Maintenance Work Research Articles

A Deep Learning Approach for Motor Fault Detection using Mobile Accelerometer Data

Electrical machines, which provide many conveniences in our daily life, may experience malfunctions that may adversely affect their performance and the general functioning of the industrial processes in which they are used. These failures often require maintenance or repair work, which can be expensive and time consuming. Therefore, minimizing the risk of malfunctions and failures and ensuring that these machines operate reliably and efficiently play a critical role for the industry. In this study, a one-dimensional convolutional neural network (1D-CNN) based fault diagnosis model is proposed for electric motor fault detection. Motor vibration data was chosen as the input data of the 1D-CNN model. Motor vibration data was obtained from a mobile application developed by using the three-axis accelerometer of the mobile phone. Three-axis data (X-axis, Y-axis and Z-axis) were fed to the model, both separately and together, to perform motor fault detection. The results showed that even a single axis data provides error-free diagnostics. With this fault detection method, which does not require any connection on or inside the motor, the fault condition in an electric motor has been detected with high accuracy.

Labelling of Annotated Condition Monitoring Data Through Technical Language Processing

We propose a novel approach to facilitate supervised fault diagnosis on unlabelled but annotated industry datasets using human-centric technical language processing and weak supervision. Fault diagnosis through Condition Monitoring (CM) is vital for high safety and resource efficiency in the green transition and digital transformation of the process industry. Learning-based Intelligent Fault Diagnosis (IFD) methods are required to automate maintenance decisions and improve decision support for analysts. A major challenge is the lack of labelled industry datasets, limiting supervised IFD research to lab datasets. However, features learned from lab environments generalise poorly to field environments due to different signal distributions, artificial induction or acceleration of lab faults, and lab set-up properties such as average frequency profiles affecting learned features. In this study, we investigate how the unstructured free text fault annotations and maintenance work orders that are present in many industrial CM systems can be used for IFD through technical language processing, based on recent advances in natural language supervision. We introduce two distinct pipelines, one based on contrastive pre-training on large datasets, and one based on a small-data human-centric approach with unsupervised clustering methods. Finally, we showcase one example of the small-data fault classification implementation on a CM industry dataset with a SentenceBERT language model, kMeans clustering, and conventional signal processing methods. Fault class imbalance and time-shift uncertainty is overcome with weak supervision through aggregates of features, and human-centric clustering is used to integrate technical knowledge with the annotation-based fault classes. We show that our model can separate cable and sensor fault recordings from bearing-related fault recordings with an F1-score of 93. To our knowledge, this is the first system to classify faults in field industry CM data based only on associated unstructured fault annotations.

Social support in workers’ physical activity

Objective To analyze the role of formal and informal social support in the practice of physical activity during workers’ leisure time. Methods A cross-sectional study carried out with 395 technical administrative workers at a public university. Data were collected using sociodemographic questionnaire, Baecke Habitual Physical Activity Questionnaire and Physical Activity and Social Support Scale. Data were analyzed using descriptive statistics, Student’s t test, Cohen’s d test and Analysis of Variance. Results Participants who reported some type of support for physical activity in their leisure time (92.2%) had higher means in the physical activity score. Institutional support (58.0%) had a prominent role as a potential influencer compared to support from immediate superiors (14.2%), although they had a certain differential among maintenance workers. Conclusion Social support plays an important role in promoting physical activity in workers’ leisure time. Institutional initiatives to encourage active behavior in the work environment need to be aligned with encouragement by immediate superiors so that they are more effective.

Care for Mechanics: Development of Motorcycle Workbench Based on ADDIE Model to Reduce Musculoskeletal Disorders

In a developing country like Indonesia, where the majority of the population is working in the informal sectors, there is a need for ergonomic tool intervention, which is low cost, and easy in terms of manufacturability with locally available materials. The rapid growth of motorcycle sales in Indonesia has stimulated the growth of motorcycle repair workshops. However, some of the non-authorized repair workshops ignore the occupational safety of the mechanics. This study aims to develop a motorcycle workbench as a tool for maintenance work to reduce musculoskeletal disorders (MSDs). The present study used Research and Development (R&D) with the ADDIE model combined with an ergonomic approach. The research subjects were 4 mechanics from one private workshop. Data was collected using interview, observation, and questionnaire techniques. The MSDs data was analyzed using Nordic Musculoskeletal Questionnaire (NMQ). The ergonomic risk factors were analyzed using Rapid Upper Limb Assessment (RULA) and Ovako Work Posture Analysis System (OWAS). The result showed an improvement in the work posture of mechanics. The MSDs complaint decreased based on NMQ Score. Furthermore, the RULA score and OWAS score also decreased. Thus, the development of the motorcycle workbench succeeded in reducing the MSDs complaint and improving mechanics’ occupational safety.

