Search Results (61)

Rolling bearing fault diagnosis in electric hoists faces significant challenges due to heavy noise and complex vibration interferences, which obscure fault signatures and hinder conventional demodulation methods. While existing techniques like the Teager–Kaiser energy operator (TKEO) and its variants (e.g., HO-AEO, SD-AEO) offer filterless demodulation, their susceptibility to noise and dependency on preprocessing limit diagnostic accuracy. This study proposes a Multi-resolution Higher-order Symmetric Analytic Energy Operator (MHSAEO) to address these limitations. The MHSAEO integrates three innovations: (1) dynamic non-adjacent sampling to suppress stochastic errors, (2) AM-FM dual demodulation via symmetric energy orthogonality, and (3) adaptive spectral mining for full-band feature extraction. Experimental validation on a 10-ton electric hoist bearing system demonstrates that the MHSAEO achieves signal-to-noise ratio improvements (SNRIs) of −3.83 dB (outer race faults) and −2.12 dB (inner race faults), successfully identifying the characteristic fault frequencies of both inner (145.9 Hz) and outer races in electric hoist bearings with 2nd–5th harmonics. Compared to traditional methods, the MHSAEO reduces computational time by 30.1 × (0.0328 s vs. 0.9872 s) without requiring preprocessing. The results confirm its superior anti-interference capability and real-time performance over the TKEO, HO-AEO, and hybrid denoising–TKEO approaches. Full article

A hoisting machine is one of the main components of an underground mine process line. The drive systems currently used in these machines are based on direct current, synchronous, or induction (AC) motors. Power electronic converters are used to power and control the speed of the motor, the type and function of which depend on the type of motor. Choosing the right motor is the most important part of the design process. The decision must be based on an evaluation of technical and economic parameters. This article describes the most popular types of hoisting machine drive systems. Four motors that could potentially be used to build a hoisting machine with the assumed parameters were analysed. The selection of the motor was made based on the analyses carried out, and the implementation of the investment and commissioning of the machine with the selected motor confirmed the validity of this choice. The technical–economic analysis of the motor selection for this hoisting machine made it possible to determine how to choose a motor for a specific shaft hoist. The information contained in this article can serve as a guideline during in-depth analyses of motor selection for modernised or constructed hoisting machines due to the possibility of generalising its conclusions. Full article

This study explores the design and construction methods for auxiliary workings for the deepening of Shaft II at the Borynia Mine. The shaft, an essential intake structure for personnel and material transport, is being extended from 980 m to 1150 m to provide access to a new mining level at 1120 m. Given the challenging geological and operational conditions, a top-to-bottom deepening method was adopted, with excavation from a sub-level accessed via an auxiliary incline. The study details the planning and implementation of key auxiliary workings, including hoisting machine chamber and technological shaft inset. A comprehensive geotechnical analysis was conducted to assess rock mass properties, classify geological formations, and estimate mechanical parameters affecting excavation stability. The support system design was carried out using both analytical and numerical methods, ensuring safe and efficient construction. The applied primary and secondary support structures have successfully maintained excavation stability. The findings demonstrate the reliability of the adopted engineering solutions and their applicability in deep mining environments. Full article

Hyper-relational knowledge graphs can enhance the intelligence, efficiency, and reliability of industrial production by enabling equipment collaboration and optimizing supply chains. However, the construction of knowledge graphs in industrial fields faces significant challenges due to the complexity of hyper-relational data, the sparsity of industrial datasets, and limitations in existing link prediction methods, which struggle to capture the nuanced relationships and qualifiers often present in industrial scenarios. This paper proposes the HyLinker model, designed to improve the representation of entities and relations through modular components, including an entity neighbor aggregator, a relation qualifier aggregator, MoE-LSTM (Mixture of Experts Long Short-Term Memory), and a convolutional bidirectional interaction module. Experimental results demonstrate that the proposed method performs well on both public datasets and a self-constructed hoisting machine dataset. In the Mine Hoist Super-Relationship Dataset (MHSD-100), HyLinker outperforms the latest models, with improvements of 0.142 in MRR (Mean Reciprocal Rank) and 0.156 in Hit@1 (Hit Rate at Rank 1), effectively addressing the knowledge graph completion problem for hoisting machines and providing more accurate information for equipment maintenance and fault prediction. These results demonstrate the potential of HyLinker in overcoming current challenges and advancing the application of hyper-relational knowledge graphs in industrial contexts. Full article

