Remote Mining Equipment Maintenance Judgment via Chronological Sensor Analysis
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Solution Overview
Problem
Existing systems for managing self-propelling mining equipment lack precision in determining whether maintenance is required, when it should be performed, and what specific actions are needed, due to limitations in remote judgment based solely on sensor data, which can be affected by operator quality, weather, or sensor abnormalities.
Innovation Solution
An operation management device with sensors on mining equipment that transmits data to a management center for signal processing and image display, allowing for chronological pattern analysis, warning levels, and additional information storage to provide accurate maintenance decisions, including maintenance history and operator performance comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sensor data is used for remote maintenance judgment, then maintenance decisions can be made remotely, but precision of maintenance judgment deteriorates due to operator quality, weather, or sensor abnormalities affecting the data
Solution Approach 1:
The patent introduces a management center as an intermediary between the mining machine and maintenance personnel. The management center receives sensor data, performs comprehensive analysis including chronological pattern recognition, and generates maintenance judgments. This intermediary process filters out false alarms caused by operator quality, weather, or sensor abnormalities, thereby maintaining remote operation capability while improving judgment precision.
Solution Approach 2:
The system implements feedback mechanisms where sensor data is continuously monitored, analyzed for chronological patterns, and used to generate maintenance warnings. The feedback loop includes comparing current sensor readings with historical patterns to distinguish between actual equipment failures and transient anomalies caused by external factors, thereby improving the precision of maintenance judgments.
2Reliability
If maintenance is performed frequently to ensure equipment reliability, then equipment failure is reduced, but loss of time for maintenance operations increases
Solution Approach 1:
The system performs preliminary analysis of sensor data to predict potential equipment failures before they occur. By detecting chronological patterns and trends in sensor readings, the system identifies equipment that requires maintenance in advance, allowing scheduled maintenance during optimal time windows rather than emergency repairs or unnecessary preventive maintenance, thereby reducing overall maintenance time while maintaining reliability.
Solution Approach 2:
The mining machine autonomously monitors its own sensor data and transmits it to the management center for analysis. The system self-diagnoses potential issues and generates maintenance requests without external intervention, enabling timely maintenance decisions while minimizing downtime through automated monitoring and prediction capabilities.
Data Source
AI summary
Operation of self-propelled mining equipment in the field can be accurately recognized at a remote position of the equipment. A management center for controlling a dump truck receives signal from sensors in order to show detection data for the working status of the operation instruments and warning indication data based upon the detection data. The warning indication data and the detection data for the working status of the operation instruments are displayed on the same display. Alternatively, in place of the detection data for working status of the operation instruments, related information from a data base concerning the record of maintenance previously conducted may be displayed, or a graph of the detection data for the working status of an operation instrument of another dump truck which is operating in the same working field may be displayed.