Maintenance Work Research Articles

Safety Culture and Worker Perception in Highway Maintenance Operations: A Survey of Alabama Department of Transportation Maintenance Technicians

The survey entitled “Field Survey of Alabama Department of Transportation (ALDOT) Transportation Maintenance Technicians (TMTs) Perception of Worker Safety” investigates the safety perceptions and concerns of maintenance workers within ALDOT through a multifaceted analysis approach. The findings reveal critical insights that can significantly enhance ALDOT’s safety practices, training programs, and overall safety culture. Disparities in safety perceptions across different ALDOT’s areas were found, emphasizing the need for ALDOT to tailor its strategies to meet the unique needs of each area, ensuring that safety measures are both relevant and effective. The study emphasizes the importance of implementing targeted interventions focused on high-risk activities and prevalent safety concerns, allowing ALDOT to prioritize resources effectively. Additionally, the research highlights the necessity for continuous improvement by regularly evaluating safety initiatives based on feedback and best practices. This ongoing evaluation ensures that safety measures remain relevant and effective in addressing the evolving needs of TMTs. By integrating these insights into its safety management practices, ALDOT can cultivate a more proactive and resilient work environment that not only addresses immediate safety concerns but also establishes a sustainable culture of safety prioritizing employee well-being. The study provides a roadmap for future improvements in workplace safety and initiates discussions on the implications and recommendations for enhancing ALDOT’s and other transportation agencies’ safety management practices.

Decomposing maintenance actions into sub-tasks using natural language processing: A case study in an Italian automotive company

Industry 4.0 has led to a huge increase in data coming from machine maintenance. At the same time, advances in Natural Language Processing (NLP) and Large Language Models provide new ways to analyse this data. In our research, we use NLP to analyse maintenance work orders, and specifically the descriptions of failures and the corresponding repair actions. Many NLP studies have focused on failure descriptions for categorising them, extracting specific information about failure, or supporting failure analysis methodologies (such as FMEA). Whereas, the analysis of repair actions and its relationship with failure remains underexplored. Addressing this gap, our study makes three significant contributions. Firstly, we focused on the Italian language, which presents additional challenges due to the dominance of NLP systems that are mainly designed for English. Secondly, it proposes a method for automatically subdividing a repair action into a set of sub-tasks. Lastly, it introduces an approach that employs association rule mining to recommend sub-tasks to maintainers when addressing failures. We tested our approach with a case study from an automotive company in Italy. The case study provides insights into the current barriers faced by NLP applications in maintenance, offering a glimpse into the future opportunities for smart maintenance systems.

Longitudinal structural resilience of shield tunnel: Characterization and field application

The longitudinal structural resilience performance of shield tunnels is an important concern given the dramatic development of underground systems and the increasing demand for maintenance work. In this paper, a new model using longitudinal relative differential settlement as the index of tunnel structural resilience performance is proposed. The resilience metric (Re) is defined as the ratio of the area integrated by the residual performance during environmental disruptions to the area integrated by the normal performance for the corresponding duration. Then, the proposed resilience analysis model is applied to a well-documented case in Shanghai, where the existing metro tunnel is disrupted by a newly constructed large-diameter shield tunnel undercrossing and subsequently repaired by soil grouting. The variations of tunnel settlement concerning construction parameters and driving distance of the shield machine are analyzed. The performance degradation characteristics of the tunnel during disruption and recovery are effectively captured. The results show that 32.3 % of the performance loss is attributed to the new tunnel undercrossing in the first 38 days. After the completion of the grouting reinforcement, the tunnel performance is improved from 0.677 to 0.868, accounting for approximately 59.1 % of the performance loss during the crossing period. Moreover, the resilience metric (Re) is calculated as 0.764, indicating a high level of resilience for the existing metro tunnel in this case. In addition, other performance indexes based on tunnel longitudinal settlement are discussed, demonstrating the good rationality and applicability of the proposed index.

