Application ANN Tool for Validation of LHD Machine Performance Characteristics

Jakkula, Balaraju; Mandela, Govinda Raj; Chivukula, Suryanarayana Murthy

doi:10.1007/s40033-019-00203-3

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…There are many papers related to various aspects of LHDs. Most of them are focused on reliability analysis [1][2][3][4][5][6], prediction and assessment of machines breakdowns [7], machine performance measures [8][9][10][11][12], utilisation analysis, optimisation, production analysis [11,[13][14][15], risk evaluation [16], residual life estimation [17], etc. Just a few works have mentioned condition monitoring [18][19][20][21][22], technical and operational aspects related to LHD machines [23][24][25][26] and real measurement of output torque, identification of operation regimes, etc.…”

Section: Brief State Of the Artmentioning

confidence: 99%

A Method for Structure Breaking Point Detection in Engine Oil Pressure Data

et al. 2021

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In this paper, a heavy-duty loader operated in an underground mine is discussed. Due to extremely harsh operational conditions, an important maintenance problem is related to engine oil pressure. We have found that when the degradation process appears, the nature of variation of pressure engine oil changes. Following this observation, we have proposed a data analysis procedure for the structure break point detection. It is based on specific data pre-processing and further statistical analysis. The idea of the paper is to transform the data into a nearly monotonic function that describes the variation of machine condition or in the statistical language—change of the regime inside the process. To achieve that goal we proposed an original data processing procedure. The dataset analyzed in the paper covers one month of observation. We have received confirmation that during that period, maintenance service has been done. The purpose of our research was to remove ambiguity related to direct oil pressure analysis and visualize oil pressure variation in the diagnostic context. As a fleet of machines in the considered company covers more than 1000 loaders/trucks/drilling machines, the importance of this approach is serious from a practical point of view. We believe that it could be also an inspiration for other researchers working with industrial data.

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Section: Brief State Of the Artmentioning

confidence: 99%

A Method for Structure Breaking Point Detection in Engine Oil Pressure Data

et al. 2021

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Performance evaluation of mining equipment in surface coal mine using reliability analysis

N.S.¹,

John²,

R³

et al. 2022

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This article deals with reliability analysis of mining equipment such as shovels and dumper in a surface coal mine at The Singareni Collieries Co. Ltd., Telangana, by using the RBD and Markov model. First, the method is to obtain the MTBF and failure rate of the individual subsystem of a shovel and each dumper using RBD. Second, the attribute of the reliability-based Markov model is dissected. The method is shown to be an effective technique to obtain the reliability of the whole system of shovel and dumper during the working period. Then, the mathematical model has written to obtain the reliability of the whole system of the shovel and the dumper is described along with its validation. The outcome shows that the reliability with a time of the entire framework is the unwavering quality incorporated of subsystems and can be treated as a factor for the optimized process of availability of the same.

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Application ANN Tool for Validation of LHD Machine Performance Characteristics

Cited by 2 publications

References 16 publications

A Method for Structure Breaking Point Detection in Engine Oil Pressure Data

A Method for Structure Breaking Point Detection in Engine Oil Pressure Data

Performance evaluation of mining equipment in surface coal mine using reliability analysis

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