Neural Network Sensor Signal Trimming for Environmental Compensation
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Solution Overview
Problem
Existing sensors face challenges in maintaining consistent sensitivity due to environmental conditions such as temperature, humidity, and stress, which affects the accuracy of signals generated by sensing elements.
Innovation Solution
A sensor system incorporating a first sensing element that generates a signal indicative of a specific stimulus, and a second sensing element that generates a signal indicative of an environmental condition affecting the sensitivity of the first sensing element. A neural network circuit adjusts the gain of the first signal based on the second signal to compensate for sensitivity variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor output is used directly without compensation, then device complexity is low, but measurement precision deteriorates due to environmental sensitivity variations
Solution Approach 1:
The patent replaces traditional mechanical compensation methods with a neural network-based electronic system. The neural network circuit processes sensor signals and environmental condition signals to generate compensated output, substituting complex analog compensation circuits with a programmable, adaptive computational approach that achieves higher precision without proportionally increasing hardware complexity
Solution Approach 2:
The patent introduces environmental condition sensors as intermediary elements that detect temperature, humidity, and other environmental factors. These intermediaries provide additional input signals to the neural network, enabling the system to understand and compensate for environmental effects on the primary sensor output, thereby improving measurement precision
2Measurement precision
If environmental compensation is implemented, then measurement precision improves, but device complexity increases due to additional sensing elements and processing circuits
Solution Approach 1:
The neural network circuit serves multiple functions simultaneously: it processes primary sensor signals, integrates environmental condition data from multiple sensors, performs compensation calculations, and generates corrected output. This multi-functionality consolidates what would otherwise require separate dedicated circuits for each task, reducing overall system complexity while maintaining high measurement precision
Solution Approach 2:
The patent merges the primary sensor signal processing with environmental condition monitoring in a single neural network architecture. By combining multiple input signals (primary sensor output and environmental conditions) into one unified processing system, the patent eliminates the need for separate compensation circuits and reduces the overall complexity of the sensor system
Data Source
AI summary
A sensor is provided, comprising: a first sensing element that is arranged to generate, at least in part, a first signal; a second sensing element that is arranged to generate, at least in part, a second signal; and a neural network circuit that is configured to output an adjusted signal based on the first signal and the second signal.