Evidence based management of medical devices: A follow-up experiment

Ensuring the optimal operation and longevity of medical devices is essential for maintaining high safety standards in healthcare. This study presents a significant advancement in the field by enhancing an existing evidence-based maintenance (EBM) framework, which is crucial for the effective management of medical equipment. Building upon previous methodologies, this research introduces a novel, comprehensive taxonomy for categorizing maintenance reports by revising and updating existing failure codes. This refinement addresses gaps in previous models, enabling more precise and effective maintenance strategies.A key innovation of this study is the development of a standard XML protocol, which addresses the current lack of standardization in the field, providing a consistent and unified approach to data management. This standardization is critical for improving communication and data exchange across different healthcare systems and technologies.To validate the enhanced EBM framework, the study applies it to corrective maintenance work orders related to Digital Angiography Systems, Magnetic Resonance Imaging, and Computed Tomography, using data from the Pisa University Hospital’s Computerized Maintenance Management System from 2021 to 2022. This validation demonstrates the reproducibility and adaptability of the framework across different medical equipment, healthcare contexts, and timeframes.The findings represent a significant advancement in healthcare technology management, offering a robust, standardized approach that optimizes the safety, functionality, and longevity of medical devices. This research not only expands maintenance standards in the healthcare sector but also provides a critical tool for addressing the current challenges in medical device maintenance, paving the way for more reliable and effective healthcare technologies.

Study on Fracture Delay of High-Strength Bolts in Road Bridge Maintenance

In the maintenance work of highway and bridge engineering structures, the fracture delay of high-strength bolts is a content that needs to be focused on and researched. Based on this, the paper analyzes the fracture delay of high-strength bolts in highway bridge maintenance, including an overview of the fundamental research on fracture delay and related specific studies. It is hoped that this study can provide scientific reference for the reasonable maintenance of high-strength bolts, so as to ensure the overall maintenance effect of highway bridge projects.

Research on Electric Heating Green Snow Melting and Anti-icing Technology for Tunnel, Bridge, and Culvert Entrances

This paper addresses the issue of electric heating snow melting at tunnel, bridge, and culvert entrances. It explores a novel carpet-style electric heating snow melting and anti-icing system for these areas. The study analyzes the shortcomings of existing electric heating snow melting methods and proposes effective measures for improvement. To accurately assess the characteristics of current snow melting techniques, the research considers the damage caused by traditional snow melting methods to road structures and subsequent maintenance issues, while emphasizing energy-saving and environmentally friendly technologies. The snow melting process was simulated using Star-CCM+. The results show that the new carpet-style electric heating elements significantly improve snow melting efficiency. Preheating the road surface before snow accumulation greatly reduces snow retention time, enabling timely snow and ice removal. Typically, electric heating elements in snow melting systems are installed beneath the road surface at tunnel entrances. After installation, to protect the elements and ensure smoothness, a layer of cement or another suitable material is poured over them. However, these heating elements require regular inspection or replacement, which necessitates breaking up the road surface, increasing maintenance costs, and disrupting normal traffic operations. This study overcomes these challenges by providing significant convenience for installation and maintenance work, reducing costs, and minimizing the impact on traffic operations.

Performance enhancement of asphalt mixture through the addition of recycled polymer materials

Enhancing the performance of asphalt binders is essential for ensuring the long-term durability and serviceability of asphalt mixtures, as it can help reduce the frequency of maintenance and repair work, ultimately leading to the development of more sustainable transportation infrastructure. To achieve this goal, this study investigates the effects of incorporating recycled polymer materials, including reclaimed polyvinyl chloride (PVC) and polystyrene (PS) derived from household waste, into hot mix asphalt. The experimental work involved subjecting the polymer-modified asphalt binders to a range of physical tests, such as softening point, penetration, ductility, indirect tensile strength, Marshall stability, and moisture susceptibility, and the results showed that the addition of recycled polymers, with an optimal content of 4%, led to lower penetration values and higher softening point temperatures, indicating improved resistance to temperature changes. Further analysis of the asphalt mixture performance revealed several beneficial outcomes, including a decrease in flow, a boost in the asphalt mixture's resistance to moisture-induced damage, and an improvement in Marshall stability and indirect tensile strength, with the inclusion of 4% recycled polymers yielding increases in Marshall stability of 43.7% and 37.4% for PVC and PS-modified mixes, respectively, and increments in indirect tensile strength of 32.2% and 29.7% for the same mixes. The study concludes that the use of recycled polymers can effectively enhance the performance and durability of asphalt mixtures, contributing to the development of more sustainable asphalt pavement construction practices by utilizing locally available or reused materials, which could lead to the increased knowledge and application of stronger and more weather-resistant asphalt mixes, ultimately promoting the advancement of sustainable transportation infrastructure.