Research on the steam power system operation condition assessment method based on PCA-AE

The traditional steam power system operation condition assessment method relies on expert knowledge and is difficult to achieve complete objectivity. Most data-driven methods require training models with system anomaly data. In response to the above issues, this article proposes the A Novel PCA-AE Steam Power System Operation Condition Assessment Method. This method utilizes the PCA model to obtain assessment indicator parameters, and uses the Autoencoder to automatically assign weights and reconstruct parameters. Finally, the vector similarity principle is used for quantitative assessment. Based on the simulation data of marine nuclear power system steam turbine and the experimental data of supercharged boiler, the feasibility and generalization ability of this method are verified. The new method can meet the requirements of different steam power systems, including the nuclear power system secondary circuits, and provide accurate quantitative assessment results of operating conditions to guide maintenance work. Meanwhile, this method does not rely on expert knowledge and abnormal data training sets, and has fewer limitations compared to traditional methods.

Preparation of polyurethane concrete and its novel application in bridge expansion joint anchorage zone

The frequent damage and repair of bridge expansion joint anchorage zone has caused a great burden to the bridge maintenance work. The objective of this study is to prepare a steel fiber reinforced polyurethane concrete (SFPUC) with balanced multi-properties of workability, compressive strength, and flexural strength for the application in bridge expansion joint anchorage zone. A four-factor, five-level orthogonal experimental design was carried out to investigate the effects of the binder-aggregate ratio ( BA), cement content ( C), fine-coarse aggregate ratio ( FC), and steel fiber dosing ( SF) on the workability, compressive strength, and flexural strength, respectively. The multi-criteria decision-making (MCDM) method was used to transform the multi-response problem in the orthogonal experimental design into a single-response problem. Finally, a real engineering application and a finite element method were used to verify the feasibility of SFPUC for the expansion joint anchorage zone. The results show that the optimum proportion of SFPUC is BA (25%), C (20%), FC (20%), and SF (2.5%). The maximum principal stress in SFPUC anchorage zone is less than that in C50 steel fiber concrete anchorage zone under the same load. SFPUC is a highly promising material for bridge expansion joint anchorage zone repair.

Factor analysis evaluation of asphalt pavement performance considering structural strength and hidden cracks

At present, the maintenance work is mainly based on the performance of the asphalt pavement, but the structure distresses inside the pavement is easily overlooked. Therefore, in view of the shortcomings of the evaluation system, this study carried out road nondestructive testing, and obtained performance, deflection basin parameters, and structure distresses of the asphalt pavement and using factor analysis to extract common factors of all indicators, which considers evaluation of performance is more comprehensive and determining the weights according to the contribution rate makes the evaluation results more unbiased. Can provide some guidance for the determination of pavement maintenance time.

Deformation of High Rise Cooling Tower through Projection of Coordinates Resulted from Terrestrial Laser Scanner Observations onto a Vertical Plane

The appearance and development of new construction materials, technology and accurate geodetic instruments have led to the necessity of their inevitable use in the health monitoring, maintenance, and restoration of civil structures and special structures such as high-rise cooling towers. This paper presents an accurate practical and analytical method for determining the structural deformation and axis inclination of high rise cooling towers using terrestrial laser scanner (TLS) observations through the projection of tower surface points coordinates on a vertical plane. Four cooling towers in El-Mahla El-Kubra city, Egypt are observed and studied. Two of them with height 56 m, and the others were 36 m height. The studied four towers have different cross-section diameters along the tower height. Each tower has a cone shape with a curved wall. The equation of the tower wall is determined using TLS observations and least squares adjustment techniques. The equations of cone projection with a curved wall are derived and presented in this paper. From TLS observations, the radii and accuracy of each 2 m tower height are determined with center coordinates, and then the inclination of the tower axis is calculated and drawn. From the results of TLS observations, data processing, and analysis using the suggested techniques, it is deduced that there is a deformation in tower walls with small values. The specified technique for observations collection and TLS data analysis through projection on a vertical plane is significant and valuable for determining the structural deformation of circular high rise buildings and towers. From the results, there are obvious deformation values in some cooling towers, so maintenance work must be included. The towers also must be checked and monitored several times at brief intervals.

Influence of Smart Sensors on Structural Health Monitoring Systems and Future Asset Management Practices.

