Surge Arrester State Evaluation Using Machine Learning
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Solution Overview
Problem
Operators of power systems face challenges in assessing the condition and remaining lifespan of surge arresters due to the complexity of the data generated by monitoring systems, which often requires specialized expertise. Additionally, surge arresters from different manufacturers and with varying designs complicate effective asset life cycle management.
Innovation Solution
A computer-implemented method for determining the operating state of a surge arrester using measurement values, which involves standardizing the data, extracting parameters, applying a machine learning algorithm to determine the state, and outputting recommendations for operation. This method enables automatic assessment and prediction of surge arrester behavior, facilitating timely maintenance or replacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If monitoring systems are used to track surge arrester conditions, then reliability of power systems is improved, but device complexity increases due to data management requirements
Solution Approach 1:
The patent introduces an intermediary evaluation system that acts as a mediator between the monitoring system and operators. This system automatically processes measurement data (leakage current, creepage current, temperature) and generates condition assessments, thereby simplifying the data management burden on operators while maintaining reliable surge arrester monitoring.
Solution Approach 2:
The evaluation system performs self-service by automatically analyzing measurement data from multiple surge arresters, extracting relevant parameters, and generating condition assessments without requiring specialized operator expertise. The system serves itself by managing the complexity of data interpretation internally.
2Measurement precision
If specialized expertise is required to evaluate surge arrester data, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs self-service evaluation by automatically processing measurement data and generating condition assessments without requiring external specialized expertise. The embedded evaluation logic within the system enables non-experts to obtain accurate assessments of surge arrester conditions.
Solution Approach 2:
The system transforms complex measurement data (leakage current, creepage current, temperature) into simplified condition parameters and assessments that can be easily interpreted by operators without specialized knowledge, while maintaining measurement precision through rigorous data processing.
3Device complexity
If manual evaluation methods are used for surge arresters, then device complexity is reduced, but loss of time increases due to specialist requirements
Solution Approach 1:
The system automatically performs condition assessments without requiring manual intervention by specialists. It self-services by collecting measurement data, processing it through evaluation algorithms, and generating results automatically, thereby eliminating time losses associated with specialist availability while maintaining evaluation quality.
Solution Approach 2:
The system performs preliminary evaluation actions by continuously processing measurement data and maintaining updated condition assessments ready for immediate retrieval, eliminating the time delay that would occur if specialists needed to conduct evaluations on demand.
4Adaptability or versatility
If surge arresters from different manufacturers are used, then adaptability is improved, but loss of information increases due to data standardization challenges
Solution Approach 1:
The evaluation system is designed with universality to handle measurement data from surge arresters of different manufacturers. It implements standardized data processing methods that can accommodate various data formats and measurement protocols, enabling multi-manufacturer compatibility while preserving the essential information needed for condition assessment.
Solution Approach 2:
The system transforms diverse manufacturer-specific measurement data into standardized condition parameters through normalization and parameter transformation. This process converts varied input data formats into uniform assessment metrics, preventing information loss while maintaining adaptability to multiple manufacturers.
Data Source
AI summary
The invention relates to a computer-implemented method for monitoring the status and evaluating the behavior of a surge arrester, the method comprising the following steps: providing measured values (S10) of one or more surge arresters; standardizing the provided measured values (S12); extracting parameters (S14) for characterizing each surge arrester from the standardized measurement values; determining a state of each surge arrester (S16) using a machine learning algorithm; and outputting an operating recommendation for each surge arrester (S18) based on the determined state of the surge arrester. (FIG. 1)