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Real-Time Comprehensive Energy Analysis of the LHD 811MK-V Machine with Mathematical Model Validation and Empirical Study of Overheating: An Experimental Approach

  • Research Article-Mechanical Engineering
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Abstract

Overheating is a critical problem encountered with an electro hydraulically operated machine working in underground mines. Aggrandizement in the temperature of the hydraulic fluids is caused due to deficiencies in the components. Thermal instability of hydraulic power systems causes temperature transients, which not only mitigates machine productivity but is also harmful. Especially considering the system inefficiency, the hydraulically driven machine has an inbuilt cooling arrangement. When the energy loss caused by faulty elements exceeds the system cooling capacity, hydrostatic transmission is overheated. Mathematical models, experimental studies, and analytical approaches evaluate the substantive reasons for heating and determine heat energy generation due to inefficient parts of the hydraulic system of the load haul dumper. The mathematical model is used to calculate heat energy addition, emulating power loss in hydraulic components and equivalence. Efficiency block diagram of entire hydraulic system has been created. Hydraulic components get worn out in due course of continuous operation of the machine. While calculating the series function, the overall efficiency up to 60% of all the components in the system will not accumulate the heat in the system. The Weibull distribution is used to analyse system reliability, and it is discovered that if the system inefficiency exceeds 40%, failure rate due to overheating increases. Excess heat energy causes fluid degradation, deterioration of rubber parts and seals, acceleration of wear, and tear of relative and mating parts and has an impact on the overall operation of the machine. Actuators' performance becomes erratic and sluggish.

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Abbreviations

T :

Temperature (°C)

t :

Time (s)

P :

Power (kW)

H :

Heat (kW)

h :

Heat transfer coefficient (w/m2K)

q :

Volumetric flow rate (m3/s)

p :

Pressure (bar)

V :

Velocity (m/s)

ηo :

Overall efficiency

η m :

Mechanical efficiency

D p :

Pump displacement (dm3)

D m :

Motor displacement (dm3)

η h :

Hydraulic efficiency

ɳ:

Efficiency

n :

Shaft speed (rpm)

n :

Number of components

D.V:

Dump valve

RVP:

Relief valve primary

RVS:

Relief valve secondary

CV:

Control valve

Cv:

Check valve

PV:

Priority valve

PRV:

Pressure reducing valve

r :

Radiator

rs:

Reservoir

τ :

Torque (Nm/s)

ω :

Angular velocity (rad/s)

μ :

Fluid dynamic viscosity (MPa.s)

\(\rho\) :

Fluid density (g/cm3)

m :

Mass flow rate (kg/s)

J :

Mechanical equivalent of Heat

C p :

Specific heat at constant pressure (J/kgK)

Z:

Height from datum (m)

g :

Gravitational acceleration (m/s2)

C d :

Discharge coefficient discharge

C s :

Slip coefficient

q 1 :

Leakage volumetric flow rate (dm3/min)

p L :

Load pressure (Psi)

p s :

Upstream pressure (Psi)

p v :

Downstream pressure (Psi)

K h :

Geometric loss factor

P t :

Pressure drop at throttle (bar)

q t :

Volumetric flow rate at throttle (dm3/min

References

  1. Al-Natour, IS: Study of an open circut hydraulic power system with compact cooler-reservoir unit. Dissertation Dublin City University, (1992)

  2. Norgard, J.S.: Thermodynamic determination of power loss in hydraulic components. J. Fluids Eng. 95, 2–7 (1973)

    Article  Google Scholar 

  3. El Haj, A.M.: Study of entropy generation in a slab with non-uniform internal heat generation. Therm. Sci. 17(3), 943–950 (2013)

    Article  MathSciNet  Google Scholar 

  4. Tang, W.; Xu, G.; Zhang, S.; Jin, S.; Wang, R.: Digital twin-driven mating performance analysis for precision spool valve. Machines 9, 157 (2021)

    Article  Google Scholar 

  5. Siddiqui, M.A.H., et al.: Sludge formation analysis in hydraulic oil of load haul dumper 811MK V machine running at elevated temperatures for bioenergy applications. Int. J. Chem. Eng. (2021). https://doi.org/10.1155/2021/4331809

    Article  Google Scholar 

  6. Tomioka K et al.:Simulation Model of Heat Generation and Transfer in Oil-Hydraulic System. In: proceedings of the JFPS international symposium on fluid power. Vol 2005. No. 6. The Japan Fluid Power System Society, (2005)

  7. Al-Gburi H., AH Al-Mamoori, and TN Hussein: Thermal analysis of sequence hydraulic system. Solid State Technol. 63.2s (2020)

  8. Maleki, H., et al.: Flow and heat transfer in non-Newtonian nanofluids over porous surfaces. J. Therm. Anal. Calorim. 135(3), 1655–1666 (2019)

    Article  MathSciNet  Google Scholar 

  9. Abdollahi, A., et al.: Experimental study to obtain the viscosity of CuO-loaded nanofluid: effects of nanoparticles’ mass fraction, temperature and basefluid’s types to develop a correlation. Meccanica 53(15), 3739–3757 (2018)