Recent developments in networked and smart sensors have significantly changed the way Structural Health Monitoring (SHM) and asset management are being carried out. Since the sensor networks continuously provide real-time data from the structure being monitored, they constitute a more realistic image of the actual status of the structure where the maintenance or repair work can be scheduled based on real requirements. This review is aimed at providing a wealth of knowledge from the working principles of sensors commonly used in SHM, to artificial-intelligence-based digital twin systems used in SHM and proposes a new asset management framework. The way this paper is structured suits researchers and practicing experts both in the fields of sensors as well as in asset management equally.

Comparing thermal strain in outdoor maintenance and indoor service workers in the mining industry during summer.

While working in the heat is a common practice within the Australian mining industry, it can lead to adverse effects on cognitive function, productivity, and physical health. This study aimed to compare the thermal strain experienced by maintenance workers and service workers in the mining industry during summer. Psycho-physiological parameters, manual dexterity, and cognitive function were assessed in maintenance workers (n = 12) and service workers (n = 12) employed at mine site villages in north-west Australia. Maintenance workers had the freedom to self-select their work intensity and predominantly worked outdoors (33.9±4.2°C, 38±18% RH), whereas service workers had to work to a fixed schedule and worked intermittently indoors (∼64% of work shift; 29.5±3.4°C, 48±8% RH) and outdoors (∼36%; 35.4±4.6°C, 47±21% RH). All workers underwent assessment at the beginning (day 2/3), middle (day 7/8), and end of their swing (day 13/14), at various time points throughout their 11-12 h shift. Service workers completed more steps (11282±1794 vs. 7774±2821; p<0.001), experienced a higher heart rate (p = 0.049) and reported higher ratings of perceived exertion (p<0.001), thermal discomfort (p<0.001), thermal sensation (p<0.001), and fatigue (p<0.012) compared to maintenance workers. Urinary specific gravity values were higher (less hydrated) in service workers (1.024±0.007) compared to maintenance workers (1.018±0.006; p = 0.007), with USG being overall higher post- compared to pre-shift (1.022±0.008 vs. 1.020±0.006; p<0.05). Core temperature, working memory capacity, processing speed and manual dexterity did not differ between occupations. Workers in hot environments who cannot self-select their work intensity should be educated about the importance of hydration before, during, and after their work-shifts and provided with more scheduled rest breaks during their shift. Employers should closely monitor workers for symptoms of heat illness, discomfort, and fatigue to ensure the health and safety of the workers.

Two-stage UHV GIL Fault Location Based on Ultrasonic Sensor Network

The failure of a long-distance Ultra-high voltage (UHV) Gas Insulated Transmission Line (GIL) during operation will cause great security risks to power transportation. How to locate GIL faults quickly and accurately and further carry out related operation and maintenance work is of great significance to the stable operation of the power grid. Based on this, this paper proposes a two-stage fault location method for UHV GIL based on an ultrasonic sensor network. In this method, ultrasonic sensors are configured in the shell of GIL to form an ultrasonic sensor network and internal faults are located by analyzing the signals collected from the network. The method is divided into two stages: 1) according to the collected signal data, the two sensors closest to the fault point are preliminarily identified, and then the fault point is roughly located, and obtain the data collected by the sensors; 2) we analyze sensor signal data, train and establish a network model based on recurrent neural network RNN for accurate fault location. The verification experiment shows that this method has fast location speed and high location accuracy, and can be effectively applied for quick maintenance, safe operation, and maintenance of GIL.

Chemical Attack on Concrete in Wastewater Treatment Plant: A Review

Wastewater treatment plant (WWTP) has become one of the most important structures nowadays and concrete is considered to be the most suitable material for the construction of this kind of structure for its several useful properties like durability, compressive strength, impermeability, abrasion resistance, etc. However in an aggressive environment, with the effects of constituents of wastewater and different chemicals applied in the treatment process of wastewater, concrete’s performance is greatly challenged. Chemicals like acid, sulfides, sulfates, salt, and gases generated from different reactions, micro-organisms, etc. can cause chloride ingress, carbonation, corrosion, sulfate attack, bio-deterioration, and erosion of concrete in wastewater treatment plants. As a consequence, a large amount of money is spent on the maintenance and repair works for wastewater treatment plants every year. Therefore, the quality of the concrete used in structures like WWTP must be very high. This study aims to explore the detrimental effects of various harmful chemicals on concrete in wastewater treatment plants, degradation mechanisms, and different methods of enhancing the resistance of concrete. The study also represents the current scenario of Bangladesh regarding this issue with the help of some excellent references, codes, and guidelines of important organizations and practical surveys.

Combined Pulmonary Fibrosis andEmphysema ina Patient With Chronic Occupational Exposure to Trichloroethylene.