The rapid development of artificial intelligence technology is driving the intelligentization process across various fields, particularly in knowledge graph construction, where significant achievements have been made. However, research on hyper-relational knowledge graphs in the industrial domain remains relatively weak. Traditional construction methods suffer from low automation, high cost, and poor reproducibility and portability. To address these challenges, this paper proposes an optimized construction process for a hyper-relational knowledge graph for mine hoist faults based on large language models. This process leverages the strengths of large language models and the logical connections of fault knowledge, employing GPT’s powerful reasoning abilities. A combined strategy of template-based and template-free prompts is designed to generate fault entities and relationships. To address potential data incompleteness caused by prompt engineering, link prediction is used to optimize the initial data generated by GPT o1-preview. We integrated the graph’s topological structure with domain-specific logical rules and applied the Variational EM algorithm for alternating optimization while also incorporating text embeddings to comprehensively enhance data optimization. Experimental results show that compared to the unoptimized MHSD, the optimized MHSD achieved a 0.008 improvement in MRR. Additionally, compared to the latest KICGPT, the optimized MHSD showed a 0.002 improvement in MRR. Finally, the optimized data were successfully imported into Neo4j for visualization. Full article

Shafts play a key role in the operation of mining plants. They connect underground excavations with the surface and provide the ability to transport people, equipment, and raw materials. The nature of the dynamic interaction of a conveyance moving at a significant speed along deformed guide rails is complex, and the method of assessing the interaction of hoisting conveyances with shaft steelwork, despite ongoing research, still requires further understanding and improvement. Misalignments of the guide rails and conveyance movements transverse to the shaft axis induce impact (guiding) forces, which are the key design parameters of shaft steelwork. The reliable assessment of guiding forces allows the design of safe and economical steelworks and the assessment of their structural safety during operation under deformations and corrosive deterioration. Determining the value of guiding forces requires their field measurements or the use of approximate empirical formulas. Both methods have their limitations—measurement is expensive and interferes with normal shaft operation, while empirical formulas are subject to high error due to the lack of consideration of many structural details specific to each shaft that significantly affect the behavior of the system. This study presents a new method for using a relatively simple-to-implement measurement of hoisting conveyance acceleration to assess guiding forces. A finite element model of the skip and steelwork was built, and simulations of the conveyance interaction with the structure were carried out. A strong relationship between the sliding plate’s impact point location and the guiding force was found. Extreme values of the guiding force were observed in the vicinity of the bunton connection. The study showed that reducing the skip load mass does not affect the force value. Simplified methods of calculating the moments of inertia of the hoisting conveyance significantly overestimate the code-based values of the guiding forces. The presented method considers the actual stiffness and mass distribution of hoisting conveyance and, therefore, allows for a more accurate estimation of the guiding forces and the transport of larger loads. This data-driven approach allows for the continuous monitoring of the guiding forces, the adjustments of the hoisting parameters, the rational planning of repairs, and a reduction in the replacement of corroded shaft steelwork. Full article

The evaluation and prediction of reliability and testability of mining machinery and equipment are crucial, as advancements in mining technology have increased the importance of ensuring the safety of both the technological process and human life. This study focuses on developing a reliability model to analyze the controllability of mining equipment. The model, which examines the reliability of a mine cargo-passenger hoist, utilizes statistical methods to assess failures and diagnostic controlled parameters. It is represented as a transition graph and is supported by a system of equations. This model enables the estimation of the reliability of equipment components and the equipment as a whole through a diagnostic system designed for monitoring and controlling mining equipment. A mathematical and logical model is proposed to calculate availability and downtime coefficients for different structures within the mining equipment system. This analysis considers the probability of failure-free operation of the lifting unit based on the structural scheme, with additional redundancy for elements with lower reliability. The availability factor of the equipment for monitoring and controlling the mine hoisting plant is studied for various placements of diagnostic systems. Additionally, a logistic concept is introduced for organizing preventive maintenance systems and reducing equipment recovery time by optimizing spare parts, integrating them into strategies aimed at enhancing the reliability of mine hoisting plants. Full article

