Predictive analysis for remote machine monitoring
First Claim
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1. A method for predicting a machine event for a mining machine comprising:
- receiving data for current events for the mining machine;
determining whether the data for the current events is within operational limits;
when the data for the current events is within operational limits, determining, using a predetermined model, whether an anomaly exists; and
generating an alert comprising information on the anomaly when the anomaly exists,wherein the data for current events comprises temperature for crowd bearings on a crowd motor drive end and temperature of crowd bearings at a non-driven end for a crowd belt oil the mining machine, and wherein the predetermined model monitors relative temperature between the crowd bearings and provides a cross-correlation between bearing temperatures and tension of the crowd belt to identify the anomaly for the crowd belt tension.
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Abstract
Methods for predicting a machine event are described. In one aspect, a method includes receiving data for current events for the machine, and determining whether the data for the current events is within operational limits. The method also includes, when the data for the current events is within operational limits, determining, using a predetermined model, whether an anomaly exists, and generating an alert including information on the anomaly when the anomaly exists. Systems and machine-readable media are also described.
87 Citations
7 Claims
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1. A method for predicting a machine event for a mining machine comprising:
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receiving data for current events for the mining machine; determining whether the data for the current events is within operational limits;
when the data for the current events is within operational limits, determining, using a predetermined model, whether an anomaly exists; andgenerating an alert comprising information on the anomaly when the anomaly exists, wherein the data for current events comprises temperature for crowd bearings on a crowd motor drive end and temperature of crowd bearings at a non-driven end for a crowd belt oil the mining machine, and wherein the predetermined model monitors relative temperature between the crowd bearings and provides a cross-correlation between bearing temperatures and tension of the crowd belt to identify the anomaly for the crowd belt tension. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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Specification