Inferring on fluvial resilience from multi-temporal high-resolution topography and geomorphic unit diversity

The resilience of a river corridor represents its ability to withstand and recover from disturbances. Quantifying fluvial resilience in the face of various stressors is essential for integrating ecology and geomorphology in a context of river management. Geomorphic unit diversity analysis emerges as a valuable tool for characterizing and quantifying fluvial resilience to disturbances due to its inherent connection with fluvial dynamics. This paper aims to analyse and quantify the fluvial resilience of a wandering gravel-bed river affected by natural (e.g., floods) and human-induced (e.g., instream gravel mining) stressors. To achieve this goal, we use multi-temporal high-resolution topographic surveys of the Upper River Cinca (South-Central Pyrenees) spanning from 2014 to 2020. By employing the Geomorphic Unit Tool (GUT) on these surveys, we can map geomorphic units over time, quantify their diversity, and study geomorphic adjustments through morphodynamic signatures, altogether allowing inferring fluvial resilience.Our findings reveal that topographic changes (i.e., erosion and sedimentation) correlate with the type of stressor: maintenance works and gravel mining lead to degradation, while floods induce aggradation. Geomorphic Unit Diversity decreases following channel disturbances caused by gravel mining but rebounds after periods primarily stressed by floods, returning to pre-impact levels within six years. Geomorphic adjustments, such as channel incision and mid bar development, reflect erosion and sedimentation processes respectively, with channel maintenance works and floods being the main drivers. Despite the recovery of the geomorphic unit diversity within the reach, the deficit resulting from gravel extraction remains unresolved, perpetuating a degrading trend that poses risks in reducing lateral connectivity and could potentially catalyse future vegetation encroachment in bars and floodplains, causing changes on flood conveyance and hydraulics. Monitoring the river's geomorphic diversity provides crucial insights for effective conservation and management decisions regarding land use, development, and conservation along riverbanks, thereby sustaining or enhancing fluvial system resilience.

A Maintenance Cost and Work Performance Analysis on Irrigation Network at Kaubun Irrigation Area of East Kutai Regency, Indonesia

An irrigation network maintenance is an effort to maintain and secure the irrigation network to be always ready and well functioned. In facilitating its operational implementation and maintain its sustainability cycle, it can be attained through maintenance, repair, prevention, and security activities that must be conducted in continuity. The Kaubun irrigation area is one of the irrigation areas under the authority of central government with area length of 1,150 Ha (standard area) and 736 Ha (functional area), located in the East Kutai Regency. The Kaubun irrigation area has 1 (one) weir or dam and 2 (two) main canals. The irrigation network maintenance has not been carried out in routine and periodical ways either by the East Kalimantan Provincial Government or by the East Kutai Regency Government. Sediment accumulation is one of the main problems found in the secondary irrigation canal and able to cause canal blockage, reduced water flow capacity and increased infrastructure damage. This research was carried out by evaluating the Irrigation Network System and observing several factors causing channel damage with a guidance from regulation of Minister of Public Works and Public Housing Number:12/PRT/M/2015 on date 6 April 2015, regarding Exploitation and Maintenance of Irrigation Network. Result of the research showed that recapitulation of the work performance index for Kaubun Irrigation Network System was obtain the largest optimum value in Physical Infrastructure aspect with an index value of 29.01. Meanwhile, the result from main treatment priority by employing Analytic Hierarchy Process (AHP) method found the Physical Infrastructure aspect has a limiting value of 0.462. Finally, the routine and periodical maintenance costs for the Kaubun irrigation area is IDR.3.753.835.675.00

Development and Usability Evaluation of Augmented Reality Content for Light Maintenance Training of Air Spring for Electric Multiple Unit