    Article  Google Scholar 

  10. Shadlaghani, A.; Farzaneh, M.; Shahabadi, M.; Tavakoli, M.R.; Safaei, M.R.; Mazinani, I.: Numerical investigation of serrated fins on natural convection from concentric and eccentric annuli with different cross sections. J. Therm. Anal. Calorim. 135(2), 1429–1442 (2019)

    Article  Google Scholar 

  11. Wodecki, J., et al.: Technical condition change detection using Anderson-Darling statistic approach for LHD machines–engine overheating problem. Int. J. Min. Reclam. Env. 32(6), 392–400 (2018)

    Article  Google Scholar 

  12. Al Natour, I.; Hashmi, M.S.J.: A mathematical model and computer aided design for the temperature distribution in an open hydraulic system. Int. J. Numer. Methods Heat Fluid Flow 3(5), 411–427 (1993)

    Article  Google Scholar 

  13. Kim, J.Y., et al.: Estimation of the heat generation and dissipation for the hydraulic system of a medium size excavator using one dimensional analysis. ASME Int. Mech. Eng. Cong. Expos. 44298, 735–740 (2010)

    Google Scholar 

  14. Samanta, B.; Sakar, B.; Mukherjee, S.K.: Reliability modelling and performance analyses of an LHD system in mining. J. South. Afr. Inst. Min. Metall. 104(1), 1–8 (2004)

    Google Scholar 

  15. Jocanović, M., et al.: Increased efficiency of hydraulic systems through reliability theory and monitoring of system operating parameters. Strojniškivestnik-J. Mech. Eng. 58(4), 281–288 (2012)

    Article  Google Scholar 

  16. Vashistha, S., et al.: Reliability and maintainability analysis of LHD Loader at Saoner Mines, Nagpur, India. IOP Conf. Ser. Mater. Sci. Eng. 691(1), 012013 (2019)

    Article  Google Scholar 

  17. Zhang, C., et al.: Research on the volumetric efficiency of a novel stacked roller 2D piston pump. Machines 9(7), 128 (2021)

    Article  Google Scholar 

  18. Zheng, Kunyao, and MingmingXu. "Design and Thermal Stability Analysis of Swing Micro-Mirror Structure for Gravitational Wave Observatory in Space." Machines 9.5 (2021): 104.

  19. Minav, IT., L Papini, and IM Pietola (2016) A thermal analysis of direct driven hydraulics

  20. Das, R., et al.: An inverse analysis of a transient 2-D conduction–radiation problem using the lattice Boltzmann method and the finite volume method coupled with the genetic algorithm. J. Quant. Spectrosc. Radiat. Transf. 109(11), 2060–2077 (2008)

    Article  Google Scholar 

  21. Singh, K.; Das, R.; Kundu, B.: Approximate analytical method for porous stepped fins with temperature-dependent heat transfer parameters. J. Thermophys. Heat Transf. 30(3), 661–672 (2016)

    Article  Google Scholar 

  22. Das, R.: A simulated annealing-based inverse computational fluid dynamics model for unknown parameter estimation in fluid flow problem. Int. J. Comput. Fluid Dyn. 26(9–10), 499–513 (2012)

    Article  MathSciNet  Google Scholar 

  23. Das, R.: Inverse analysis of Navier-Stokes equations using simplex search method. Inverse Probl. Sci. Eng. 20(4), 445–462 (2012)

    Article  MathSciNet  Google Scholar 

  24. Bashirnezhad, K., et al.: Viscosity of nanofluids: a review of recent experimental studies. Int. Commun. Heat Mass Transf. 73, 114–123 (2016)

    Article  Google Scholar 

  25. Esfe, M.H., et al.: Experimental study on thermal conductivity of ethylene glycol based nanofluids containing Al2O3 nanoparticles. Int. J. Heat Mass Transf. 88, 728–734 (2015)

    Article  Google Scholar 

  26. Goodarzi, M., et al.: Investigation of heat transfer and pressure drop of a counter flow corrugated plate heat exchanger using MWCNT based nanofluids. Int. Commun. Heat Mass Transf. 66, 172–179 (2015)

    Article  Google Scholar 

  27. Afrand, M., et al.: Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network. Int. Commun. Heat Mass Transf. 76, 209–214 (2016)

    Article  Google Scholar 

  28. Mohammadreza, H., et al.: Numerical study of entropy generation in a flowing nanofluid used in micro-and minichannels. Entropy 15(1), 144–155 (2013)

    Article  MathSciNet  Google Scholar 

  29. Safaei, M.R., et al.: Heat transfer and pressure drop in fully developed turbulent flows of graphene nanoplatelets–silver/water nanofluids. Fluids 1(3), 20 (2016)

    Article  Google Scholar 

  30. Alrashed, A.A.A.A., et al.: Effects on thermophysical properties of carbon based nanofluids: experimental data, modelling using regression, ANFIS and ANN. Int. J. Heat Mass Transf. 125, 920–932 (2018)

    Article  Google Scholar 

  31. McCandlish, D.; Dorey, R.E.: The mathematical modelling of hydrostatic pumps and motors. Proc. Inst. Mech. Eng. Part B Manag. Eng. Manuf. 198(3), 165–174 (1984)

