• Geomechanics and Engineering
• /
• v.13 no.6
• /
• pp.997-1010
• /
• 2017

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

• Geomechanics and Engineering
• /
• v.17 no.3
• /
• pp.295-305
• /
• 2019

The bedding plane has a significant influence on the effect of blasting fragmentation and the overall performance of underground mining. This paper explores the effects of fragmentation of the bedding plane and different angles by using the numerical analysis. ANSYS/LS-DYNA code was used for the implementation of the models. The models include a dynamic compressive and tensile failure which is applied to simulate the fractures generated by the explosion. Firstly, the cracks propagation with the non-bedding plane in the coal with two boreholes detonated simultaneously is calculated and the particle velocity and maximum principal stress at different points from the borehole are also discussed. Secondly, different delay times between the two boreholes are calculated to explore its effects on the propagation of the fractures. The results indicate that the coal around the right borehole is broken more fully and the range of the cracks propagation expanded with the delay time increases. The peak particle velocity decreases first and then increases with the distance from the right borehole increasing. Thirdly, different angles between the bedding plane and the centerline of the two boreholes and the transmission coefficient of stress wave at a bedding plane are considered. The results indicated that with the angles increase, the number of the fractures decreases while the transmission coefficient increases.

• Safety and Health at Work
• /
• v.13 no.2
• /
• pp.180-186
• /
• 2022

Background: In occupational studies, it is a known situation that technical and organizational attempts are used to prevent occupational accidents. Especially in the mining sector, if these attempts cannot prevent occupational accidents, personal protective equipment (PPE) becomes a necessity. Thus, in this study, the main objective is to examine the effects of the variables on the use of PPE and identify important factors. Methods: A questionnaire was implemented and structural equation modeling was conducted to ascertain the significant factors affecting the PPE use of mining employees. The model includes the factors that ergonomics, the efficiency of PPE and employee training, and PPE usage habit. Results: The results indicate that ergonomics and employee training have no significant effect (p > 0.05) on the use of PPE. The efficiency of PPE has a statistically meaningful effect (p < 0.05) on the use of PPE. Various variables have been evaluated in previous studies. However, none of them examined the variables simultaneously. Conclusion: The developed model in the study enables to better focus on ergonomics and employee training in the PPE usage. The effectiveness of a PPE makes its use unavoidable. Emphasizing PPE effectiveness in OHS training and even showing them in practice will increase employees' PPE usage. The fact that a PPE with high effectiveness is also ergonomic means that it will be used at high rates by the employee.

• Safety and Health at Work
• /
• v.7 no.3
• /
• pp.225-230
• /
• 2016

Background: This study seeks to examine the relationship and impact of occupational health and safety on employees' organizational commitment in Ghana's mining industry. The study explores occupational health and safety and the different dimensions of organizational commitment. Methods: A cross-sectional survey design was used for this study. The respondents were selected based on simple random sampling. Out of 400 questionnaires administered, 370 were returned (77.3% male and 22.7% female) and used for the study. Correlation and multiple regression analysis were used to determine the relationship and impact between the variables. Results: The findings of this study revealed positive and significant relationship between occupational health and safety management, and affective, normative, and continuance commitment. Additionally, the results revealed the significant impact of occupational health and safety on affective, normative, and continuance commitment. Conclusion: Management within the mining sector of Ghana must recognize the fact that workers who feel healthy and safe in the performance of their duties, develop emotional attachment and have a sense of obligation to their organization and are most likely committed to the organization. Employees do not just become committed to the organization; rather, they expect management to first think about their health and safety needs by instituting good and sound policy measures. Thus, management should invest in the protection of employees' health and safety in organizations.

• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.3
• /
• pp.581-590
• /
• 2024

This study aims to extract key topics through text mining of incident records (incident history, post-incident measures, preventive measures) from construction safety accident case data available on the public data portal. It also seeks to provide fundamental insights contributing to the establishment of manuals for disaster prevention by identifying correlations between these topics. After pre-processing the input data, we used the LDA-based topic modeling technique to derive the main topics. Consequently, we obtained five topics related to incident history, and four topics each related to post-incident measures and preventive measures. Although no dominant patterns emerged from the topic pattern analysis, the study holds significance as it provides quantitative information on the follow-up actions related to the incident history, thereby suggesting practical implications for the establishment of a preventive decision-making system through the linkage between accident history and subsequent measures for reccurrence prevention.

• Geomechanics and Engineering
• /
• v.23 no.1
• /
• pp.51-59
• /
• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• Journal of the Korean Society of Safety
• /
• v.23 no.6
• /
• pp.51-56
• /
• 2008

As RFID/USN technology is used in the latest industry trend, the information analysis paradigm shifts to intelligence service environment. The intelligent service includes autonomic operation, which select activity by defining itself to the status of industry facilities. Furthermore, information analysis based on IT used to frequently data mining for detecting the meaning information and deriving new pattern. This paper suggest self-classifying of context-aware by applying data mining in gas facilities for serving the intelligent gas safety management. We modify data algorithm for fitting the domain of gas safety, construct context-aware model by using the proposed algorithm, and demonstrate our method. As the accuracy of our model is improved over 90%, the our approach can apply to intelligent gas safety management based on RFID/USN environments.

• Safety and Health at Work
• /
• v.10 no.4
• /
• pp.461-469
• /
• 2019

Background: Collisions involving workers and mobile machines continue to be a major concern in underground coal mines. Over the last 30 years, these collisions have resulted in numerous injuries and fatalities. Recently, the Mine Safety and Health Administration (MSHA) proposed a rule that would require mines to equip mobile machines with proximity detection systems (PDSs) (systems designed for automated collision avoidance). Even though this regulation has not been enacted, some mines have installed PDSs on their scoops and hauling machines. However, early implementation of PDSs has introduced a variety of safety concerns. Past findings show that workers' trust can affect technology integration and influence unsafe use of automated technologies. Methods: Using a mixed-methods approach, the present study explores the effect that factors such as mine of employment, age, experience, and system type have on workers' trust in PDSs for mobile machines. The study also explores how workers are trained on PDSs and how this training influences trust. Results: The study resulted in three major findings. First, the mine of employment had a significant influence on workers' trust in mobile PDSs. Second, hands-on and classroom training was the most common types of training. Finally, over 70% of workers are trained on the system by the mine compared with 36% trained by the system manufacturer. Conclusion: The influence of workers' mine of employment on trust in PDSs may indicate that practitioners and researchers may need to give the organizational and physical characteristics of each mine careful consideration to ensure safe integration of automated systems.

• Journal of Korean Association for Spatial Structures
• /
• v.21 no.3
• /
• pp.85-92
• /
• 2021

The purpose of this paper is to understand the key factors for efficient maintenance of rapidly aging facilities. Therefore, the safety inspection/diagnosis reports accumulated in the unstructured data were collected and preprocessed. Then, the analysis was performed using a text mining analysis method. The derived vulnerabilities of tunnel facilities can be used as elements of inspections that take into account the characteristics of individual facilities during regular inspections and daily inspections in the short term. In addition, if detailed specification information and other inspection results(safety, durability, and ease of use) are used for analysis, it provides a stepping stone for supporting preemptive maintenance decision-making in the long term.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2022.04a
• /
• pp.39-40
• /
• 2022

The use of asbestos has been completely prohibited in Korea since 2015. Therefore, nationally, the asbestos demolitions in the building are actively underway. In the process of demolishing asbestos, scattering dust occurs, which poses a risk to human body. These dusts causes fatal disease, and especially there is an increasing concern of safety about construction workers and building users. Until this day, however, only few researches have been conducted on asbestos demolishing process. Accordingly, it is necessary to analyze key factors and to develop a safety prediction model for workers. This study is an early stage of building quantified DB, and aims to actualize the safety problems of asbestos demolishing process using text mining method.