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Assessment of Self-Heating Susceptibility of Indian Coal Seams – a Neural Network Approach

机译:神经网络方法对印度煤层自热敏感性的评估

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The paper addresses an electro-chemical method called wet oxidation potential technique for determining the susceptibility of coal to spontaneous combustion. Altogether 78 coal samples collected from thirteen different mining companies spreading over most of the Indian Coalfields have been used for this experimental investigation and 936 experiments have been carried out by varying different experimental conditions to standardize this method for wider application. Thus for a particular sample 12 experiments of wet oxidation potential method were carried out. The results of wet oxidation potential (WOP) method have been correlated with the intrinsic properties of coal by carrying out proximate, ultimate and petrographic analyses of the coal samples. Correlation studies have been carried out with Design Expert 7.0.0 software. Further, artificial neural network (ANN) analysis was performed to ensure best combination of experimental conditions to be used for obtaining optimum results in this method.All the above mentioned analysis clearly spelt out that the experimental conditions should be 0.2 N KMnO4 solution with 1 N KOH at 45°C to achieve optimum results for finding out the susceptibility of coal to spontaneous combustion. The results have been validated with Crossing Point Temperature (CPT) data which is widely used in Indian mining scenario.
机译:该论文提出了一种电化学方法,称为湿氧化电位技术,用于确定煤对自燃的敏感性。该实验研究共使用了从分布在印度大多数煤田的13个不同采矿公司收集的78个煤样品,并通过改变不同的实验条件进行了936个实验,以标准化该方法的广泛应用。因此,对于特定的样品,进行了湿氧化电位法的12个实验。通过对煤样品进行近距离,极限和岩石学分析,将湿氧化电位法(WOP)的结果与煤的固有性质相关联。相关性研究已使用Design Expert 7.0.0软件进行。此外,为了确保最佳实验结果的最佳组合,我们进行了人工神经网络(ANN)分析,所有上述分析清楚地表明,实验条件应为0.2 N KMnO4溶液和1 N KOH在45°C时可获得最佳结果,以找出煤对自燃的敏感性。结果已通过在印度采矿场景中广泛使用的交叉点温度(CPT)数据进行了验证。

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