Equipment Accidents Research Articles

Application of 360 Camera Technology and Excavator Operator Workload at a Nickel Ore Mine and Its Implication for Work Accident Rates Using the Nasa-TLX Method

Indonesia, as one of the largest nickel producers in the world, has around 90% of nickel reserves spread across various regions, such as Central Sulawesi, South Sulawesi, Southeast Sulawesi, and North Maluku. Even though demand for nickel continues to increase, a severe problem that needs attention is the rate of work accidents in mining fields. Most heavy equipment accidents that occur are caused by operator negligence while operating. This negligence can occur when operators are in a hurry, make mistakes while using heavy equipment, or do not have proper work time management. This research aims to analyze the impact of 360-degree camera technology on excavator operators in nickel ore mines on work accident rates and operator workload. The case study was carried out at PT Rifky and Raisha Anursyah using the NASA-TLX method to measure workload. In contrast, the number of accidents that occurred to each operator within one month was used to measure work accidents. The 360 camera technology provides a comprehensive view of the work environment, allowing operators to monitor the surrounding area better and reduce blind spots. The research results show that applying this technology can reduce the risk of work accidents and increase the work efficiency of excavator operators. With better monitoring, operators can identify potential hazards earlier and reduce the risk of accidents. Workload evaluation using NASA-TLX shows a decrease in operator workload after implementing 360 camera technology. This research provides strategic recommendations for workload management and implementing safety technology in the mining industry.

The relationship between freight train length and the risk of derailment.

In recent years, longer and heavier trains have become more common, primarily driven by efficiency and cost-saving measures in the railroad industry. Regulation of train length is currently under consideration in the United States at both the federal and state levels, because of concerns that longer trains may have a higher risk of derailment, but the relationship between train length and risk of derailment is not yet well understood. In this study, we use data on freight train accidents during the 2013-2022 period from the Federal Railroad Administration (FRA) Rail Equipment Accident and Highway-Rail Grade Crossing Accident databases to estimate the relationship between freight train length and the risk of derailment. We determine that longer trains do have a greater risk of derailment. Based on our analysis, running 100-car trains is associated with 1.11 (95% confidence interval: 1.10-1.12) times the derailment odds of running 50-car trains (or a 11% increase), even accounting for the fact that only half as many 100-car trains would need to run. For 200-car trains, the odds increase by 24% (odds ratio 1.24, 95% confidence interval: 1.20-1.28), again accounting for the need for fewer trains. Understanding derailment risk is an important component for evaluating the overall safety of the rail system and for the future development and regulation of freight rail transportation. Given the limitations of the current data on freight train length, this study provides an important step toward such an understanding.

Railway accident causation prediction with improved transformer model based on lexical information and contextual relationships

The railway system is a prime example of a safety-critical system. Predicting the causes of railway accidents holds immense significance in enhancing railway transportation safety. Previous approaches to railway causation analysis have encountered huge challenges regarding data processing and analytical capabilities. To address this concern, this paper proposes an innovative deep model framework based on the Transformer architecture that utilizes historical data on railway equipment accidents to predict the causes behind such incidents. Firstly, this paper proposes the utilization of Convolutional Block Attention in the domain of text processing, serving as a lexical encoder to augment word semantics acquisition in accident texts. Subsequently, in order to address the deficiency of traditional Transformers that lack positional representation information, we propose incorporating a BiGRU (Bidirectional Gated Recurrent Unit) as a contextual positional information encoder to capture contextual positional information in railway accident data effectively. Finally, considering that accident data reports are discrete tabular data, this study suggests employing cue word techniques for preprocessing accident data to alleviate the model's learning burden. We applied the proposed model to the FRA (Federal Railroad Administration) dataset. The results demonstrate that our model surpasses the current state-of-the-art language models, exhibiting superior performance compared to the optimal model with a notable improvement of 3.56%, 0.42%, and 0.76% in Precision, Recall, and F1-score, respectively. Furthermore, our model accurately predicts accident categories prone to misjudgment even when trained on limited data, outperforming existing language models. The study findings will contribute to the prevention and management of railway accidents.