Renewable energy generation methods such as wind power and photovoltaic power have problems of randomness, intermittency, and volatility. Gravity energy storage technology can realize the stable and controllable conversion of gravity potential energy and electric energy by lifting and lowering heavy loads. The hoisting system is an important component of a gravity energy storage system, and its lifting capacity and speed seriously restrict its energy storage capacity, energy conversion efficiency, and operational safety and reliability. In this paper, a design method for a multi-rope friction hoisting system of a vertical shaft gravity energy storage system is proposed. The parameter design and calculation of the hoisting rope, balance rope, and friction wheel of the friction hoisting system under typical conditions were carried out. The static and dynamic anti-slip capabilities of the friction hoisting system under the typical condition were explored. The results show that the maximum acceleration and deceleration speed of the compacted strand wire rope scheme is the largest, and the lifting and lowering time is the shortest. The maximum acceleration and deceleration speed of the triangular strand wire rope scheme is the lowest, and the lifting and lowering time is the longest. The dynamic tension of the hoisting rope at the heavy-load end is positively correlated with the acceleration, and the maximum value occurs in the accelerated lifting stage and decelerated lowering stage of the heavy load. The static anti-slip safety factor between the hoisting rope and the friction lining and the specific pressure between the hoisting rope and the friction lining comply with the requirements of China’s Safety Regulations for Coal Mines. The dynamic anti-slip safety factor of the hoisting system under different rope selection schemes is greater than the minimum value of 1.25 stipulated in the Safety Regulations for Metal and Nonmetal Mines. The research results are of great significance for the safety, reliability, and stable and efficient energy storage of a gravity energy storage system. Full article

The development of the open-pit mining industry has set higher performance standards for mining electric shovels. Addressing issues such as low efficiency, high energy consumption, and high failure rates in working mining electric shovel devices, this paper comprehensively considers bulk mechanics, structural mechanics, and dynamics to conduct a multidisciplinary, collaborative design optimization for electric shovels by introducing the BLISCO method, which is based on an approximated model, into the structural-optimization design process of working electric shovel devices, aiming to enhance the overall performance of electric shovels. Firstly, a dynamic model of an electric shovel is established to analyze the hoist force and crowd force during the excavation process, and an accurate load input for the dynamic analysis is provided through the bulk material mechanics model. Additionally, to ensure that the stiffness of the boom meets the requirements, the maximum stress at the most critical position of the optimized boom is considered. Subsequently, the design variables are screened through experimental design, and an approximate model is established. Focusing on the hoist force, crowd force, maximum stress at the critical position of the boom, and the angle between the dipper arm and the wire rope, a mathematical model is constructed and optimized using a two-level integrated system co-optimization framework based on an approximate model (BLISCO-AM), followed by a simulation. Finally, a test bench for the electric shovel working device is constructed to compare pre- and post-optimization performance. Experimental results show that through the optimized design, the hoist force and crowd force required in a single excavation process are reduced by 6% and 8.48%, respectively, and the maximum angle between the wire rope and the dipper arm is increased by 4%, significantly improving excavation efficiency while ensuring the safety and reliability of the equipment. Full article

Investigating the influence of varying shaft steelwork stiffness on the stability of horizontal mass displacements, which are crucial elements of a conveyance-shaft steelwork system, is a significant step in evaluating the risk of parametric vibrations in steel constructions. While the Rayleigh method is limited to the first approximation in the solution to this analysis, it still provides valuable insights. Our examination indicates that the impact of a varying shaft steelwork system may not be noticeable in practical applications. This is a significant finding, as it suggests that the impact of varying stiffness in real working objects may be ignored, because the increase in the parametric resonance effects is negligible. This underscores the importance of our research in understanding the stability of steel constructions. This research, which involves theoretical analysis, simplifies the dynamic analysis of the conveyance-shaft steelwork system’s behavior. The result of the performed analysis is a valuable equation for predicting stable work in real hoist installations. Full article

In industrial plants with dynamically varying load profiles, the problem of increased charges for over-contracted reactive power consumption is very common. To eliminate these charges, reactive power compensation systems are used. This article presents a case study of an automatic reactive power compensation system in an underground mine where a thyristor hoisting machine is used. To reduce the higher current harmonics of the hoisting machine and compensate for the reactive power of the PCC (Point of Common Coupling), the main reactive power automatic compensation system and an ASVG (Advanced Static Var Generator) with a nonstandard control loop were used. The article considers aspects of the operation of the ASVG, locally with the hoisting machine, and also as a master-controlled device that is part of the reactive power automatic compensation system. This part of the article is based on measurements taken in a mine. The reactive power automatic compensation system considered in this article has been successfully implemented, improving PQ (Power Quality) and eliminating additional overcompensation charges. Full article

