3D Vehicle Damage Detection for OEM Deviation Assessment
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Solution Overview
Problem
Current vehicle damage assessment systems are inaccurate and time-consuming, relying on 2D probe measurements and manual estimation, which fail to capture all aspects of structural damage and require significant technician input, leading to potential underestimation of repair costs and inefficiencies.
Innovation Solution
A 3D point cloud capture and analysis system that compares a damaged vehicle's point cloud to an OEM standard, using machine learning algorithms to identify and quantify deviations, generate repair estimates, and provide a protocol for precise vehicle repair.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D probe measurements are used for vehicle damage assessment, then the measurement process is simple and quick, but the measurement precision and completeness of structural damage is insufficient
Solution Approach 1:
The patent transitions from 2D probe measurements to 3D laser scanning technology. The 3D scanner captures the entire vehicle frame structure in three dimensions, creating a comprehensive point cloud model that accurately represents all structural deviations. This dimensional upgrade enables complete coverage of the vehicle frame without missing any damage areas, directly resolving the measurement precision and completeness issue.
Solution Approach 2:
The patent creates a digital 3D copy (point cloud model) of the damaged vehicle frame by scanning it with a laser scanner. This digital replica can be compared against the OEM specification model to automatically identify all deviations. The copying approach eliminates the need for manual probing while maintaining high measurement precision across the entire structure.
2Reliability
If manual probe measurements are taken at predetermined points, then the measurement process is fast, but the reliability and completeness of damage assessment is limited
Solution Approach 1:
The 3D laser scanning system continuously captures data across the entire vehicle frame in a single sweeping motion, rather than taking discrete measurements at predetermined points. This continuous scanning ensures no damage is missed and provides complete coverage of the frame structure, significantly improving reliability while the automation reduces time loss through rapid data processing.
Solution Approach 2:
The patent replaces the mechanical probe measurement system with an optical 3D scanning system. The laser scanner uses light to capture the entire frame structure simultaneously, eliminating the need for manual probing at predetermined points. This substitution provides continuous, complete data capture across the entire vehicle frame, improving both reliability and efficiency.
3Measurement precision
If 3D point cloud scanning is implemented for complete vehicle frame measurement, then measurement precision and completeness improve, but device complexity and processing requirements increase
Solution Approach 1:
The 3D scanning system serves multiple functions: it captures the entire vehicle frame geometry, identifies all damage locations, quantifies deviations from OEM specifications, and generates repair documentation. This multi-functionality consolidates what would otherwise require multiple separate measurement and assessment tools into a single integrated system, making the increased complexity worthwhile.
Solution Approach 2:
The patent introduces a computer processing system as an intermediary that automatically compares the scanned 3D point cloud data against the OEM specification model. This intermediary handles the complex data processing, deviation detection, and analysis, eliminating the need for manual measurement and assessment. The intermediary system manages the complexity by automating the comparison process and generating comprehensive damage reports.
4Measurement precision
If comprehensive 3D scanning and analysis is performed, then repair estimation accuracy improves, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary 3D scanning and creates a complete digital model of the damaged vehicle frame immediately after collision. This preliminary action captures all damage information before any repair work begins, enabling accurate repair estimation and planning. By having the complete 3D data available upfront, the system avoids repeated measurements and ensures all damage is accounted for in the repair plan.
Solution Approach 2:
The system provides immediate feedback by automatically comparing the scanned 3D point cloud against the OEM specification model and highlighting all deviations. This real-time feedback mechanism identifies damage locations and quantifies deviations as the scanning occurs, enabling rapid assessment and accurate repair estimation without lengthy post-processing delays.
Data Source
AI summary
A vehicle damage detection system operating on a computer system for evaluating specific damage to a vehicle. The vehicle damage detection system capturing a 3D point cloud of a damaged vehicle with a 3D scanner and identifies one or more sites of vehicle damage based on comparison of the captured 3D point cloud of the damaged vehicle to a baseline 3D file by identifying points within the 3D point cloud of the damaged vehicle that deviate from an original equipment manufacturer (OEM) standard vehicle of the same type. The damage detection system can be used to determine and identify replacement parts and components and generate an estimate and parts list based on previously damaged vehicles having a similar damage pattern, allowing an improved method for vehicle damage assessment and repair.