, disease diagnosis, and maintenance prediction. This paper proposes an image retrieval framework to search for images containing similar irregular patterns by extracting a set of morphological features (DefChars) from images. The datasets employed in this paper contain wind turbine blade images with defects, chest computerised tomography scans with COVID-19 infections, heatsink images with defects, and lake ice images. The proposed framework was evaluated with different feature extraction methods (DefChars, resized raw image, local binary pattern, and scale-invariant feature transforms) and distance metrics to determine the most efficient parameters in terms of retrieval performance across datasets. The retrieval results show that the proposed framework using the DefChars and the Manhattan distance metric achieves a mean average precision of 80% and a low standard deviation of ±0.09 across classes of irregular patterns, outperforming alternative feature–metric combinations across all datasets. Our proposed ImR framework performed better (by 8.71%) than Super Global, a state-of-the-art deep-learning-based image retrieval approach across all datasets. Full article

Reinforced concrete bridges (RCBs) are essential elements of transportation infrastructure, necessitating ongoing inspection and maintenance to guarantee their durability and structural integrity. This research aims to develop an integrated framework for inspection and maintenance intervention in reinforced concrete bridges (RCB), leveraging the potential of as-is Bridge Information Modeling (BrIM). The methodology begins by converting 2D drawings into a 3D as-is BrIM model, facilitating a more accurate representation of the bridge’s current state. This is followed by creating a comprehensive bridge inventory, allowing for meticulous tracking of vital components and their condition. Subsequently, inspection data are acquired using advanced sensing technologies, enabling real-time data collection and analysis. Structural defects are modeled on the as-is BrIM model to enhance diagnostic capabilities, providing a visual representation of areas requiring intervention. The framework also makes it easier to create reports, ensuring that important information is efficiently shared with the right people. A thorough case study using a concrete bridge is used to show the effectiveness of the created framework. The BrIM framework’s potential to improve the bridge inspection and maintenance process was demonstrated by integrating inspection reporting with BrIM, which produced encouraging results. The research contribution to the body of knowledge is significant as the developed framework considerably enhances the administration of bridge inspection and maintenance procedures, resulting in greater efficacy by offering a thorough and clear picture of the bridge’s current state. Full article

Globally, bridges are rapidly aging, and traditional maintenance approaches face significant challenges in terms of efficiency and cost. To overcome these challenges, considerable research has been conducted to introduce enhanced bridge management systems (BMSs) based on bridge information modeling (BrIM) from various perspectives. However, most studies have highlighted the advantages of BrIM, while neglecting the practical issues that potential users may encounter on existing bridges. The primary problem is digitizing existing bridges that have not yet adopted BrIM. The universal applicability of BrIM should be carefully considered from the perspective of national maintenance authorities managing thousands of bridges, because modeling based on commercial software is expected to be time-consuming and costly. Therefore, in this study, information and functional requirements were derived from interviews with stakeholders, including bridge owners, managers, and site inspectors. Based on this understanding, a data-driven modeling approach using basic bridge information was implemented, and an inventory code system was integrated to efficiently manage and utilize the data. Moreover, mapping and deep learning-based vectorization were considered for managing inspection information, and features for bridge assessment, dashboards, and reporting were incorporated to support decision-making. The developed BrIM demonstrated the potential for enhancing maintenance efficiency through a case study. Particularly, significant improvements were observed in mandatory documentation tasks, along with their investigation and analysis, as required by regulations. Additionally, efficient modeling and data management were achieved for the existing bridge. Full article

NOx pollution is one of the greatest air quality issues that urban areas face today, particularly within the European Union (EU), yet currently this pollutant is only controlled through the homologation process. There is currently no periodic technical inspection (PTI) process for NOx emissions within the EU, leaving a weakness in the legislation that is currently allowing high polluters to negatively impact air quality. Work needs to be performed to incorporate a simple, quick, inexpensive, and representative test to accurately identify these high emitters within the on-road vehicle fleet. This paper investigates options for the incorporation of a NOx test into the EU PTI test procedures. In a trial constituting over 600 vehicles, a 3DATX parSYNC was used to measure the NOx emissions over a series of short test types. These are an idle test, two types of high idle test (a constant high idle and a rapid high idle), and an on-road driving dynamic acceleration test. The repeatability of all three test types was good. The NOx concentrations have strong correlations to the mass emissions for each test type, with the use of mean concentrations being deemed more representative than the use of maximum concentrations. The mean results across the tested fleet are calculated and used to define pass/fail thresholds for different vehicle types. The findings of this work show that multiple test methods have the potential to characterize NOx emissions from a vehicle, but in order to catch high emitters on a PTI test, the unloaded idle and high idle test types are not suitable substitutes for a dynamic acceleration test, particularly for petrol vehicles. Full article