The air spring for railway vehicles uses the air pressure inside the bellows to absorb vibration and shock to improve ride comfort and adjust the height of the underframe with a leveling valve to control stable driving of the train. This study developed augmented reality content that proposes a novel visual technology to effectively support the training of air spring maintenance tasks. In this study, a special effect algorithm that displays the dispersion and diffusion of fluid, and an algorithm that allows objects to be rotated at various angles, were proposed to increase the visual learning effect of fluid flow for maintenance. The FDG algorithm can increase the training effect by visualizing the leakage of air at a specific location when the air spring is damaged. In addition, the OAR algorithm allows an axisymmetric model, which is difficult to rotate by gestures, to be rotated at various angles, using a touch cube. Using these algorithms, maintenance personnel can effectively learn complex maintenance tasks. The UMUX and CSUQ surveys were conducted with 40 railway maintenance workers to evaluate the effectiveness of the developed educational content. The results showed that the UMUX, across 4 items, averaged as score of 81.56. Likewise, the CSUQ survey score, consisting of 19 questions in 4 categories, was very high, at 80.83. These results show that this AR content is usable for air spring maintenance and field training support.

Effect of Animated Instructional Software on Students’ Academic Achievement in Motor Vehicle Maintenance Work in Government Technical Colleges in Rivers State for Sustainable Economy

The study investigated the effect of animated instructional software on students’ academic achievement in motor vehicle maintenance work (MVM) in Government Technical Colleges in Rivers State, Nigeria for sustainable economy. The study adopted quasi-experimental non-randomized control group design. The population of the study was 95 MVM students from the three Government Technical Colleges in Rivers State that offer motor vehicle maintenance work (MVM). A sample of 75 respondents was drawn using a random sampling technique. Three objectives, three research questions, and three hypotheses guided the study. The instrument used for data collection was the Motor Vehicle Maintenance Work Achievement Test (MVMAT) which has thirty (30) multiple choice questions with four options A-D developed by the researcher and validated by three experts of which two are from the Department of Industrial Technical Education, Ignatius Ajuru University of Education, Port Harcourt and one from Department of Measurement and Evaluation, Rivers State University, Port Harcourt. The reliability of the instrument was determined by a pre-test on 10 respondents from Government Technical College, Owerri, Imo State, who are not part of the population and produced a reliability coefficient of.74 after subjecting student’s responses to the Kudar-Richardson (KR-20) formula. Mean and standard deviation were used to analyze data from the research questions while Analysis of Covariance (ANCOVA) was used to test the hypotheses of the study at .05 level of significance. The study revealed that the use of animated instructional software in the teaching of MVM aided the academic achievement of students, as those in the experimental group performed better than those in the control group. The study recommends, among others, that animated instructional software should be adopted by curriculum designers and NBTE for technical teachers who will be trained in the usage of the software and should be adequately supervised for effective implementation in instructional delivery.

Evaluasi pemeliharaan lanskap terhadap kapasitas tenaga kerja di trans studio mall bandung

Landscape maintenance work is part of landscape work that focuses on daily activities to maintain the quality of beauty, environment, health, and plant growth in a landscape. Landscape maintenance at Trans Studio Mall Bandung is included in operational work that aims to increase the selling value of the mall landscape area, if the work is carried out in accordance with the capacity and work program that has been determined. Trans Studio Mall Bandung is an international standard shopping center that has green open space in its area. The green open space is managed by the Landscape Maintenance Unit (UPL) of Trans Studio Mall. To evaluate the landscape maintenance at Trans Studio Mall, a study will be conducted on the capacity of each type of maintenance work throughout the landscape area. The evaluation of maintenance work that will be discussed includes daily routine work carried out by the gardener. The studies start from preparation, data collection, analysis, and synthesis. Data was collected through observation, interviews, and literature studies, then analyzed qualitatively and quantitatively. The results obtained show that the number of workers still does not meet the minimum capacity for landscape maintenance at Trans Studio Mall.