The work analyzes the performance assurance of mine hoisting machines, including the problem of the quality of performance of the functions. The quality of functioning allows evaluation of a set of properties of the process of lifting loads, designed to meet the given requirements in accordance with the purpose and evaluated performance indicators. In this case, the quality of the function depends not only on the elements that worked properly or failed during system functioning but also on the moments involving certain changes in the states of the system. The considered system of power supply of mine hoisting installations is rather complex with respect to reliability. The proposed approach allows this rather complex system to lead in terms of the form of a serial connection of elements, allowing for determining the influence of the functioning of its subsystems and electrical equipment on the technological process of cargo lifting in a coal mine. The presented mathematical concept of increasing the reliability and failure-free operation of mine hoisting plants with the help of the developed mathematical model of the mine hoisting plant allowed studying the reliability indicators of the hoisting plant operation and reserving the equipment most effectively to increase reliability. The determination of coupling coefficients in this study made it possible to analyze the impact of the reliability of electrical equipment and power supply systems on the operation of technological machines to improve the reliability of mining equipment and the efficiency of technical systems of mining equipment. Full article

The issues of the evaluation and prediction of the reliability and testability of mining machinery and equipment are becoming particularly relevant, since the safety of technological processes and human life is reaching a new level of realisation due to changes in mining technology. The work is devoted to the development of a logical model for analysing the controllability of mining equipment. The paper presents a model of reliability of the operation of mining equipment on the example of a mine load and passenger hoist. This generalised model is made in the form of a graph of transitions and supplemented with a system of equations. The model allows for the estimation of the reliability of equipment elements and equipment as a whole. A mathematical and logical model for the calculation of the availability and downtime coefficients of various designs of mining equipment systems is proposed. This model became the basis for the methods to calculate the optimal values of diagnostic depth. At these calculated values, the maximum value of availability factor will be obtained. In this paper, an analytical study was carried out and dependences of the readiness factor of parameters of the investigated system such as the intensity of control of technical systems, intensity of failures, etc., were constructed. The paper proposes a mathematical model to assess the reliability of mine hoisting plants through its integration into the method of improving the reliability of mine hoisting plants. Full article

The primary function of a mine hoist is the transportation of personnel and equipment, serving as a crucial link between underground and surface systems. The proper functioning of key components such as work braking and safety braking is essential for ensuring the safety of both personnel and equipment, thereby playing a critical role in the safe operation of coal mines. As coal mining operations extend to greater depths, they introduce heightened challenges for safe transportation, compounded by increased equipment loss. Consequently, there is a pressing need to enhance safety protocols to safeguard personnel and materials. Traditional maintenance and repair methods, characterized by routine equipment inspections and scheduled downtime, often fall short in addressing emerging issues promptly, leading to production delays and heightened risks for maintenance personnel. This underscores the necessity of adopting predictive maintenance strategies, leveraging digital twin models to anticipate and prevent potential faults in mine hoists. In summary, the implementation of predictive maintenance techniques grounded in digital twin technology represents a proactive and scientifically rigorous approach to ensuring the continued safe operation of mine hoists amidst the evolving challenges of deepening coal mining operations. In this study, we propose the integration of a CNN-LSTM algorithm within a digital twin framework for predicting faults in mine hoist braking systems. Utilizing software such as AMESim 2019 and MATLAB 2016b, we conduct joint simulations of the hoist braking digital twin system. Subsequently, leveraging the simulation model, we establish a fault diagnosis platform for the hoist braking system. Finally, employing the CNN-LSTM network model, we forecast failures in the mine hoist braking system. Experimental findings demonstrate the effectiveness of our proposed algorithm, achieving a prediction accuracy of 95.35%. Comparative analysis against alternative algorithms confirms the superior performance of our approach. Full article

In the mine hoisting system, rigid guide failures and the influence of internal and external airflow intensify vessel transverse vibration, heightening demands on operational safety and equipment reliability. This paper focuses on integrating magnetorheological dampers and disc springs as the roller cage shoe buffer for vibration control, resulting in an innovative buffer device. The structure and magnetic circuit were meticulously designed. Using Maxwell simulation, we analyzed the impact of magnetic circuit parameters—specifically the damping gap and core radius—on the magnetorheological damper. We optimized these parameters through orthogonal testing to enhance damping and vibration reduction. This led to a notable 58% increase in the damper output force. A virtual prototype of the lifting system under actual working conditions was established. A simulation analysis verified the vibration-damping performance of the optimized roller cage shoe. The results indicate that the new roller cage shoes effectively inhibit transverse vibration, surpassing traditional roller cage shoe performance. This is scientifically and practically significant for ensuring safe cage shoe lifting system operation. This paper can provide a crucial theoretical basis for the design of roller cage shoes in ultra-deep mine lifting systems. Full article