Combined pulmonary fibrosis and emphysema (CPFE) is a clinical syndrome of upper-zone-predominant emphysema on high-resolution CT and a peripheral and basal-predominant diffuse pulmonary fibrosis. Multiple occupational and inhalational exposures have been associated with CPFE. We describe a U.S. veteran, who developed CPFE after a prolonged, intense exposure to trichloroethylene as an aircraft maintenance worker. We believe that this may be another example of occupational-associated CPFE.

Performance evaluation of rail trackbed stiffness: pre and post stabilisation

Excessive deflection of a rail in response to axle loading can lead to discomfort for passengers and increased wear of both railway structures and trains. These oscillations are often caused by poor trackbed stiffness which may be due to either soft subgrade and/or contaminated ballast. A variety of trackbed stabilisation (TBS) techniques are available to remediate soft subgrades and increase the safety of tracks within the railway network. Traditional TBS methods require track removal, which is expensive, disruptive and often inefficient maintenance works. Micro-piling, using screw piles installed between sleepers, is an innovative low disruption TBS technique. This paper investigates the performance of a soft subgrade and contaminated ballast section of rail line in the UK, before and after screw pile TBS. Pre and post remediation, a computer vision-based system was used to measure rail vertical deflections during train passages and then analysed to quantify the trackbed stiffness. Additionally, 3D finite element models are created and validated by the site measurements. The finite element models are used to simulate a range of different scenarios exploring how changes to the TBS piling layout and/or further works, such as ballast improvement could add further improvements or design efficiencies. Site measurements show TBS reduced rail deflection by 20–30%, indicating that micro-piling is an effective technique for soft subgrades. The finite element analysis revealed the efficiency of micro-piling is highly dependent on the conditions of ballast, strength of the ground at the pile toe, and the pile arrangement. When the aforementioned are optimised the rail deflection could be reduced to approximately 50% of the pre TBS condition.

Improved RAkEL's Fault Diagnosis Method for High-Speed Train Traction Transformer.

The traction system is very important to ensure the safe operation of high-speed trains, and the failure of the traction transformer is the most likely fault in the traction system. Fault diagnosis in actual work relies largely on manual experience. This paper proposes an improved RAkEL (Random k-Labelsets) algorithm for the fault diagnosis of high-speed train traction transformers. Firstly, this article starts from the large amount of "sleeping" fault maintenance data accumulated by the railway department, takes a single maintenance record as an instance, uses specific monitoring values to construct an instance vector, and uses the fault phenomena corresponding to the monitoring indicators as labels. Then, this paper improves the step of selecting k-labelsets in RAkEL, and extracts associated faults using the Relief algorithm. Finally, this paper excavates and uses the association rules between data and faults to identify traction transformer faults. The results showed that the improved RAkEL diagnostic method had a significant improvement in the evaluation indicators. Compared with other multi-label classification algorithms, including BR (Binary Relevance) and CLR (Calibrated Label Ranking), this method performs well on multiple evaluation indicators. It can further help engineers perform timely maintenance work in the future.

Main problems in the operation of metal gas discharge pipes

This paper considers the main problems of operation of metal gas discharge pipes on the example of research and survey work on the examination of building structures of the exhaust tower with three gas discharge trunks 180 m high, flue gas purification unit of the sintering shop of LLP "NDFZ" in Zhambyl region. Analysis of the actual technical condition, considered in this article exhaust tower with three gas discharge shafts, according to the results of the survey, its volume-planning and structural solutions, showed its generally unrepairable, due to the mass of characteristic critical and unacceptable damage to the load-bearing elements of the frame, physical fatigue of materials, significant corrosion wear of metal structures, which will require a significant amount of proposed repair and maintenance work to eliminate them. The conducted complex of researches has shown that the service life of chimneys built before the 1960s and after has practically expired. Repair or reconstruction of chimneys using previously mastered technologies and materials does not solve the issues of reliability improvement. Rational solutions to these problems are periodic technical expertise by highly specialized organizations and implementation on its basis of methods of overhaul of both gas-exhausting trunks and building structures and interface units, wide implementation of which will solve the problem of extending the life of chimneys.