Moisture Sensitivity Performance of Hot Mix Asphalt Mixture Incorporating Fly Ash Geopolymer (FAG) Asphalt Binder

In Malaysia, Hot Mix Asphalt (HMA) is widely used in asphalt production. HMA is a mixture of asphalt and aggregates that give durability to the road surface for pavement. Due to vehicles excessive traffic loadings that cause road surface damage, this pavement technology frequently undergoes maintenance and rehabilitation work. This study used recycled material as a modified binder and showned the best result in increasing stiffness and better rutting performance with high percentages of additives. This research focuses on the effect of FAG additive on asphalt mixture performance evaluation according to SuperpaveTM mixes design method. The procedures were specified according to the American Association of State Highway and Transportation Officials (AASHTO), American Society for Testing and Materials (ASTM), British Standard (BS) and Malaysian Standard (MS). The granite aggregate type was produced by a local quarry with conventional asphalt binder grade 80/100 and 60/70. Incorporation FAG in modified asphalt binder as levels of 0, 3, 5, 7, 9, and 11% by mass of asphalt binder. The performance of moisture sensitivity showed low moisture damage susceptibility for the mixture based on consistent values of TSR, in which all the specimens met the minimum TSR threshold of 80%. The optimization findings indicated that 9% of fly ash geopolymer might be the ideal content for modifying the asphalt binder. Overall, research findings suggest that using geopolymers may have improved some of the characteristics of asphalt binder and the performance of asphalt binders in pavement applications. Thus, the outcomes of this research were significantly used for further performance test and analysis on the asphalt mixture.

FCT-Net: A dual-encoding-path network fusing atrous spatial pyramid pooling and transformer for pavement crack detection

Cracks are a typical form of road damage, and accurate detection of cracks is of great significance for road maintenance work and ensuring traffic safety. Recently, computer vision has gradually been applied in the field of crack segmentation. However, there are still some extremely challenging problems in crack segmentation, such as complex backgrounds, information loss caused by pooling and convolution operations, and insufficient fusion of global and local semantic information. In response to the above problems, this paper proposes a dual-encoding-path network with U-Net architecture called FCT-Net, by fusing channel atrous spatial pyramid pooling (CASPP) and transformer. Specifically, CASPP obtains multi-scale receptive fields by incorporating spatial and channel attention, while refining and extracting local features. Meanwhile, we introduce long-short distance attention to construct a novel transformer with the prominent characteristic of interaction between local and global attention features. In addition, a residual convolution module is designed to enhance the local features of the transformer. Furthermore, we devise a multi-scale attention weight cross fusion module to aggregate the features of the dual encoding branch, for reducing information loss during downsampling and suppress background information. Eventually, we evaluate the performance of FCT-Net by experiments on three public datasets. Extensive experimental results show that FCT-Net achieves higher F1-score and mean intersection over union (mIoU) than state-of-the-art segmentation networks on the DeepCrack537 and CrackLS315 datasets. Meanwhile, it has excellent segmentation performance for cracks in complex scenes, with the highest recall, F1-score, and mIoU respectively as 85.64%, 81.67%, and 84.05% on the CrackTree260 dataset.

Subsurface anomaly assessment in asphalt layers using Rayleigh waves dispersion characteristics: a test-pit study

ABSTRACT Any subsurface anomaly present in asphalt pavement layers may lead to their localised progressive structural failure. The detrimental effects of such anomalies are not visible on the top surface in the early stages. It may cause a major cost escalation if gone unnoticed during construction or maintenance works. Hence, there is a need for their quick and reliable detection and assessment. Present study explores the non-destructive assessment of subsurface anomalies (such as void/buried utility, etc.) in asphalt layers. This work developed a simple experimental approach using the two-receiver Spectral Analysis of Surface Waves (SASW) method to generate the experimental dispersion curves (EDC) whose shape characteristics are utilised for the detection, location, and identification of subsurface anomalies. An in-situ asphalt pavement test-pit facility was developed consisting of a number of different sub-sections with various anomaly conditions. A test system utilising high-frequency accelerometers was custom-integrated for such assessments. Based on the EDC shape characteristics, a direct information extraction technique was developed which does not require backcalculation procedures. The study found the proposed technique to be reasonably applicable for a quick, non-destructive detection and assessment of the subsurface anomalies. Further extensive testing with different profiles, anomalies, and test conditions will help in further acceptance of this simple approach.

Assessing lifetime occupational chrysotile inhalation exposure, respiratory symptoms, and lung cancer risk among brake maintenance workers in Malaysia.

