Single-Phase Overcurrent Cause Identification Using Wavelet Transform
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods fail to accurately identify the cause of single-phase overcurrents in electric cables, leading to potential permanent failures and increased power losses, as they cannot distinguish between incipient failures and other transient events.
Innovation Solution
A method involving wavelet transform and association coefficient calculation to determine an indicator feature vector from three-phase current signals, which then identifies the reason for the overcurrent by comparing with predetermined reference samples, using a db4 wavelet and five-layer decomposition to extract relevant indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only short-time single-phase overcurrent signal detection is performed, then the detection process is simple, but the identification accuracy of incipient failure is low
Solution Approach 1:
The patent segments the overcurrent signal analysis into multiple feature dimensions including waveform characteristics, frequency spectrum features, and time-domain statistics. By dividing the complex identification task into separate feature extraction and evaluation stages, the system achieves high identification accuracy without requiring overly complex detection methods.
Solution Approach 2:
The patent transitions from single-dimensional current magnitude detection to multi-dimensional signal analysis by incorporating waveform shape, frequency components, and temporal patterns. This dimensional expansion enables accurate distinction between incipient failures and normal transient events while maintaining manageable system complexity through structured feature processing.
2Measurement precision
If wavelet transform and association coefficient calculation are used to accurately identify overcurrent causes, then the identification accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary wavelet decomposition and feature extraction before association coefficient calculation. By pre-processing the signal to extract relevant features and organize data structures in advance, the system reduces the computational burden during the actual identification phase, achieving high accuracy with optimized power consumption.
Solution Approach 2:
The patent extracts only the essential features from the overcurrent signal using wavelet transform, such as singularities and characteristic coefficients, rather than processing the entire signal. This selective extraction of critical information maintains high identification accuracy while significantly reducing computational power requirements.
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
Accurately determines the cause of single-phase overcurrents, enabling timely intervention to prevent permanent failures, reducing power losses and extending the service life of electric grid lines.
Implementation Method 1
performing a wavelet transform on the three-phase current signals in the electric cable by using a db4 wavelet; performing a five-layer discomposing on the transformed three-phase current signals
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
Provided are a method for identifying an overcurrent in an electric cable and a device for the same. The method includes: detecting whether a single-phase overcurrent occurs in three-phase current signals; determining an indicator feature vector sample of an overcurrent phase current signal in a case that it is detected that the single-phase overcurrent occurs in the three-phase current signals; calculating association coefficients between the indicator feature vector sample and predetermined indicator vector reference samples of indicators, where the indicator vector reference samples respectively correspond to reasons for the single-phase overcurrent; calculating association degrees between the indicator feature vector sample and the predetermined indicator vector reference samples based on a predetermined indicator weight vector and the association coefficients corresponding to the indicators; and finding a reason for the single-phase overcurrent, which corresponds to an indicator vector reference sample having a maximal association degree. Hence, an incipient failure of the electric cable is identified.