Sensor Channel Selection With Quality Threshold Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Engineers face challenges in optimizing sensor arrangements for devices, as they need to select the right combination and quality of sensors to meet output requirements while minimizing costs and complexity, given the vast array of sensor options and their varying costs and accuracies.
Innovation Solution
A system and method that utilize machine learning to identify and assemble optimized sensor combinations by selecting sensor channels and determining threshold quality criteria, using a sensor optimizer to generate optimized sensor sets and sensitivity balancer to ensure cost-effective solutions that meet performance targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a comprehensive array of high-quality sensors is selected to meet output requirements, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the sensor selection process into distinct functional modules: a sensor optimizer that generates optimized sensor sets with threshold values, a channel selector that validates sensor combinations against output requirements, and a sensitivity balancer that determines quality thresholds. This segmentation transforms the overwhelming comprehensive selection task into manageable sequential steps, reducing device complexity while maintaining measurement precision through systematic evaluation of sensor combinations.
2Reliability
If more sensors are used to achieve required output states, then measurement precision and reliability are improved, but the number of sensors and cost increase
Solution Approach 1:
The patent implements partial action by determining threshold values for sensor quality criteria that define the minimum necessary sensor performance rather than requiring all sensors to exceed maximum quality levels. The sensitivity balancer identifies the precise quality threshold needed for each sensor channel to meet output requirements, eliminating excessive sensor quality specifications and reducing the number of high-cost sensors while maintaining reliability.
Solution Approach 2:
The system dynamically adjusts sensor quality parameter thresholds based on specific output requirements and sensor combination performance. The sensitivity balancer modifies the quality criterion thresholds for different sensor channels according to their individual contributions to output states, allowing the system to use fewer sensors by optimizing their quality parameters rather than uniformly specifying high-quality sensors across the board.
3Ease of manufacture
If multiple sensor combinations are evaluated to find the most cost-effective option, then cost efficiency is improved, but the time and computational resources required increase
Solution Approach 1:
The patent applies preliminary action by pre-generating optimized sensor sets with determined threshold values using the sensor optimizer before the actual sensor selection process. This preliminary optimization creates a filtered set of candidate sensor combinations that are already evaluated for cost-effectiveness and performance, allowing engineers to quickly select from pre-validated options rather than evaluating all possible sensor combinations from scratch, significantly reducing selection time while maintaining cost efficiency.
Solution Approach 2:
The system replaces manual sensor selection and evaluation processes with automated computational algorithms. The sensor optimizer, channel selector, and sensitivity balancer collectively substitute human engineering judgment with machine-based optimization that rapidly evaluates multiple sensor combinations, determines threshold values, and identifies cost-effective configurations without the time and resource expenditure required for comprehensive manual analysis.
Data Source
AI summary
A system and method are provided for identification of a combination of sensors suitable for achieving a set of output requirements, enabling assembly thereof. An arrangement of sensors is assembled according to an optimized sensor set, generated to define at least one sensor channel having a threshold value for at least one quality criterion. The sensor sets are generated by down-selection of the sensor channels from a previously tested set of available channels to a subset mapping to a set of required output states. Assignment of a threshold value for each sensor channel is based on a mapping of the value to a target value of a performance metric.