    Google Scholar 

  32. Zhu, K., et al.: Analysis of the torque loss of high-speed transmission mechanism with a stacked roller set. Machines 9(8), 140 (2021)

    Article  Google Scholar 

  33. Sepulveda, N.E.; Sinha, J.: Mathematical validation of experimentally optimised parameters used in vibration-based machine-learning model for the faults diagnosis in rotating machines. Machines 9, 155 (2021)

    Article  Google Scholar 

  34. Akers, A.; Gassman, M.; Smith, R.: Hydraulic power system analysis. CRC Press, London (2006)

    Book  Google Scholar 

  35. Ghahfarokhi, P.S., et al.: Determination of heat transfer coefficient from housing surface of a totally enclosed fan-cooled machine during passive cooling. Machines 9(6), 120 (2021)

    Article  Google Scholar 

  36. El Haj, A.M.; Kotiaho, V.W.: Thermal analysis of a counterflow heat exchanger with a heat source. Int. J. Ambient Energy 31(4), 211–217 (2010)

    Article  Google Scholar 

  37. Said, Z., et al.: Heat transfer enhancement and life cycle analysis of a shell-and-tube heat exchanger using stable CuO/water nanofluid. Sustain. Energy Technol. Assess. 31, 306–317 (2019)

    Google Scholar 

  38. Badrinarayanan, S.; Bhinder, K.S.; Ramesh Kumar, V.: Thermal analysis of hydraulic system of landing gear. IOP Conf. Ser. Mater. Sci. Eng. 402, 012100 (2018)

    Article  Google Scholar 

  39. Drexler, P.: Planning and design of hydraulic power systems. Mannesmann Rexroth, Germany (1988)

    Google Scholar 

  40. Liu, Q., et al.: Adaptive cutting control for road headers based on performance optimization. Machines 9(3), 46 (2021)

    Article  Google Scholar 

  41. Salameh T, Tawalbeh M, and El Haj Assad, M. (2018) Experimental and numerical study on heat transfer enhancements of concentric tube heat exchanger using water based nanofluids. In: 2018 5th international conference on renewable energy: generation and applications (ICREGA), IEEE

  42. Malik, S.C.; Chauhan, S.K.; Ahlawat, N.: Reliability analysis of a nonseries–parallel system of seven components with Weibull failure laws. Int. J. Syst. Assur. Eng. Manag. 11(3), 577–582 (2020)

    Article  Google Scholar 

  43. IR Kuhlhoff (2018) Application of Weibull reliability model for functional safety of electro-hydraulic system. Computer Science

  44. M Orošnjak, Jocanović M, and Karanović V (2016) Quality analysis of hydraulic systems in function of reliability theory. In: annals of DAAAM & proceedings 27

  45. Rahimdel, M.J., et al.: Reliability-based maintenance scheduling of hydraulic system of rotary drilling machines. Int. J. Min. Sci. Technol. 23(5), 771–775 (2013)

    Article  Google Scholar 

  46. Jagtap, H.P., et al.: RAM analysis and availability optimization of thermal power plant water circulation system using PSO. Energy Rep. 7, 1133–1153 (2021)

    Article  Google Scholar 

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Funding

This work is supported with no financial assistance from any of the funding sources.

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Authors and Affiliations

  1. Coal India Limited, Western Coal Fields Limited, Saoner, Nagpur, India

    Mohd. Ahtesham Hussain Siddiqui

  2. Indian Institute of Technology (Indian School of Mines), Dhanbad, India

    Mohd. Ahtesham Hussain Siddiqui & Somnath Chattopadhyaya

  3. Department of Mechanical Engineering, IK Gujral Punjab Technical University, Kapurthala, 144603, India

    Shubham Sharma

  4. Sustainable and Renewable Energy Engineering Department, University of Sharjah, P O Box 27272, Sharjah, UAE

    Mamdouh El Haj Assad

  5. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China

    Changhe Li

  6. Department of Mechanical Engineering, Curtin University, Bentley, Perth, WA, 6155, Australia

    Alokesh Pramanik

  7. Civil Engineering Department, Istanbul Esenyurt University, 34510, Istanbul, Turkey

    Huseyin Cagan Kilinc

Authors
  1. Mohd. Ahtesham Hussain Siddiqui
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  2. Somnath Chattopadhyaya
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  3. Shubham Sharma
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  4. Mamdouh El Haj Assad
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  5. Changhe Li
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  7. Huseyin Cagan Kilinc
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Corresponding authors

Correspondence to Shubham Sharma or Mamdouh El Haj Assad.

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This article does not contain any studies with human participants or animals performed by the author.

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The data presented in this study are available on request from the corresponding author.

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Siddiqui, M.A.H., Chattopadhyaya, S., Sharma, S. et al. Real-Time Comprehensive Energy Analysis of the LHD 811MK-V Machine with Mathematical Model Validation and Empirical Study of Overheating: An Experimental Approach. Arab J Sci Eng 47, 9043–9059 (2022). https://doi.org/10.1007/s13369-021-06439-0

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