The penetration of diesel particulate filters (DPFs) in the market is growing fast. However, in the current inspection/maintenance (I/M) regulation for these vehicles, particulate emissions were capped with smoke opacity, which is incompetent to identify the excessive particle number (PN) induced by non-major DPF failures such as small cracks in substrate. This research aimed at developing a fast identification method for such malfunctioning vehicles using a low-cost condensation particle counter (CPC). To verify the effectiveness of idle PN test, 33 China-5 and China-6 heavy-duty vehicles fueled with diesel and natural gas (NG) were tested using the regulatory portable emission measurement system (PEMS) as per China-6 protocol and idle PN tests using a low-cost CPC-based system. PN emissions from China-6 vehicles with malfunctioning DPFs were at a similar level to those from China-5 vehicles (without DPF), which were significantly higher than the proper counterparts. Idle PN tests using a CPC-based system managed to identify the vehicles with DPF failures. Volumetric PN concentrations of these vehicles were much higher than those of the proper ones. This study proved that an easy, fast, and low-cost procedure could be used to screen out those high emitters with DPF failure. Full article

Air pollution is a major cause of premature death in Greater Cairo, but studies on emission control are limited. We used local and international data to predict the impact of transport emission control measures on sector parameters including congestion. The International Vehicle Emission model accordingly estimated quantities of criteria, toxic and global warming emissions produced by on-road vehicles. Emissions were estimated for 2019 base case (2019-BC) and projected for 2030 under the ‘do nothing’ scenario (2030-DNS) and five scenarios: fuel subsidy removal (2030-FSR), road expansions (2030-RE), public transport improvements (2030-PTI), inspection and maintenance (I/M) programs (2030-I/MP), and fuel enhancements (2030-FE). The 2030-FSR would reduce emissions by 11.2% versus 2030-DNS. The 2030-RE resulted in an average increase of 37% in emissions compared with 2030-DNS since it induces more traffic. The 2030-PTI provides alternatives to car travel; hence, cars result in an average drop of 32.8% for all emission types compared with 2030-DNS. The 2030-I/MP exhibited reductions in PM₁₀ and toxic pollutants, of 35–54.8% compared with 2030-DNS. The 2030-FE reduced SO_x, benzene and N₂O emissions by 91.8%, 81% and 39.1%, respectively, compared with 2030-DNS. The 2030-I/MP is most effective in reducing health damaging pollutants while 2030-PTI positively impacts commuters’ lifestyle. Full article

Over the last decade, particular interest in using state-of-the-art emerging technologies for inspection, assessment, and management of civil infrastructures has remarkably increased. Advanced technologies, such as laser scanners, have become a suitable alternative for labor intensive, expensive, and unsafe traditional inspection and maintenance methods, which encourage the increasing use of this technology in construction industry, especially in bridges. This paper aims to provide a thorough mixed scientometric and state-of-the-art review on the application of terrestrial laser scanners (TLS) in bridge engineering and explore investigations and recommendations of researchers in this area. Following the review, more than 1500 research publications were collected, investigated and analyzed through a two-fold literature search published within the last decade from 2010 to 2020. Research trends, consisting of dominated sub-fields, co-occurrence of keywords, network of researchers and their institutions, along with the interaction of research networks, were quantitatively analyzed. Moreover, based on the collected papers, application of TLS in bridge engineering and asset management was reviewed according to four categories including (1) generation of 3D model, (2) quality inspection, (3) structural assessment, and (4) bridge information modeling (BrIM). Finally, the paper identifies the current research gaps, future directions obtained from the quantitative analysis, and in-depth discussions of the collected papers in this area. Full article

To improve air quality in urban centers, vehicle Inspection and Maintenance (I/M) programs were created to identify highly polluting vehicles and force them to undergo mechanical maintenance. In this context, a methodology, based on a single measurement campaign using a Remote Sensing Device (RSD), is presented in this work to assess the reduction in vehicles emissions obtained from implementing I/M programs. As a case study, an RSD campaign was carried out in Mexico, specifically in Monterrey’s Metropolitan Area (MMA). Approximately 0.4% of the vehicles registered in this region were sampled under similar conditions to those found in I/M programs. The results obtained suggested that 39% of the vehicles would not comply with the current national regulations for circulating vehicles. Following a conservative scenario, the implementation of a vehicle I/M program in this urban center has the potential of reducing the current mass emissions of HC, CO and NO in approximately 69%, 42% and 28%, respectively. Full article

Asian countries are facing major air pollution problems due to rapid economic growth, urbanization and motorization. Mortality and respiratory diseases caused by air pollution are believed to be endemic in major cities of these countries. Regulations and standards are the first requirement for reducing emissions from both fixed and mobile sources. This paper emphasizes monitoring problems such as vehicle registration systems, inspection and maintenance (I/M) systems and fuel quality monitoring systems for vehicles in use. Monitoring problems in developing countries share similar characteristics such as a weakness in government initiatives and inadequate operation of government agencies, which results from a lack of human resources and availability of adequate facilities. Finally, this paper proposes a method to assure air quality improvements under the different shares of emission regulations in these Asian countries and introduces an example of an evaluation method based on a policy survey to improve air quality. Full article