Adaptive fast Walsh-Hadamard transform for magnetic flux leakage signal of broken wire damage extraction under noise background

ABSTRACT Steel wire rope usually works in harsh environments, making it prone to damage during frequent use. Magnetic flux leakage testing is an important way of non-destructive testing, preventing some major accidents of hoist equipment by identifying the damage to steel wire ropes. Whereas, the harsh environment usually generates noise and results in difficulty in extracting the damage features of the magnetic flux leakage signal, which makes it hard to identify the damage. The fast Walsh-Hadamard transform is widely used in signal processing. The denoising effect depends closely on the transform coefficients. If the transformation coefficients can be adaptively retained, better denoising effects can be achieved. Therefore, we propose the adaptive fast Walsh-Hadamard transform to extract the magnetic flux leakage signal of steel wire rope under noise background. Using the cross-correlation co efficient and the similarity of the greyscale histogram as the indexes, the Fast Walsh-Hadamard transform combines the adaptive particle swarm optimisation to adaptively retain the optimal transformation coefficient and then gets the optimal denoising signal. Meanwhile, compared to wavelet denoising methods, the adaptive fast Walsh-Hadamard transform can effectively improve denoising performance in peak-to-peak reductivity and can be successfully used in steel wire rope damage extraction.

Снижение пульсаций давления газа в линии всасывания поршневого компрессора при использовании дроссельных шайб

This article discusses the problem of combating pressure fluctuations in the suction line of piston compressors. As you know, incorrect calculation of communications can lead to accidents of compressor equipment. Therefore, special attention must be paid to the layout of pipelines and equipment, while avoiding resonance phenomena. One way to combat pressure pulsations in the suction line is to install diaphragms. This method is the cheapest and easiest to implement, especially for compressors already in operation. The experimental studies carried out confirmed the known data that the area of the diaphragm opening should be four times smaller than the diameter of the pipeline. At the same time, a threefold reduction in the amplitude of pressure fluctuations is achieved. Installation of a diaphragm design with parameters close to the recommended ones is possible anywhere in the suction line, since the change in amplitude at different pressure from the suction valves does not exceed 5...7 %. When installing a diaphragm with dimensions different from those recommended, it is necessary to install it closer to the suction valve.

Leveraging Technology in Advancing Construction Workers Safety

Construction worker safety is a top priority in the construction business. It refers to the procedures, protocols, and practises put in place to ensure the safety and physical well-being of construction workers. Because of the presence of heavy gear, high work zones, and possible exposure to different dangers such as falls, equipment accidents, toxic chemicals, and structure collapses, construction sites are inherently hazardous settings. Safety for construction workers cannot be stressed. Construction safety is a guideline that construction safety managers follow and implement. It is the consequence of proper equipment use, worker safety, frequent site inspections, and risk assessments. Compliance with regional safety and health requirements is a critical component of construction safety. In many nations, ensuring worker safety is not just a moral imperative, but also a legal necessity. Construction businesses must offer a safe working environment and follow safety regulations and guidelines to avoid accidents, injuries, and fatalities. To reduce the occurrence of construction accidents and enhance the safety record of construction projects, dangerous elements must be identified by monitoring construction workers' behaviours. The aim of this study is to look at the implementation and adoption of technologies for construction workers safety as well as the opinions and perspectives of the construction industry towards these technologies.

Analysis on the Causes and Countermeasures of Mechanical and Electrical Transportation Accidents in Coal Mines

There are many types of mechanical and electrical equipment involved in current coal mine mechanical and electrical transportation, and many workers are not familiar with the operation of mechanical and electrical equipment. Improper operation often leads to operational failures of coal mine mechanical and electrical equipment. The important reason for this phenomenon is that the transportation management of underground mechanical and electrical equipment is not in place, and there may also be incorrect and unreasonable management methods. This situation will directly hinder coal mining work and exacerbate the threat to the safety of workers' lives. Therefore, coal mining enterprises must develop good management measures for underground mechanical and electrical equipment based on the current operating status of the equipment and the company's own development status, reduce operational accidents of mechanical and electrical equipment, and improve normal and stable production in the coal mine.