This study aimed to estimate workers' occupational lifetime exposure to chrysotile and examine the respiratory symptoms and lung cancer risk. A total of 112 workers were interviewed about their occupational histories. Exposure modeling using information on the determinants of exposure was used to estimate chrysotile emissions. The cumulative lifetime exposure was then assessed for each worker. Respiratory symptoms were obtained using a validated questionnaire. Lung cancer mortality rate was also predicted using a model. Almost all the workers were male and young (mean age = 30 years, SD = 7). The estimated lifetime occupational chrysotile inhalation exposure ranged from 0.0001 to 0.0486 f/mL.years (median = 0.0018 f/mL.years, IQR = 0.486). A high prevalence of cough symptom (11.7%), and low estimated cancer risk (<1%) were reported. In conclusion, the lung cancer risk among our cohort of workers was at a low level because of lower cumulative lifetime occupational chrysotile exposure.

Sleep Behavior in Royal Australian Navy Shift Workers by Shift and Exposure to the SleepTank App.

Rotating shiftwork schedules are known to disrupt sleep in a manner that can negatively impact safety. Consumer sleep technologies (CSTs) may be a useful tool for sleep tracking, but the standard feedback provided by CSTs may not be salient to shift-working populations. SleepTank is an app that uses the total sleep time data scored by a CST to compute a percentage that equates hours of sleep to the fuel in a car and warns the user to sleep when the "tank" is low. Royal Australian Navy aircraft maintenance workers operating on a novel rotational shift schedule were given Fitbit Versa 2s to assess sleep timing, duration, and efficiency across a 10-week period. Half of the participants had access to just the Fitbit app while the other half had access to Fitbit and the SleepTank app. The goal of this study was to evaluate differences in sleep behavior between shifts using an off-the-shelf CST and to investigate the potential of the SleepTank app to increase sleep duration during the 10-week rotational shift work schedule. Royal Australian Navy volunteers agreed to wear a Fitbit Versa 2 with the SleepTank app (SleepTank condition), or without the SleepTank app (Controls), for up to 10 weeks from May to July 2023 during the trial of a novel shift rotation schedule. Participants from across 6 units worked a combination of early (6:00 AM to 2:00 PM), day (7:30 AM to 4:30 PM), late (4:00 PM to 12:00 AM), and night shifts (12:00 AM to 6:00 AM) or stable day shifts (6:00 AM to 4:00 PM). Differences in sleep behavior (time in bed, total sleep time, bedtime, wake time, sleep efficiency [SE]) between conditions and shift types were tested using Analysis of Variance. This study was approved by the Australian Departments of Defence and Veterans' Affairs Human Research Ethics Committee. Thirty-four participants completed the full study (n = 17 Controls; n = 17 SleepTank). There was a significant effect of shift type on 24-hour time in bed (TIB24; F(4,9) = 8.15, P < .001, η2 = 0.15) and total sleep time (TST24; F(4,9) = 8.54, P < .001, η2 = 0.18); both were shorter in early shifts and night shifts compared to other shift types. TIB24 and TST24 were not significantly different between conditions, but there was a trend for greater SE in the SleepTank condition relative to Controls (F(1,9) = 2.99, P = .08, η2 = 0.11). Sleep data collected by Fitbit Versa 2s indicated shorter sleep duration (TIB24, TST24) for Royal Australian Navy workers during early and late shifts relative to stable day shifts. Access to the SleepTank app did not greatly influence measures of sleep duration but may be protective against fatigue by affecting SE. Further research is needed to evaluate the utility of the SleepTank app as a means of improving sleep hygiene in real-world, shift-working environments.

