Synchronous Machine Health Monitoring Using Negative Sequence EMF
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Solution Overview
Problem
Conventional synchronous machine health monitoring methods fail to accurately detect inter-turn faults due to assumptions of sinusoidal winding distribution, leading to erroneous fault detection and potential unplanned outages, especially in critical applications like aviation engines.
Innovation Solution
A system and method for monitoring synchronous machine health by estimating the negative sequence back electromotive force (EMF) using sequence components of phase voltages and currents, which includes a data store for lookup values and a prognostic module to compute a machine health indicator, raising alarms for deviations from healthy states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional synchronous machine health monitoring methods assume sinusoidal winding distribution, then the monitoring system is simple to implement, but fault detection accuracy deteriorates under inter-turn fault conditions
Solution Approach 1:
The patent changes the monitoring approach from assuming sinusoidal distribution to calculating actual winding distribution parameters using sequence components. By computing negative sequence voltage and current components and deriving the actual winding distribution function, the system adapts to fault conditions without requiring complex hardware modifications, thus improving detection accuracy while maintaining reasonable system complexity
Solution Approach 2:
The patent replaces the mechanical assumption of sinusoidal winding distribution with an electrical calculation approach using sequence components. Instead of physically measuring or mechanically verifying winding distribution, the system uses electrical measurements (voltages and currents) and mathematical transformations to determine actual winding distribution, simplifying the physical system while improving accuracy
2Ease of manufacture
If synchronous machine models assume sinusoidal winding distribution, then model creation is straightforward, but the model becomes inaccurate under fault conditions leading to erroneous fault detection
Solution Approach 1:
The patent makes the model dynamic by allowing it to adapt to fault conditions. Instead of using a fixed sinusoidal assumption, the model dynamically calculates the actual winding distribution based on measured sequence components. This dynamic adjustment enables the model to remain accurate whether the machine is healthy or experiencing an inter-turn fault, improving reliability without significantly complicating model creation
Solution Approach 2:
The monitoring system performs self-verification by using its own measurements to detect faults. The system calculates negative sequence components from its measurements and uses these to determine actual winding distribution, enabling the model to self-adjust and self-verify its accuracy without external intervention, thereby improving reliability while maintaining ease of implementation
3Ease of operation
If conventional monitoring methods are used, then the system operates with simple assumptions, but inter-turn faults remain undetected until they cause unplanned outages
Solution Approach 1:
The patent implements preliminary fault detection by continuously monitoring negative sequence components and comparing actual winding distribution against healthy baseline values. This preliminary detection occurs before faults escalate to cause unplanned outages, allowing maintenance to be scheduled proactively. The system performs this monitoring with straightforward operations using standard electrical measurements and calculations
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables early detection of inter-turn faults in synchronous machines, reducing the risk of unplanned outages and allowing for timely maintenance by accurately assessing the health of the armature winding, even under asymmetrical fault conditions.
Implementation Method 1
estimating the negative sequence back electromotive force (EMF) using sequence components of phase voltages and currents
Data Source
Figure 1
Figure 2A~2B
Figure 3
AI summary
A method, system and computer program product for monitoring health of a synchronous machine is provided. The method includes receiving (402) a plurality of phase voltage values and a plurality of phase current values. The method then computes (404) a negative sequence voltage (Vn) based on the plurality of phase voltage values. The method also computes (406) one or more operating parameters based on at least one of the plurality of phase voltage values and the plurality of phase current values. The method retrieves (408) from a data store, one or more known Vn based on the one or more operating parameters. The method then computes (410) a machine health indicator based on the computed Vn and the one or more known Vn, and raises (412) an alarm based on the machine health indicator.