Partial Discharge Signal Filtering for High-Noise HV Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Partial discharge detection in high voltage applications is challenging due to high noise levels and requires costly, complex equipment, making it difficult to distinguish between noise and partial discharge signals.
Innovation Solution
Transforming the signal from time to frequency domain, cutting frequencies above a defined threshold, and retransforming the truncated signal back to the time domain to analyze the information content, using methods like Shannon entropy to differentiate between noise and partial discharge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex and costly equipment is used for partial discharge detection, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and removes high-frequency noise components from the detected signal by applying a low-pass filter that eliminates frequencies above a defined threshold. This separation of useful partial discharge signals from harmful high-frequency noise allows for accurate detection using simpler equipment, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent transforms the signal from time domain to frequency domain and applies frequency threshold filtering, changing the parameter domain for analysis. By comparing information content in different frequency ranges and transforming back to time domain, the method achieves precise partial discharge detection with less complex equipment
2Measurement precision
If complex equipment is used for partial discharge detection, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent extracts only the relevant low-frequency components containing partial discharge information while removing high-frequency noise components. This selective extraction allows the use of simpler, less expensive detection equipment while maintaining high measurement precision for partial discharge events
Solution Approach 2:
The patent employs a cost-effective signal processing approach using standard filtering and transformation techniques rather than expensive specialized hardware. The method uses readily available computational resources to achieve precise partial discharge detection, reducing equipment costs while maintaining measurement accuracy
3Measurement precision
If signal processing is applied to distinguish partial discharge from noise, then measurement precision is improved, but loss of information may occur
Solution Approach 1:
The patent transforms the signal to frequency domain, applies selective filtering based on frequency thresholds, then transforms back to time domain. By comparing information content before and after filtering and using bidirectional transformation, the method maintains essential partial discharge information while removing noise, achieving precise discrimination without significant information loss
Solution Approach 2:
The patent compares the information content of the original signal with the filtered signal to verify that essential partial discharge information is preserved. This feedback mechanism ensures that the filtering process distinguishes partial discharge from noise while maintaining measurement accuracy and preventing information loss
Data Source
AI summary
A method for partial discharge recognition in high voltage applications and a high voltage unit using the method, includes the steps of detecting a signal, transforming the signal from time to frequency domain, cutting frequencies above a defined threshold, and retransform the truncated signal from frequency to time domain. The information content of detected and truncated signals is determined and compared.