Residential Load Identification for Nuisance Breaker Tripping
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Solution Overview
Problem
Residential fault diagnostics tools are unable to clearly identify specific loads causing unwanted tripping or nuisance tripping conditions in electronic circuit breakers, leading to cumbersome and time-consuming troubleshooting processes for homeowners and electrical contractors.
Innovation Solution
A system comprising a residential fault diagnostics tool connected to a residential power distribution panel via electrical outlets, paired with a mobile device or laptop running a classification analyzer application, which records and analyzes electrical conditions to identify the tripping load by matching it with known loads, providing a likelihood match and facilitating replacement with less interfering loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional fault diagnostics tools are used to detect tripping conditions, then fault detection capability is provided, but specific load identification capability is lost
Solution Approach 1:
The system segments the fault detection process into two distinct phases: first detecting the tripping condition using traditional methods, then separately identifying the specific load causing the trip through classification analysis. This segmentation allows both fault detection and load identification to be performed without compromising either capability.
Solution Approach 2:
The system introduces an intermediary classification analyzer that processes electrical characteristics and waveforms captured during tripping events. This intermediary component bridges the gap between generic fault detection and specific load identification, enabling the system to determine whether the tripped load is a nuisance trip source without losing either detection accuracy or identification capability.
2Loss of time
If manual load identification methods are used by following branch circuits, then specific load can be identified, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system enables self-service load identification by automatically capturing electrical characteristics during tripping events and performing classification analysis without requiring manual intervention. The device autonomously determines the specific load causing the trip, eliminating the need for technicians to manually follow branch circuits and test each load individually.
Solution Approach 2:
The system performs preliminary action by capturing and storing electrical waveforms and characteristics at the moment of tripping, before any manual troubleshooting begins. This preliminary data capture enables rapid automated analysis that identifies the problematic load instantly, saving significant time compared to manual methods.
3Measurement precision
If automated classification analysis is implemented, then load identification accuracy improves, but device complexity increases
Solution Approach 1:
The system achieves universality by integrating multiple functions into a single device: traditional fault detection, electrical characteristic capture, waveform recording, and automated classification analysis. This multi-functionality allows the device to perform load identification accurately without requiring separate specialized equipment, thereby managing complexity while maintaining high identification accuracy.
Data Source
AI summary
A system for identification of loads in a residential branch of electrical circuit including a plurality of electrical outlets is provided. It comprises a residential power distribution panel comprising an electronic circuit breaker. The electronic circuit breaker may experience unwanted tripping in the residential branch of electrical circuit. The system further comprises a residential fault diagnostics tool connected to the residential branch of electrical circuit. It can record, store, experience electrical conditions which are also experienced by the electronic circuit breaker. The system further comprises a communicating device to display relevant diagnostics information for an end user. The mobile device is configured to be in wireless communication with the residential fault diagnostics tool. The mobile application (APP) includes a classification analyzer for the identification of the loads. A decision of the identification is provided on the mobile application (APP).