Time-Series Transfer Learning: An Early Stage Imbalance Fault Detection Method Based on Feature Enhancement and Improved Support Vector Data Description

Early stage fault detection plays a pivotal role in Industrial equipment accidents avoidance and scientific maintenance. While limited by the complex operation background, its application encounters with the conundrum of fault feature indistinctness. To address the challenge, a time-series transfer learning (TSTL) method is proposed, which contains two phases: first, early stage series are transferred to their corresponding serious stage for fault feature enhancement. Moreover, due to the improvement of model structure and loss function, the limitation of mismatched working condition is well-weaken. Second, a transferred fault mode recognition model is trained by using transferred normal series that provides a novel solution for data imbalance. Finally, the TSTL method is verified by actual vibration datasets of power pole tower bolts. Its superiority in feature transfer and fault detection is confirmed by several groups of comparative experiments and results demonstrate TSTL outperforms mainstream methods.

Efficient safety management plan for industrial accident prevention of hazardous machinery: Focus on safety certification system and regulations in South Korea

The “4th industrial revolution” is accelerating changes in technology, industry, and machinery, and the “Internet of everything” (IoE) requires comprehensive integration of people and machines. Despite the development of these technologies, fatal accidents continue to occur due to malfunctions of dangerous machinery, so the importance of the safety certification system is increasing, but there are few objective analysis data. In this study, the necessity of a safety certification system was confirmed by analyzing the effect of the safety certification system on the prevention effect of industrial accidents in three methods. Based on these analysis results, the industrial accident prevention effect of the current safety certification system and necessary supplementary tasks were derived. Safety certification systems for more than 30 machines and equipment are in operation in South Korea. In this research, the press, crane, catapult, and lift machines most commonly used in industrial fields were analyzed. This study was conducted in five steps: a safety certification system operation status investigation, a survey and interviews, an analysis of dangerous machinery and equipment accidents, focus group interviews, and study of the direction of safety certification systems in consideration of recent IoE developments. As a result of the analysis, various opinions were presented on the safety certification system by subject, and it was found that it was necessary to prepare supplementary measures for the advancement of the safety certification system advancement, expand its field applicability, and improve the efficiency of safety certification.

건설공사 굴착기 근접 작업자의 불안전행동 기반 휴먼에러 연구

According to the latest data released by the Ministry of Employment and Labor, 259 (18.9%) of the 1,371 construction accident deaths between 2018 and 2020 were caused by construction machinery or equipment. In particular, excavators cause the most deaths among construction equipment, and are classified as the most dangerous equipment in previous studies on equipment risk index.
 Serious accidents of excavators mainly occur in the form of a crush or a collision with a nearby worker while the equipment is reversing or rotating the boom. In the meantime, studies for preventing excavator accidents have been conducted several times, but the trend is focusing on physical safety measures such as safety devices and alarms, or research for improving the safety capabilities of equipment operators. However, as most of the equipment accidents are caused by human factors, it is judged that research on this should be conducted in parallel.
 Accordingly, this study attempted to analyze why workers who were working around excavators were suffering from accidents due to unsafe behavior around dangerous equipment like it. To this end, we focused on the ‘factors’ and ‘causes’ of Human Error, and conducted a survey focusing on ‘factors’ as 4M aspects and ‘causes’ with James Reason’s Generic Error Modeling System (GEMS). The survey was analyzed using the SPSS statistical program. As a result of the study, the 'factors' of human error related to workers around excavators were analyzed as human error factors and job factors. and the 'Cause' of human error were identified as Slip, Lapse, Knowledge-based mistake, Situational violations. In order to maintain the attention of workers around excavator, some improvement measures like enhancing the effectiveness of safety education were suggested in this study.

Literature Review: Analysis of Potential Work Accidents in Construction Projects Using the Hazard Identification, Risk Assessment, and Risk Control Method

<p>Along with advances in science and technology, the development of the building sector is also increasing. Multi-storey buildings are an alternative to meet the needs of big cities with very limited land. The rapid development of construction project development, in addition to providing benefits, can also cause the risk of accidents that can cause disruption or cessation of project work activities. The literature review aims to review the potential for work accidents and risk assessments on construction projects. A literature review is based on issues, methodologies, similarities and research proposals. Based on the result of 8 studies, it was found that the high-risk category is the risk of falling from a height, workers buried by avalanches during excavation work, the risk of being hit by material, and being electrocuted during excavation work with tools and equipment accidents. Based on the identification and assessment, it was found that the work of the upper structure has more risk, and the average risk index is greater than that of the lower structure.</p>

