Motor Phase Fault Detection with Sector Peak Current Comparison
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Solution Overview
Problem
Existing motor control systems face challenges in efficiently detecting and mitigating unbalance phase and phase loss faults, which can lead to decreased output torque, increased current and temperature, and potential damage to stator windings.
Innovation Solution
A phase fault detection system that determines peak phase channel current sums and compares them across sectors to detect unbalance, using stator energization vectors to identify unbalance and initiate protective actions when thresholds are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional motor control systems are used without advanced fault detection, then the system structure remains simple, but the reliability of motor operation deteriorates due to undetected unbalance phase and phase loss faults
Solution Approach 1:
The fault detection system divides the motor operation into discrete sectors (e.g., six sectors per electrical cycle) and evaluates phase current balance independently in each sector. This segmentation allows the system to detect local unbalance conditions without requiring complex continuous analysis, thereby improving reliability while maintaining manageable system complexity.
Solution Approach 2:
The system performs preliminary evaluation of phase current balance in each sector before making fault determination decisions. By pre-calculating current sums and comparing them across sectors, the system prepares fault detection data in advance, enabling rapid and reliable fault identification without requiring complex real-time processing during critical fault events.
2Measurement precision
If sector-based peak current sum comparison is implemented, then the precision of fault detection is improved, but the computational complexity increases
Solution Approach 1:
Instead of analyzing all phase currents continuously, the system focuses on detecting peak current values and their sums in each sector. This partial action approach concentrates computational resources on the most critical moments (peak currents) that indicate fault conditions, achieving high detection precision without requiring complex continuous processing of all current data.
Solution Approach 2:
The system creates simplified representations of the phase current characteristics by calculating sector-based current sums. These summed values serve as copies or proxies for the actual complex current waveforms, allowing fault detection through comparison of these simplified metrics rather than direct analysis of the full current signals, thereby reducing processing complexity while maintaining detection precision.
3Reliability
If continuous monitoring of all phase currents is performed, then the detection coverage is comprehensive, but the processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential information needed for fault detection by focusing on peak current values and their sector sums. Instead of processing all phase current data continuously, it extracts and analyzes only the critical peak current characteristics that indicate unbalance or phase loss conditions, achieving comprehensive fault coverage with reduced processing time and computational burden.
4Reliability
If normalization operation is applied to difference measure, then the robustness against interference is improved, but the computational steps increase
Solution Approach 1:
The system applies normalization to the difference measure by dividing by the sum of current sums, transforming the raw difference into a dimensionless ratio. This parameter change makes the fault detection metric independent of absolute current magnitude variations caused by load changes or interference, thereby improving robustness. The normalization step, while adding one computational operation, uses a simple division that maintains efficiency while significantly enhancing reliability under varying conditions.
Data Source
AI summary
Various examples in accordance with the present disclosure provide systems, apparatuses, methods, and computer program products associated with detecting phase fault in a motor, such as unbalance phase and phase loss fault.