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The operating conditions of the drum shearer are very complex, and its ranging arm gear system often suffers from gear scuffing and wear. Gear scuffing is caused by the adhesive wear, which is due to the instantaneous friction and flash temperature of the tooth surface, and the gear meshing power loss is also caused by tooth surface friction. In order to resist tooth scuffing and improve meshing efficiency of the transmission system, an improved semi-analytical tooth surface flash temperature calculation method was used. The tooth flash temperature status under various working conditions were analyzed in detail. Based on the mechanical model of the shearer drum picks, the load condition of the drum was analyzed. Under these load and boundary conditions, the misalignments of each gear pair in the ranging arm were calculated. The tooth surface load distribution was calculated under the gear misalignments, and then the theoretical tooth surface flash temperature and meshing power loss were determined. Next, the tooth micro-geometry was modified to reduce flash temperature and meshing power loss. The flash temperature distribution pattern of the optimized tooth surface was studied under various working conditions, and the meshing power loss was also obtained. Finally, experiments were conducted to verify the effects of the optimized tooth surface on the friction temperature rise and the effectiveness of the modification method. Tooth surface optimization aimed at reducing tooth surface flash temperature can also effectively reduce meshing power loss, which has a significant effect on gear anti-scuffing and energy saving. [ABSTRACT FROM AUTHOR]

The operating conditions of the drum shearer are very complex, and its ranging arm gear system often suffers from gear scuffing and wear. Gear scuffing is caused by the adhesive wear, which is due to the instantaneous friction and flash temperature of the tooth surface, and the gear meshing power loss is also caused by tooth surface friction. In order to resist tooth scuffing and improve meshing efficiency of the transmission system, an improved semi-analytical tooth surface flash temperature calculation method was used. The tooth flash temperature status under various working conditions were analyzed in detail. Based on the mechanical model of the shearer drum picks, the load condition of the drum was analyzed. Under these load and boundary conditions, the misalignments of each gear pair in the ranging arm were calculated. The tooth surface load distribution was calculated under the gear misalignments, and then the theoretical tooth surface flash temperature and meshing power loss were determined. Next, the tooth micro-geometry was modified to reduce flash temperature and meshing power loss. The flash temperature distribution pattern of the optimized tooth surface was studied under various working conditions, and the meshing power loss was also obtained. Finally, experiments were conducted to verify the effects of the optimized tooth surface on the friction temperature rise and the effectiveness of the modification method. Tooth surface optimization aimed at reducing tooth surface flash temperature can also effectively reduce meshing power loss, which has a significant effect on gear anti-scuffing and energy saving.

This paper attempts to apply the resilience concept to the mining sector, especially to mining machinery and production systems. The quantitative analysis method using the linear recovery function has been applied. As the core part of the proposed method, it is assumed that in the mining machinery fleet, the performance function falls to a “zero” value immediately after the occurrence of a failure. Therefore, the resilience calculation process runs through the concept of time to repair and machine maintainability. As a case study for the proposed concept, the operation and failure data of the drum shearer machine in Parvadeh longwall mine in Iran is applied. The data pertains to a coal cutting operation in a whole longwall panel over the period of two years. In total, the calculations encompass over 2600 hours of actual operation and 171.8 hours of repair time, which reveals that the studied shearer has a resilience of 96.7 percent. Along with the case study results, it is confirmed by this paper that resilience as a developing concept could be adequately applied to coal mining systems as a support measure for production assurance and reliability.

Copyright of Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Heilongjiang University of Science & Technology is the property of Journal of Heilongjiang University of Science & Technology Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During operation, the acoustic signal of the drum shearer contains a wealth of information. The monitoring or diagnosis system based on acoustic signal has obvious advantages. However, the signal is challenging to extract and recognize. Therefore, this paper proposes an approach for acoustic signal processing of a shearer based on the parameter optimized variational mode decomposition (VMD) method and a clustering algorithm. First, the particle swarm optimization (PSO) algorithm searched for the best parameter combination of the VMD. According to the results, the approach determined the number of modes and penalty parameters for VMD. Then the improved VMD algorithm decomposed the acoustic signal. It selected the ideal component through the minimum envelope entropy. The PSO was designed to optimize the clustering analysis, and the minimum envelope entropy of the acoustic signal was regarded as the feature for classification. We then use a shearer simulation platform to collect the acoustic signal and use the approach proposed in this paper to process and classify the signal. The experimental results show that the approach proposed can effectively extract the features of the acoustic signal of the shearer. The recognition accuracy of the acoustic signal was high, which has practical application value.

