Transformer Winding Event Localization Using UHF Sensor Timing
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Solution Overview
Problem
Power grid components, such as transformers, experience system events like partial discharges due to aging, which can indicate insulation degradation and predict future failures, but existing detection methods lack precision in locating these events within the components.
Innovation Solution
A system utilizing ultra-high frequency sensors to detect electromagnetic emissions from power component windings, processing device to determine event parameters based on sensor measurements, and generating estimates of event positions within the component, including noise reduction techniques like the Savitzky-Golay filter to improve localization accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection methods are used to detect system events in power components, then detection capability is provided, but localization precision of events within components deteriorates
Solution Approach 1:
The detection system is segmented into multiple independent sensors positioned at different locations within the power component. Each sensor independently detects electromagnetic emissions and provides localization data, with the system determining event positions by combining measurements from multiple sensor segments to achieve precise three-dimensional localization
Solution Approach 2:
A processing device acts as an intermediary between the sensors and the final localization output. The processing device receives raw sensor measurements, applies noise reduction algorithms (Savitzky-Golay filter), determines arrival times of emissions at each sensor, and computes the precise position of system events based on time differences across multiple sensors
2Measurement precision
If noise reduction techniques are applied to improve event localization accuracy, then measurement precision is improved, but processing complexity increases
Solution Approach 1:
Noise reduction processing is performed preliminarily on sensor measurements before arrival time determination. The Savitzky-Golay filter is applied to raw sensor data to reduce measurement noise in advance, ensuring that subsequent arrival time calculations and localization computations are based on cleaned, high-quality signals
Solution Approach 2:
The system changes the temporal parameters of signal processing by defining arrival windows for each sensor and applying time-dependent filtering. The Savitzky-Golay filter modifies the signal in the time domain, and the system determines arrival times by analyzing signal characteristics within specific time windows, transforming raw measurements into precise temporal events
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
Enables precise detection and localization of system events, facilitating timely maintenance and repair by accurately identifying the positions of partial discharge events within power grid components, thereby preventing potential failures.
Implementation Method 1
the plurality of sensors includes ultra-high frequency sensors configured to detect high frequency electromagnetic waves
Data Source
AI summary
Disclosed herein are methods, systems, and devices for system event detection associated with power grid components. Methods include detecting, at a plurality of sensors, emissions from a system event associated with at least one winding of a power component. Methods also include determining, using a processor, a plurality of event parameters based, at least in part, on measurements made by the plurality of sensors, the event parameters identifying arrival times of the emissions at each of the plurality of sensors. Methods further include generating, using the processor, an output identifying an estimate of a position of the system event within the power component, the estimate being generated based, at least in part, on the arrival times identified by the plurality of event parameters.