Alternative for HPC22 after repairs in the drinking water distribution system

There is a risk of contamination by (pathogenic) microorganisms from the outside environment into the drinking water during maintenance or pipe breaches in the drinking water distribution system (DWDS) and, consequently, the drinking water distributed to consumers may result in possible detrimental effects on public health. Traditional time-consuming microbiological testing is, therefore, performed to confirm drinking water is not microbially contaminated. This is done by culturing methods of the faecal indicators Escherichia coli, intestinal enterococci and the technical parameters coliform bacteria and heterotrophic plate counts at 22 °C (HPC22). In this study, fast methods (adenosine triphosphate (ATP), flow cytometry, enzyme activity and qPCR) were compared as an alternative for HPC22. Using dilution series and field samples, ATP (ATPtotal-lab and ATPcell-mob) and enzymatic activity (ALP-2) methods proved to be the more reliable and sensitive than flow cytometry and qPCR methods for detecting microbiological contaminations in drinking water. Significant (p < 0.05) and relatively strong correlations (R2 = 0.61–0.76) were obtained between HPC22 and both ATP methods, enzyme activity and qPCR parameters, but relations with flow cytometry were weak (R2 = 0.24 – 0.52). The samples taken after repairs or a calamity from the DWDS showed in general limited variation in the HPC22 count and were in most cases below the guidance level of 1,000 CFU/mL. We recommend that the best performing alternative methods, i.e. ATPtotal-lab and ATPcell-mob and ALP-2, should be included next to HPC22 in additional field studies to further test and compare these methods to be able to decide which fast method can replace HPC22 analysis after maintenance work in the DWDS.

ТЕСТОВЫЙ КОНТРОЛЬ ТОПЛИВНЫХ НАСОСОВ СОВРЕМЕННОЙ АВТОТРАКТОРНОЙ ТЕХНИКИ

The article presents the results of a study of the energy balance when the technical condition of the fuel pump of agricultural machines changes. Over 30% of internal combustion engine failures occur in the fuel system. Timely diagnostics, repairs and maintenance work (the latter is often not provided for or not performed) of electric fuel pumps can increase the service life and service life. Calculation of the energy balance is a prerequisite for developing a new or upgrading an existing method for diagnosing a fuel pump. The importance of using current strength as a diagnostic parameter (when determining the technical condition) of the pump in the mode of creating maximum pressure in the fuel system is emphasized. Based on the research results, an additional diagnostic parameter can be the rate of increase in the pump supply current. Research has shown that with an increase in the hydraulic resistance of the fuel system by 90%, the average rate of current increase was 7.6 A/s. When the hydraulic resistance of the fuel supply system decreased by less than 10%, the average rate of current increase was 19.2 A/s. Current is a sensitive parameter that increases or decreases depending on the level of increase in hydraulic resistance or leaks in the fuel system. The pump power expended on hydraulic losses did not change significantly due to the constant value of the pump operating voltage. The ideas (methods, techniques) developed in the article are in good agreement with the issues of modeling processes in hydrodynamic tribocouplings of high-pressure fuel pumps, in particular for Common Rail systems. The research was carried out at the expense of the Russian Science Foundation grant No. 23-29-10042, Topic: Numerical modeling of processes in hydrodynamic tribocouplings of high-pressure fuel pumps for advanced high-pressure diesel engines https://rscf.ru/project/23-29-10042/.”

PSPMoni: A Robust Wear Monitoring Method of Pantograph Slide Plate

The pantograph slide plate (PSP) plays a crucial role in the daily maintenance of trains by transmitting electrical energy from the contact wire (CW) to the train. Automatic monitoring of PSP wear condition is essential to notice abnormal wear promptly. In field applications, the target PSP edge may be obscured by the rear side PSP due to the operating attitude of the pantograph, leading to false detections and interfering with the field maintenance work. Meanwhile, the scenario of the PSP occlusion is characterized by randomness, which brings a considerable challenge to the reconstruction of the occluded edges. A robust PSP wear monitoring method is proposed to improve the performance of wear detection in field applications, considering the PSP occlusion scenarios. Firstly, the wear area of the PSP is localized using the YOLOv5s model. Subsequently, a fusion of the morphology method and the Canny operator is employed to extract the edge of the PSP. Different occlusion types are identified through detailed observation, and corresponding edge reconstruction methods are proposed for occluded edges. Finally, a robust wear condition evaluation method and five evaluation criteria for assessing wear condition are introduced. Experimental results demonstrate that the system achieves accurate PSP wear detection with an accuracy of 0.6 mm, and the reconstructed edge at occlusion locations closely matches the target edge compared to other automatic systems.