Analysis and Discussion on Tension of Long Transport Belt

The technical field of belt tensioning force studied in this paper, in particular, relates to a hydraulic belt tensioning device, including a base, a hydraulic system and a rail fixed on the base, and a tail wheel trolley sliding on the rail; This device can provide a large tension to the tail wheel of the conveyor belt to meet the tension required by the long conveyor belt. At the same time, it can automatically adjust the tension to the tail wheel of the conveyor belt according to the tension of the conveyor belt to realize the dynamic tension control of the conveyor belt; The device prevents belt deviation and material leakage, reduces labor intensity of workers, avoids equipment accidents, and improves industrial production capacity.

Software Defect Fault Intelligent Location and Identification Method Based on Data Mining

With the advancement of the times, computer technology is also constantly improving, and people's requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%.

Fast electrothermal coupling calculation method for supporting digital twin construction of electrical equipment

AbstractThe failure of electrical equipment directly or indirectly caused by overheating has become one of the main reasons for equipment accidents. The real‐time condition monitoring method of electrical equipment based on digital twin (DT) has received extensive attention and is considered as a technology with great engineering values and excellent application prospects. However, the current calculation of DT mostly relies on the traditional finite element method (CFEM). This method becomes less computationally efficient as the size of the DT increases, especially for electrical equipment with high complexity. It is difficult to meet the requirements real‐time calculation in DT. Therefore, starting from the algorithm optimization and parallel architecture, based on the weighted residual method and stabilised conforming nodal integration, a novel discrete method of electrothermal coupling equation is proposed and the data storage structure of the algorithm from the bottom layer is redesigned, and the corresponding GPU and multi‐core CPU parallel framework are proposed. Finally, taking the high voltage bushing as an example, the correctness of the method in this paper is verified by the CFEM code and commercial software ABAQUS. Under the same grid and accuracy requirement, the calculation time is shortened by at least five times than ABAQUS. And the method is easy to extend to other types of multi‐physics calculations.

Investigation of the fire danger of the main oil pumping station GNPS-1 “Taishet” by LLC “Transneft-Vostok”

Statistical data and equipment parameters are used to analyze accidents caused by the termination of the receipt of electricity and heat, technical failures, control failures and human errors. The main reasons for the damage of technological equipment are determined on the example of the head oil pumping station GNPS-1 “Taishet” in connection with fire propagation scenarios; the ways of solving the problems are described. Exceeding the design loads while maintaining the design strength of the equipment causes excessive mechanical effects. An example of the mechanical action is an increase in operating pressure in technological equipment. Violation of the integrity of the structural material of pipelines and technological devices occurs as a result of electrochemical corrosion. In the presence of moisture on the surface of structures, a film containing dissolved air and atmospheric impurities develops. The use of corrosion-resistant materials and the insulation of the inner and outer surfaces of pipelines with anticorrosive coatings increase their reliability. The most dangerous scenarios of accidents, fires, and explosions are accidents at three sites: in the tank farm, at the main oil pumping and back-up pumping stations. The scenarios for the development of an accident of the technological equipment and pipeline sections will allow us to determine the distribution of fire risks on the territory of the facility and beyond its borders, including assessing the magnitude of fire risks in order to develop measures to reduce it.

