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Author: search.filters.author.Dorthi, K.Has files: No

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    Accurate Estimation for Stability of Slope and Partition Over Old Underground Coal Workings Using Regression-Based Algorithms
    (Springer Science and Business Media Deutschland GmbH, 2022) Dorthi, K.; Kumar, A.; Ram Chandar, K.R.
    Numerical modeling simulation has found to be best solution for predicting slope and partition stability over old underground coal workings. But it has taken huge time to complete a single simulation model. In this regard, machine learning-based framework is used to predict the stability of old galleries. A case study is taken up in opencast mine and simulation is carried out using numerical model and machine learning-based framework. Framework has shown an overall accuracy of 94–95% for different slope and partition stability. Framework shows a speedup of 2366 × against numerical simulator. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Computer aided slope stability monitoring
    (Disaster Advances disaster@managein.org, 2017) Dorthi, K.; Ram Chandar, K.R.
    Slope stability accidents are one of the leading causes of fatalities at surface mining operations. Monitoring of the slopes of surface mines can prevent loss of life, destruction of equipment, loss of ore reserves and closure of the mine. In this paper, an attempt is made to review the recent developments in slope stability monitoring system. Zigbee based Wireless Sensor Networks (WSNs) of short distance, low- complexity, low power consumption, low data rate, low-cost, twoway and wireless communication solution for slope stability monitoring system is discussed. A comparison of slope monitoring systems has been done by considering different parameters such as accuracy, update rate, range, slope coverage, weather conditions etc.
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    Slope stability monitoring in opencast coal mine based on wireless data acquisition system-a case study
    (Science Publishing Corporation Inc ijet@sciencepubco.com, 2018) Dorthi, K.; Ram Chandar, K.R.
    Real time monitoring of slope failures is necessary to maintain the stability of slopes in open cast mines. A 3-level structure of Wireless Data Acquisition System (WDAQ) is developed for real time monitoring of slope deformation and analysis of data. In this paper, a case study is presented in a large opencast coal mine. Deformation in the slopes with slope angles of 49°, 53°, 58°, 64°, 68° and 70° is monitored over old underground workings. The deformation caused due to the external load like movement Heavy Earth Moving Machinery (HEMM). Maximum deformation was 1.57mm for slope angle of 70°. It can be observed that the deformation increased with increased slope angle. This paper also describes that the validation of data based on WDAQ with the conventional method of monitoring as well as numerical modeling. The data obtained using WDAQ is in close to other two methods. The variation is around 11%. © 2018 Authors.
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    Zigbee based Wireless Data Acquisition System for monitoring of partition stability above old underground coal workings
    (Springer, 2020) Dorthi, K.; Bayyapu, N.; Ram Chandar, R.C.
    Conversion of old underground workings into opencast mines leads to rock displacement, collapse of partition, and slope failures some times. Continuous monitoring of slopes and partition is required to maintain the stability over old workings. Wireless sensor network is more suitable method for continuous monitoring, and it is cost-effective, two-way communication, and provides real-time monitoring and analysis of data. In this paper, development of a low-cost Zigbee based Wireless Data Acquisition System (WDAQ) is described. Field investigations were carried out in an opencast coal mine in south India to assess the strain and deformation for different partition thicknesses of 4.12m, 5.91m, 6.86m, 7.91m, 10.21m and 12.10m over old underground workings, due to the external load caused by the movement of Heavy Earth Moving Machinery (HEMM). Maximum strain and deformation were 387 × 10?6 and 2.41 mm for 4.12 m partition, respectively. It can be observed that the strain and deformation are decreased with increased partition thickness. This paper also describes that the validation of data based on Zigbee based WDAQ with conventional method of monitoring as well as numerical modeling. The data obtained using WDAQ is in close to the other two methods. The variation is around 5–19%. © 2020, Saudi Society for Geosciences.
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    Integrated Slope Monitoring System for Slope Stability Over Old Underground Galleries During Surface Mining Operations Using Internet of Things
    (Springer Science and Business Media Deutschland GmbH, 2023) Dorthi, K.; Ram Chandar, R.C.
    Surface mining methods have been adopted to extract the coal which is in the form of pillars and roof in old underground coal workings. There are slope failures associated with the extraction method. Conventional slope monitoring systems are available but require physical presence of the person at the site and the readout units which are physically connected to the base units and generally such monitoring is done only during day light. Radar-based systems are being used to monitor the broad area through rain, dust, smoke and operate during both day and night. They provide accurate results, but they are high-cost and require a skilled person for operating in the field. Hence, an investigation taken up to assess the stability of the slope stability over old underground coal workings by using wireless sensor networks (WSNs) and internet of things (IoT). In this paper, monitoring of slope stability using a low cost wireless sensor networks is discussed. An integrated wireless data acquisition system is developed to assess the slope stability and it is validated with conventional instrument and numerical modeling approach. The variation in between integrated slope monitoring system (ISMS) to data logger and numerical modeling is around 3.03%–19%. Statistical analysis results revealed that there is a good correlation between field observations and modeling studies. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.