Automotive Seat Pressure Mapping Automation
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Solution Overview
Problem
The manual separation and alignment of pressure map data from automotive seating into zones and mapping these against human body models is a lengthy and error-prone process, necessitating an automated solution for efficient data measurement and alignment.
Innovation Solution
A pressure mapping system that automatically aligns pressure sensor data with seating images and human body models by analyzing pressure maps to extract features, reducing initial setup requirements and providing consistent measurements, utilizing capacitive pressure sensors and digital signal processing for accurate pressure measurement and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual separation and alignment of pressure map data into zones and mapping against human body models is performed, then measurement precision can be achieved, but the process becomes lengthy and error-prone
Solution Approach 1:
The patent replaces manual mechanical alignment operations with automated image processing and pattern recognition algorithms. The system automatically detects seating features in images, extracts corresponding pressure map data, and aligns them through computational methods, eliminating the need for manual zone separation and mapping while maintaining high precision.
Solution Approach 2:
The system enables self-alignment through automated feature detection and matching. The pressure mapping system automatically identifies seating features, extracts relevant data, and performs alignment without requiring manual intervention, making the system self-sufficient in the alignment process.
2Manufacturing precision
If manual zone separation and mapping is performed, then detailed pressure analysis is possible, but the process becomes complex and error-prone
Solution Approach 1:
The patent replaces complex manual zone separation and mapping operations with automated image processing algorithms. The system uses computational methods to detect seating features, extract pressure map data, and perform alignment, significantly reducing process complexity while maintaining or improving alignment accuracy.
Solution Approach 2:
The patent introduces an automated image processing and data extraction system as an intermediary between the pressure sensors and the human body model mapping. This intermediary automatically performs feature detection, data extraction, and alignment, simplifying the overall process while ensuring precise zone alignment.
3Productivity
If automated pressure mapping is implemented, then productivity and consistency are improved, but initial setup requirements increase
Solution Approach 1:
The system is designed to be self-configuring through automated feature detection and alignment algorithms. Once the basic hardware is in place, the system automatically detects seating features, extracts pressure map data, and performs alignment without requiring extensive manual setup, thereby achieving high productivity with reduced setup complexity.
Solution Approach 2:
The patent incorporates preliminary automated calibration and feature detection routines that are executed automatically during the first use. The system pre-identifies seating features and establishes alignment parameters through automated processes, reducing the burden of initial setup while enabling high-speed data processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates rapid and consistent development of automotive seating products by providing higher quality contact areas, lower peak pressures, and smaller pressure distributions, enabling quality assurance and design evaluations through automated data analysis and comparison with historical data.
Implementation Method 1
utilizing capacitive pressure sensors and digital signal processing for accurate pressure measurement and visualization
Data Source
AI summary
A pressure sensor measures the surface pressure distribution of a body supported by a surface, for example a person sitting on an automotive seating. In one approach, a pressure mapping system presents this pressure data in the form of a pressure map. The pressure map can be aligned to an image of the automotive seating including measurement zones of interest. The measurement zones of interest are mapped onto a human body model, which may include various body zones. In this way, the pressure distribution on different body zones can be visualized and interpreted to assess the performance of the automotive seating.