Motor Abnormality Detection via Torque-Parameter Comparison
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Solution Overview
Problem
Existing motor detection systems cannot predict problems related to wear and tear of machines and often fail to distinguish between motor malfunctions and issues with other system components.
Innovation Solution
A system that uses a processor and memory to compare current motor and machine parameter measurements against stored baseline values to detect abnormal operations, allowing for real-time monitoring and differentiation between motor and system component issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sensing devices are used to monitor operating parameters, then abnormal operation can be detected, but the system cannot predict wear and tear problems or distinguish between motor and component issues
Solution Approach 1:
The patent segments the monitoring approach by creating separate monitoring pathways: one for machine operating parameters (pressure, temperature, flow) and another for motor-specific parameters (current, voltage, speed). This segmentation allows the system to detect abnormalities in both the machine and motor independently, enabling differentiation between component failures and motor issues.
Solution Approach 2:
The patent adds a temporal dimension to monitoring by continuously tracking parameter changes over time and comparing them against historical data and expected ranges. This dimensional addition transforms static threshold checks into dynamic trend analysis, enabling prediction of wear and tear before failure occurs.
2Reliability
If continuous monitoring is implemented to detect abnormalities, then system reliability improves, but operational interruptions for maintenance increase
Solution Approach 1:
The system performs preliminary detection and diagnosis continuously during normal operation, identifying potential issues before they cause failures. By detecting wear trends and abnormal patterns early, the system enables planned maintenance scheduling that minimizes operational interruptions while maintaining high reliability.
Solution Approach 2:
The patent implements feedback loops where monitored parameters are continuously compared against expected ranges and historical data. When deviations are detected, the system provides feedback alerts that trigger maintenance actions only when necessary, avoiding unnecessary shutdowns while preventing failures.
Data Source
AI summary
There is provided a system and method for detecting an abnormal operation of a motor controlling an operating parameter of a machine. Both a torque of the motor and the operating parameter are monitored. A memory stores a plurality of predetermined torque values indicative of a normal operation of the motor. A plurality of operating parameter values are also stored in the memory with each operating parameter value having a corresponding predetermined torque value associated therewith. The predetermined torque value corresponding to the monitored operating parameter is retrieved from the memory and compared to the monitored torque value to detect an abnormal operation of the motor.