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METHOD AND SYSTEM FOR ONLINE MONITORING AND OPTIMIZATION OF MINING AND MINERAL PROCESSING OPERATIONS

  • US 20200132882A1
  • Filed: 10/24/2019
  • Published: 04/30/2020
  • Est. Priority Date: 10/26/2018
  • Status: Active Grant
First Claim
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1. A processor implemented method for online monitoring and optimization of mining and mineral processing operations, the processor implemented method comprising:

  • fetching from a plurality of data sources, by one or more hardware processors, data for a set of variables corresponding to a set of sensors associated with the mining and mineral processing operations;

    pre-processing, by the one or more hardware processors, the fetched data corresponding to the set of variables by discarding outliers, performing imputation for adding artificial values at missing positions, organizing data collected at different frequencies to one common frequency, identifying and selecting data based on steady state operation of a process or a sub-process associated with the mining and mineral processing operations;

    determining, by the one or more hardware processors, standard operating condition for the mining and mineral processing operations using the pre-processed data corresponding to the set of variables;

    segregating each variable among the set of variables into one of drilling-blasting operations, hauling operations, comminution operations, and flotation and concentration operations, wherein segregation is performed in accordance with a master tag list;

    generating, by the one or more hardware processors, a set of models based on the segregated set of variables and preprocessed data, wherein the set of models is generated for a set of Key Performance Indicators (KPIs) of interest and a plurality of process parameters of interest associated with the mining and mineral processing operations, wherein the generated set of models comprise a set of Machine learning (ML) models or a set of individualized physics based models or hybrid models, and wherein the set of individualized physics based or hybrid models are generated for the plurality of process parameters based on known physics based models by determining model parameters using non-linear curve fitting;

    simulating, by the one or more hardware processors, current operating condition of the mining and mineral processing operations corresponding to the set of variables based on at least one of;

    the generated ML models, the set of individualized physics based or hybrid models of the KPIs and the plurality of process parameters, wherein the simulated current operating condition provides current values for KPIs and the plurality of process parameters of interest; and

    hierarchically optimizing, by the one or more hardware processors, the KPIs of interest of the mining and mineral processing operations to update the current operating conditions of a subset of variables among the set of variables of the mining and mineral processing operations, wherein the KPIs of interest are from at least one of mining operations, a comminution circuit, and a flotation and concentration circuit.

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