타워크레인 전문신호수의 효율적 운영체계에 대한 연구

Recently, in the case of domestic construction sites, the ratio of construction equipment to construction manpower is increasing due to high-rise and large-scale buildings. As a result, the death toll from construction machinery and equipment accidents accounts for more than 20% of all deaths in the construction industry. Accordingly, from 2017, as a measure to strengthen safety management for tower cranes, the installation and dismantling team registration system was introduced and the right to stop work was strengthened, the professional qualification system was introduced (tower crane installation and dismantling workers), the collision prevention system became mandatory, and the installation, dismantling, and climbing work were recorded. the age limit of old cranes (restriction of use in principle for more than 20 years), and mandatory non-destructive inspection are added and managed, but most of them are limited to the management and technical fields of equipment aspects of tower cranes and have been strengthened. It seems that there are very few things. As with the results of the analysis of disaster cases of tower cranes in the past, the role of a dedicated signal operator is important when lifting weights, but anyone can play a role as a dedicated signal operator signal operator if they only receive 8 hours of special safety training, so it is urgent to supplement this. In this study, based on the review of previous research results and the analysis of disaster cases that occurred in the past 10 years (2010~2019) of tower cranes by the Korea Occupational Safety and Health Agency, we reviewed the signal management system in advanced countries such as the United States and the United Kingdom. An interview was conducted with a tower crane official (manager of a professional construction company, tower crane operator) and a signal officer, and direct and indirect problems were identified. Based on this, an improvement plan was derived by conducting a survey, and the AHP (Analytic Hierarchy Process) analysis method was used to derive the priority of the improvement plans. As a result of the study, the management system for dedicated signalman should be nationally reorganized and built and managed by improving the dedicated signalman system laws and systems. The result was that As in the results of this study, it is expected that tower crane accidents will not occur any more by implementing the improvement of laws and systems for tower crane dedicated signalmen.

Use of Virtual Reality to Increase Awareness of Line-of-Sight Hazards around Industrial Equipment

Impaired operator line of sight has been implicated in several pedestrian–equipment accidents and fatalities in the mining industry. Existing training methods for conveying visibility information lack worker engagement and may be insufficient to capture the dynamic, three-dimensional nature of blind spots around industrial equipment. The present study utilized a custom virtual reality experience intended to shift the way in which visibility information is presented. Visibility knowledge, confidence levels and safe pedestrian behaviors around the load-haul-dump vehicle were examined among participants in control and experimental (virtual reality and conventional training) groups (n = 72). Results demonstrate that the virtual reality intervention was not effective for increasing visibility knowledge and safe pedestrian behaviors relative to controls, although the performances of the virtual reality and conventional training groups were comparable. A discrepancy was identified in the perceived versus actual visibility knowledge and safe pedestrian behaviors at the rear of the load-haul-dump vehicle among the virtual reality training group. The findings suggest poor knowledge transfer between the three-dimensional virtual reality experience and the two-dimensional visibility plot used. The work also speaks to the importance of emphasizing rear-facing visibility deficits around machinery within industry safety training materials.

Diagnosing Potentially Abnormal Attribute of Power Transformers Method

Design Method: In this paper, the program integrates those diagnostic methods from the Big data, the ANSI/IEEE C57.104 specification, and the Key gas to develop a kind of diagnostic method in power transformer. Their main diagnostic element is the insulating oil dissolved gas, which is integrated through the "correlation coefficient" and "classical detection and estimation theory". To develop a novel method diagnoses the latent abnormality attribute of the power transformer. The new method is accomplished through clever loop control, which has been validated by repeated and extensive data testing. This method is superior to the existing traditional diagnosis method in type of latent abnormality of diagnose, and has an accuracy of 90% under the verification those actual cases obtained from Research Institute of Taiwan Electric Power Company. This method is based on the MATLAB application software to execute all steps. In addition to being easy to operate and displaying the results of test in text, it not only improves the accuracy of the diagnosis of the latent abnormal attribute inside the power transformer, but also prevents the accident of blackout equipment and affects the power supply. It can to say, it is a powerful tool for electrical equipment maintenance technicians to detect.
 Design Purpose: Based on this diagnostic method to improve the accuracy of the diagnosis of the latent abnormal attribute inside the power transformer by MATLAB application software.
 Design Effectiveness: The program has been tested from some actual cases to improve the accuracy of diagnosis is been risen 90% up.

The FEM Analysis of the Height Protection Equipment of the Crane

According to the statistical data of special equipment accidents, and in accordance with the requirements of the "double limit" policy, the height limit device of hoisting machinery includes a variety of types, focusing on the two representative types of fire interrupter device and mechanical drive height limit. By establishing a CAD model of the corresponding device mechanism structure, using the finite element method, simulating the movement of the device mechanism, analyzing the force of the structure, and obtaining relevant information, the cause and mechanism of the device failure can be obtained, and then from the design, manufacture, installation and the use of the device. Reliability improvement and enhancement are carried out in multiple links such as inspection.

Software Defect Fault Intelligent Location and Identification Method Based on Data Mining

With the advancement of the times, computer technology is also constantly improving, and people’s requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%.