The drum shearer is one of the main equipments of the long-wall mining system that has been widely used in coal mining for decades. Influenced by large fluctuation and intensive impact of drum load, the drum driving system is a weak part of the drum shearer due to the large dynamic deformation on ranging arm housing and the changes of gear meshing state. Since previous studies did not consider the coupling effects of housing and gearing transmission system, this study is concerned with hybrid finite element/lumped parameter dynamic modeling of the housing-transmission coupled system. In order to model the drum driving system, it is subdivided into two substructures: housing and transmission system. The housing is modeled by finite element method while the transmission system is modeled by lumped parameter method. The dynamic sub-structuring method (DSM) is used to develop a hybrid dynamic model, taking elastic coupling between the housing and transmission system into consideration. Then the influence of housing topological optimization on the dynamic characteristics of drum driving system is also analyzed through the hybrid dynamic model. The housing topological optimization is conducted through the Optistruct solver in Hypermesh, aiming at increasing the natural frequency of housing. It can be concluded that the ranging arm housing topological optimization could reduce the dynamic deformation of the housing and thus also reduce the equivalent mesh misalignment. However, the influence of housing topological optimization on the dynamic meshing force is not very significant.

The impact of the load on the shearer is mainly transmitted through cutting part. In this paper, in order to get the vertical steering vibration characteristics of the cutting part of the drum shearer, the working condition of coal mining machine is simplified. A simplified vertical steering model and the simplified vibration model of the whole cutting part of shearer are established. The vertical steering vibration process of the cutting unit is simplified into a single freedom and one forced vibration system under harmonic excitation. The dynamic response of the cutting part under sine excitation is obtained by using Matlab/Simulink for modeling and simulation. The influence of the support rigidity and damping of the high oil cylinder on the vertical steering vibration characteristics of the cutting part is analyzed. The results show that the damping of the cylinder can reduce the vibration of the system and the stability of the swing process of cutting the part is improved. [ABSTRACT FROM AUTHOR]

A BP neural network algorithm based hierarchical identification method， which divides the coal seam hardness into six levels， was proposed for identifying the coal seam hardness. The identification signals were taken from the stator currents of both the cutting motor and the traction motor of the mining machine， as well as the pressure signal of the height adjustment cylinder. The wavelet packet decomposition was used for extracting the characteristics of each signal， and these signals were taken as the input signals for training and testing the neural network. The experimental results show that the identification accuracy reaches 96.7% and 93.3% toward the simulation data and the real data， respectively， validating the effectiveness of the method. The method proposed provides the foundation for precisely identification of coal seam hardness. [ABSTRACT FROM AUTHOR]

In order to extend the service life of the long-chain gear transmission system of a drum shearer, an electro-mechanical coupling model of a drum shearer cutting unit is established. The model considers the dynamic characteristics of the motor, time-varying meshing stiffness, as well as the drum load characteristics. Additionally, the dynamic characteristics and control strategy for suppressing the dynamic load of the gear transmission system under impact load are investigated based on this model. Firstly, the influence of the gear transmission system of the drum shearer cutting unit under impact load is analyzed. Then, on that basis, the active control strategy based on motor torque compensation is proposed to suppress the dynamic load of the gear transmission system caused by mutational external load. Finally, the suppression effect on the dynamic load of the gear transmission system is analyzed. Research results indicate that this control strategy has good control effects to suppress the dynamic load caused by a mutational external load, which confirms the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cutting arms are the main productive units of coal shearer machine that contact directly with coal seam. More importantly, the cutting arms operate under a high-stressed environment. In this paper, in order to suggest an optimum maintenance plan for the subsystem of shearer machine, firstly, we conducted a failure and reliability analysis using the data acquired from the Parvade coal mine, Iran over the two years. The analysis shows that the Power Law Process model provides a good fit to the failure data. Also, we applied estimated distribution functions and calculated cost parameters to identify the cost-based optimum preventive maintenance interval. Furthermore, we conducted a sensitivity analysis of the studied machine and identified that if we consider the variation of the world price of the raw coal then the maintenance plan is sensitive to the price. The analysis showed that, big changes in world price of raw coal are not so effective on maintenance plan but have a considerable effect on maintenance costs of the cutting arms of the shearer machine. However, the effects of this change on reliability improvement are almost zero. [ABSTRACT FROM PUBLISHER]

Spray jets constitute one of the most important parts of each type of rock cutting machine, especially the drum shearer. This system cools the cutting picks and controls the dust emission. The blockage of spray jets causes the coal shearer machine to stop automatically. Therefore, the reliable performance of this system assists the achievement of a smooth coal cutting operation. Field's data shows that the maintenance of this system is time-consuming and causes major downtimes in the production process. Therefore, it is essential to find an optimum preventive maintenance task and intervals, to reduce the downtime and minimize the associated costs of the machine. The aim of this paper is to identify an applicable and effective maintenance task, with its associated interval, for management of the failure modes of the spray jets of coal shearers. A case study has been conducted on spray jets of double-drum shearer machine in Tabas Coal Mine in Iran. In the study, the RCM approach is used to select an applicable and effective maintenance task. The failure data were analyzed using a parametric approach to evaluate the reliability of the spray jets, and to estimate the reliability parameters. A reliability-based cost modeling has been implemented to identify the optimum maintenance interval and frequencies of restoration for the spray jets. In the study, a cost rate function (CRF) has been introduced in which an as-good-as-new (AGAN) effectiveness for restoration actions is considered. The CRF also considers restoration and repair times, and takes into account the costs associated with repair and restoration, and the opportunity cost of the equipment's lost production due to maintenance downtime, to arrive at the most cost-effective maintenance intervals. The results of the analysis have shown that the minimum cost per unit of time, $46.5/h, will be achieved within a range of intervals i.e., T = 210 to T = 260 . [ABSTRACT FROM AUTHOR]