A study on carbon dioxide emissions of high-polymer road maintenance technology based on life cycle assessment evaluation

Road repair and maintenance is the foundation for maintaining the health of roads. High-polymer grouting technology is an advanced non-excavation road repair and reinforcement technique. However, there is limited existing research focusing on this material and technique's carbon dioxide emissions and influencing factors. This study aims to elucidate the carbon dioxide emissions in the life cycle assessment of high-polymer grouting repair technology, using the example of maintenance work on semi-rigid asphalt pavement. The solidification reaction of each kilogram of high-polymer grouting material will release approximately 11.82 g of carbon dioxide. Comparative analysis was conducted by juxtaposing the carbon dioxide emissions at various stages of high-polymer grouting technology with those of cement grouting techniques and traditional excavation-based repair methods, encompassing conventional assessment (CA) on fuel combustion of engineering equipment and comprehensive life cycle assessment (LCA) on the materials production, fuel production, traffic delay, and engineering equipment. The results indicate a substantial reduction in carbon dioxide emissions for highway maintenance projects employing high-polymer grouting repair technology. The carbon dioxide emissions were reduced by 76.1% and 87.3% respectively per kilometer. The primary contribution to carbon dioxide reduction is observed during the construction phase and in terms of alleviating traffic delays. An indirect relationship is established between the carbon dioxide emissions of high high-polymer grouting materials and their strength, providing a reference for dynamically selecting material density in maintenance projects. The analysis of potential strategies to reduce CO2 emission in the transport sector and other industrial sectors suggests that the LCA model has the capability to accurately pinpoint the main contributing factors and CO2 emission levels stemming from specific maintenance processes within the intricate transportation system. The emphasis on enhancing the production technology of high-polymer materials is pivotal for further reducing carbon dioxide emissions in the context of high-polymer grouting repair technology.

Assessing Delay Factors and Mitigation Measures in Building Maintenance Works

When it comes to the operation of a construction industry, building maintenance is critical. Any structure must be well-maintained to prevent minor problems from becoming major ones. Delayed building maintenance may result in increased repair costs as well as a reduction in building lifespan. To avoid this problem, research has been conducted to identify the factors that cause building maintenance delays and mitigation measures to resolve building maintenance delays. To achieve the study's objectives, extensive literature research and a questionnaire survey were conducted. Based on previous literature research, accumulated data was used to create a questionnaire for 250 Malaysian building maintenance delay factors and mitigation measures. A group of professionals and experts, including top management, project managers, engineers, architects, assistant engineers, technicians, human resources and administration, and others, participated in this survey. SPSS statistical software was used to analyse the collected data using the average mean index method and correlation. According to the data, the three highest mean index values from the factors that cause maintenance work delays are an increase in maintenance costs as the building age increases, an incorrect timing for work can incur higher maintenance costs when a critical job item is overlooked, and improper planning and budgeting. For correlation analysis, it was found that the correlations amongst the five groups of delay factors are having strong relationship with Pearson correlation value of 0.5. While for mitigation measures of the delay, it was found that three highest ranks are prefer other organizational structure follows by policy and objective and good communication. The findings can assist construction practitioners in prioritising their maintenance works.

Combined Optimization of Maintenance Works and Crews in Railway Networks

This study develops optimal maintenance schedules for train lines, a critical endeavor ensuring the safety, efficiency, and reliability of railway networks. The study addresses the combined scheduling problem of maintenance works and crews on the railway networks. The baseline scheduling model is initially established with the primary objective of allocating maintenance tasks efficiently while adhering to pertinent constraints, encompassing task grouping and cost minimization. Subsequently, this baseline model is enhanced through the integration of crew scheduling, wherein work crews are strategically assigned to execute predefined tasks, thereby facilitating effective workload distribution. The combined maintenance work and crew scheduling problem is mathematically formulated as a binary linear programming model, enabling the attainment of globally optimal solutions. Comparing the outcomes of our enhanced model, which incorporates both maintenance works and crew schedules, with the baseline model that solely addresses maintenance works, we reveal that task grouping in accordance with predefined conditions leads to reduced overall costs by minimizing maintenance duration during various periods. Additionally, the judicious distribution of workload among the crews ensures comprehensive coverage of all essential tasks. These findings underscore the significance of our proposed approach in enhancing the operational efficacy and economic viability of railway maintenance scheduling, thereby offering valuable insights for practical implementation and future research endeavors.

Craft knowledge and sustainability

Historical gardens and green cultural environments maintain and transmit parts of our biocultural heritage. The gardener's maintenance and cultivation work affects both the content and our experience of these environments. While modern management methods in many cases are necessary to fulfil requirements for the work environment and efficiency, we want to investigate the extent to which alternative/traditional working methods can contribute with other qualities and with solutions for more sustainable management. Garden and Landscape Crafts bachelor's programme students at the Department of Conservation are practicing a lost craft skill by participating in a comparative cultivation experiment to gain an understanding of historical methods and their relation to the present, as well as the future development and revitalisation of sustainable historical environments.