Digital Image Testing for Electrical Distribution Board Suitability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing methods for testing the suitability of electrical distributors for connecting electric vehicle charging stations are inefficient, often requiring physical inspections and overwhelming customers with online forms, which can lead to unsuccessful installations and hinder the transition to electromobility.
Innovation Solution
A digital image-based testing method using object recognition modules, such as deep learning neural networks, to identify electrical components and free slots in the distributor, determining the suitability for installing a wallbox by analyzing images from mobile devices and providing test results via a communication network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a service technician performs a physical inspection of the electrical distribution box, then the suitability for wallbox installation can be determined, but travel time and inspection appointments are required
Solution Approach 1:
The patent creates a digital copy (image) of the electrical distribution box that can be analyzed remotely. Instead of requiring a technician to physically inspect the box, customers can capture an image and send it for automated analysis, eliminating the need for travel and on-site inspection while maintaining assessment accuracy
Solution Approach 2:
The patent replaces the mechanical/physical inspection process with an automated digital image recognition system. The object recognition module analyzes the distribution box image automatically, substituting the technician's manual inspection with an AI-based system that provides results without requiring physical presence
2Ease of operation
If customers fill out an online form about the condition of the electrical distribution box, then installation requirements can be checked, but customers feel overwhelmed and refrain from installing a wallbox
Solution Approach 1:
Instead of requiring customers to manually input detailed information about their distribution box, the system accepts a simple image copy of the box. The object recognition module then automatically extracts all necessary information from this image, making the process much easier for customers while ensuring complete data capture
Solution Approach 2:
The system enables customers to perform the assessment themselves by simply uploading an image of their distribution box. The automated object recognition module handles the complex analysis, allowing customers to independently determine wallbox installation suitability without needing to understand technical requirements or fill out complex forms
3Productivity
If an object recognition module is used to detect electrical components in the electrical distribution board, then remote testing is enabled and unnecessary inspections are reduced, but the complexity of the testing system increases
Solution Approach 1:
The patent introduces an intermediary object recognition module that acts as a bridge between the customer's simple image upload and the complex assessment requirements. This module handles the complexity of electrical component recognition internally, presenting a simple interface to customers while performing sophisticated analysis in the background
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A test method for an electrical distribution board (20) in a low-voltage network (80) is disclosed. The method comprises the following steps: obtaining a digital image (42) of the electrical distribution board (20), feeding the digital image (42) to a first object recognition module (50) to perform an initial object recognition in the digital image (42) to detect an electrical component (30, 31, 32, 33), obtaining a result of the initial object recognition, and outputting (140) a test result depending on the result of the initial object recognition. Furthermore, test modules, object recognition modules, and methods for training object recognition modules are disclosed.