In this article, the reliability of the cable system of a drum shearer machine was studied and analysed using operation and maintenance data from an Iranian mine for a period of two years. The tests for trend and serial correlation show that the times between successive failures for the cable system are not independent and identically distributed. A goodness-of-fit test shows that the power law process model provides a good fit to the failure data of this system. After parameter estimation for the power law model, reliability and failure rate plots were obtained. Based on analysis and results, a period of 125 h was defined as the reliability-based maintenance interval for the cable system of the shearer. The analysis shows that, by using this strategy, the reliability of the system will improve by at least 50%. [ABSTRACT FROM AUTHOR]

The hydraulic system plays an important role in supplying power and its transition to other working parts of a coal shearer machine. In this paper, the reliability of the hydraulic system of a drum shearer was analyzed. A case study was done in the Tabas Coal Mine in Iran for failure data collection. The results of the statistical analysis show that the time between failures (TBF) data of this system followed the 3-parameters Weibull distribution. There is about a 54% chance that the hydraulic system of the drum shearer will not fail for the first 50 h of operation. The developed model shows that the reliability of the hydraulic system reduces to a zero value after approximately 1 650 hours of operation. The failure rate of this system decreases when time increases. Therefore, corrective maintenance (run-to-failure) was selected as the best maintenance strategy for it. [ABSTRACT FROM AUTHOR]

The reliability and maintainability of electrical system of drum shearer at Parvade.1 Coal Mine in central Iran was analyzed. The maintenance and failure data were collected during 19 months of shearer operation. According to trend and serial correlation tests, the data were independent and identically distributed (iid) and therefore the statistical techniques were used for modeling. The data analysis show that the time between failures (TBF) and time to repair (TTR) data obey the lognormal and Weibull 3 parameters distribution respectively. Reliability-based preventive maintenance time intervals for electrical system of the drum shearer were calculated with regard to reliability plot. The reliability-based maintenance intervals for 90%, 80%, 70% and 50% reliability level are respectively 9.91, 17.96, 27.56 and 56.1 h. Also the calculations show that time to repair (TTR) of this system varies in range 0.17∼4 h with 1.002 h as mean time to repair (MTTR). There is a 80% chance that the electrical system of shearer of Parvade.1 mine repair will be accomplished within 1.45 h. [ABSTRACT FROM AUTHOR]

• A new classification of failure mechanism of mining tools was suggested. • 33 cutting picks pf a drum shearer machine in a longwall mine was studied. • 3D geometrical, macroscopic and microscopic analysis were carried out. • Design and operational guidelines were recommended to reduce the tool wear. In this paper, the results of a comprehensive study on failures of coal shearer picks in Parvadeh coal mine in Iran has been carried out and the main mechanisms and causes for pick failures have been investigated. For this purpose, 33, worn-out picks were collected from mine for laboratory studies. A series of tests and measurements, including weight loss, 3D geometry analysis of wear, macroscopic, and SEM microscopic analysis, were conducted. The results showed that pick body wears, breakage of pick tip, slimming of pick body, and separation and removal of pick tip are the most frequent failure and wear mode of studied picks. It is also observed that due to the locking of some picks in their holders, the high level of stress is transferred through the pick body to its bottom. It finally damages the pick and destroys the pick location on the drum. Nevertheless, the main reasons for most of the identified failures are the ineffective rock breakage, which is caused by long spaces between the picks. Finally, some practical recommendations especially redesigning the drum and picks' configuration, are presented in the paper to enhance the lifetime of cutting picks of the studied shearer. [ABSTRACT FROM AUTHOR]

During operation, the acoustic signal of the drum shearer contains a wealth of information. The monitoring or diagnosis system based on acoustic signal has obvious advantages. However, the signal is challenging to extract and recognize. Therefore, this paper proposes an approach for acoustic signal processing of a shearer based on the parameter optimized variational mode decomposition (VMD) method and a clustering algorithm. First, the particle swarm optimization (PSO) algorithm searched for the best parameter combination of the VMD. According to the results, the approach determined the number of modes and penalty parameters for VMD. Then the improved VMD algorithm decomposed the acoustic signal. It selected the ideal component through the minimum envelope entropy. The PSO was designed to optimize the clustering analysis, and the minimum envelope entropy of the acoustic signal was regarded as the feature for classification. We then use a shearer simulation platform to collect the acoustic signal and use the approach proposed in this paper to process and classify the signal. The experimental results show that the approach proposed can effectively extract the features of the acoustic signal of the shearer. The recognition accuracy of the acoustic signal was high, which has practical application value. [ABSTRACT FROM AUTHOR]