Electric Motor Health Monitoring Using Virtual Sensor Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for monitoring the operational health of electric motors in safety-critical applications, such as flight control, often rely on redundant motors and additional sensors, which can increase complexity and cost. These systems struggle to detect faults, such as winding shorts or bearing failures, without causing imbalances that can lead to further failures.
Innovation Solution
A health monitoring system that includes a state estimator and a fault detector. The state estimator models estimated motor values based on motor control parameters and states, while the fault detector provides a fault signal by comparing these estimates to predetermined threshold values, and modifies a non-transitory computer readable medium accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant motors are used in safety critical applications, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements preliminary action by continuously monitoring motor health parameters (temperature, vibration, current) and predicting potential failures before they occur. The system estimates motor values such as winding resistance and bearing condition in advance, allowing proactive maintenance scheduling that prevents catastrophic failures without requiring redundant motors, thus maintaining reliability while reducing system complexity.
2Measurement precision
If additional sensors are added for motor monitoring, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies the copying principle by creating virtual models (digital twins) of the motor's internal states using mathematical estimation algorithms. Instead of installing physical sensors to directly measure winding resistance, magnetic field strength, or bearing wear, the system copies the motor's behavior through computational models that process readily available data from standard motor control circuits, achieving precise measurement without additional hardware complexity.
Solution Approach 2:
The patent replaces mechanical/physical sensing systems with computational estimation methods. Rather than using physical sensors to directly detect motor parameters, the system substitutes mathematical algorithms that estimate these parameters from electrical measurements already taken for motor control, eliminating the need for additional sensor hardware while maintaining measurement precision.
3Productivity
If motor operation continues without monitoring, then productivity is maintained, but reliability deteriorates due to undetected faults
Solution Approach 1:
The patent implements continuous feedback by monitoring motor health parameters in real-time during normal operation and using this information to adjust maintenance schedules and operational decisions. The system provides feedback loops where estimated motor values are continuously compared against thresholds and trends, enabling proactive maintenance that maintains productivity by preventing unexpected failures while improving reliability through continuous health assessment.
Data Source
AI summary
The subject matter of this specification can be embodied in, among other things, an electric motor health monitoring system that includes an estimator module configured to model one or more estimated motor values of an electric motor based on one or more motor control parameters and one or more motor control states, a non-transitory computer readable medium, and a fault detector module configured to (1) provide a fault signal based on the modeled one or more estimated motor values of the motor and a predetermined parameter threshold value, and (2) modify the non-transitory computer readable medium based on the fault signal.