Skip to main content
SpringerLink
Log in

Neural Network Assisted Analysis for Longwall Gate Road Stability Using Measured Roof Convergence Data

  • Original Paper
  • Published:
Geotechnical and Geological Engineering Aims and scope Submit manuscript

Abstract

Immediate roof of a longwall panel is composed of layered coal, shaly coal, shale and clay strata overlaying by a thick sandstone main roof. The average depth of the coal seam is about 420 m and it has dip of 10°. The gate roads of width 5.2 m and height 3.5 m are developed in either sides of the panel and the roof is supported by 2.4 m resin grouted rock bolts. A special resin grouted 60 tonne capacity, 6.1 m long bulb type cable bolt is also installed for effectively supporting 8 m width shield installation roadway and gate roads during retreat of the longwall panel. The paper emphasizes on the monitoring and analysis of roof convergence in gate roads by convergence recorder as well as double telescopic telltale devices. Based on the analysis results, design is modified to improve the stability of gate roads. Cumulative roof convergence (CRC) data during development of gate roads are found to vary as tangent hyperbolic function with passage of time and are analyzed using artificial neural network to estimate the key parameters of the function. Convergence increase rate along with the maximum CRC is then used to prepare a Trigger Action Response Plan for immediate notification of the ground control problems. Data analysis also suggests that during retreat of longwall panel, CRC increases exponentially if the longwall face approaches within 10 to 25 m from a measuring station installed along main and tail gate roads. In this paper, methodologies are described for the analysis of CRC data for better understanding of roof behavior and for taking timely decision for any unusual event.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  • Afrouz A, Hassani FP, Scoble M (1988) The performance of longwall gate roads with soft floors. Canad Geotech J 25:279–291

    Article  Google Scholar 

  • Barron L, DeMarco MJ (1995) Longwall gate road stability in a steeply pitching thick coal seam with a weak roof

  • Barron LR, DeMarco MJ, Kneisley RO (1994) Longwall gate road stability in four deep western US coal mines. Information circular. United States. https://www.osti.gov/biblio/7018935-longwall-gateroad-stability-four-deep-western-us-coal-mines-information-circular. Accessed 26 Mar 2019

  • Colwell M, Frith R (2009) ALTS 2009—a ten year journey. In: N Aziz (ed) Coal 2009: coal operators’ conference, 12–13 February, pp 37–53

  • Deb D, Verma AK (2004) Ground control problems in Indian longwall mines: a perspective and future research outlook. J Mines Metals Fuels 52(9 & 10):178–185

    Google Scholar 

  • Frith R, Reed G, Mckinnon M (2017) Fundamental principles of an effective reinforcing roof bolting strategy in horizontally layered roof strata and areas of potential improvement. Int J Min Sci Technol 28:67–77

    Article  Google Scholar 

  • Ghose AK (2003) Why longwall in India has not succeeded as in other developing country like China. IE(I) J MN 84:2001–2004

    Google Scholar 

  • Kumar B, Chandrasekhar S, Reddy BV (2016) Construction and operation of high capacity longwall project—Adriyala experience. In: An international conference on recent advances in rock engineering, Bangalore, pp 16–18

  • Mahdevari S, Shahriar K, Sharifzadeh M, Tannant D (2017) Stability prediction of gate roadways in longwall mining using artificial neural networks. Neural Comput Appl 28:3537–3555

    Article  Google Scholar 

  • Mahdi S, Li C (2012) Numerical modeling of longwall mining and stability analysis of gates in a coal mine. J Rock Mech Min Sci 51:24–34

    Article  Google Scholar 

  • Maleki H, Agapito J, Wangsgard M, Cort J (1986) Gate road layout design for two-seam longwall mining. Int J Min Geol Eng 4:111–127

    Article  Google Scholar 

  • Park D, Deb D (1999) Longwall strata control and maintenance system—a stethoscope for longwall mining. Min Eng 51:49–53

    Google Scholar 

  • Park D, Lee S, Jiang Y, Deb D (1993) Numerical simulation of main roof behavior in Longwall mining, In: First Canadian symposium on numerical modeling applications in mining and geomechanics, Montreal, Canada, pp 129–139

  • Peng S (1987) Support capacity and roof behaviour at longwall faces with shield supports. J Min Geol Eng 5:29–57

    Article  Google Scholar 

  • Rezaei M, Hossaini MF, Majdi A, Najmoddini I (2017) Determination of the height of destressed zone above the mined panel: an ANN model. Int J Min Geo-Eng 51(1):1–7

    Google Scholar 

  • Trueman R, Lyman GJ, Cocker A (2009) Longwall roof control through a fundamental understanding of shield-strata interaction. J Rock Mech Min Sci 51:24–34

    Google Scholar 

  • Tulu I, Su D (2018) Analysis of global and local stress changes in a longwall gateroad. J Min Sci Technol 28:127–135

    Article  Google Scholar 

  • Verma AK, Deb D (2007) Statistical and neural regression approach for prediction of longwall chock-shield support pressure. In: 11th ISRM Congress, 9–13 July, Lisbon, Portugal

  • Verma AK, Kaushal K, Chatterjee S (2016) Prediction model of longwall powered support capacity using field monitored data of a longwall panel and uncertainty—based neural network. Geotech Geol Eng 34:2033–2052

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to express their sincere appreciation and grateful thanks to the management of SCCL for their support and cooperation, for permitting to present this paper and also permitting to use certain data for presenting in this paper.

Author information

Authors and Affiliations

  1. Adriyala Longwall Project, APA, SCCL, Bhadradri Kothagudem District, India

    Srikanth Katkuri

  2. Mining Engineering Department, IIT Kharagpur, Kharagpur, India

    Debasis Deb

  3. Adriyala Projects Area, SCCL, Bhadradri Kothagudem District, India

    B. V. Reddy

  4. Department of Mining Engineering, IIT(ISM)-Dhanbad, Dhanbad, India

    Hemant Kumar

Authors
  1. Srikanth Katkuri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Debasis Deb
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. V. Reddy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hemant Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Debasis Deb.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Katkuri, S., Deb, D., Reddy, B.V. et al. Neural Network Assisted Analysis for Longwall Gate Road Stability Using Measured Roof Convergence Data. Geotech Geol Eng 37, 3843–3860 (2019). https://doi.org/10.1007/s10706-019-00873-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10706-019-00873-6

Keywords

Search

Navigation