Multi-Substrate Sensor Signal Filtering for Noise-Accurate Sensing
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Solution Overview
Problem
Conventional technologies face challenges in properly acquiring measurement data from sensors due to noise interference.
Innovation Solution
A sensing apparatus with a dual-substrate configuration, including low-pass filters and conversion circuits, is employed to remove noise from sensor signals and convert them into digital form, utilizing a control unit for data processing and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If measurement data is acquired directly from sensors without noise filtering, then data acquisition speed is maintained, but measurement precision deteriorates due to noise interference
Solution Approach 1:
The sensing apparatus is divided into multiple independent sub-substrates, each handling specific sensor groups with dedicated low-pass filters and conversion circuits. This segmentation allows noise filtering to be applied locally to each sensor group without requiring a complex centralized processing system, thus improving measurement precision while maintaining manageable device complexity
Solution Approach 2:
Low-pass filters are applied to sensor signals before they reach the conversion circuits, performing noise removal in advance. This preliminary action ensures that only cleaned signals are converted to digital form and transmitted, improving measurement data quality without requiring complex post-processing operations
2Measurement precision
If multiple sub-substrates are used for sensor signal processing, then measurement precision is improved through noise filtering, but device complexity increases due to additional components
Solution Approach 1:
The system uses multiple sub-substrates where each substrate processes signals from specific sensors independently. Each sub-substrate contains its own low-pass filter and conversion circuit, allowing parallel processing of multiple sensor signals. This modular approach improves measurement precision for each sensor group while keeping individual substrate complexity low and manageable
Solution Approach 2:
Multiple sub-substrates are integrated onto a single main substrate that provides common power supply and control functions. This merging approach allows the system to benefit from multiple filtered and converted sensor signals while sharing common infrastructure, thus improving overall measurement precision without proportionally increasing total device complexity
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
Enables proper acquisition and analysis of sensor data, reducing noise interference and facilitating timely detection of abnormalities in monitored apparatuses.
Implementation Method 1
a low-pass filter configured to remove noise in the signals from the first input unit
Implementation Method 2
a conversion circuit configured to convert analog signals from the low-pass filter into digital signals
Data Source
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AI summary
Provided is a sensing device comprising: a first sub-substrate having a first input unit for inputting signals from a plurality of first sensors, a low-pass filter for removing noise of the signals from the first input unit, and a conversion circuit for converting analog signals from the low-pass filter into digital signals; a second sub-substrate having a second input unit for inputting signals from a plurality of second sensors, a low-pass filter for removing noise of the signals from the second input unit, and a conversion circuit for converting analog signals from the low-pass filter into digital signals; a main substrate for supplying electric power to the first sub-substrate and the second sub-substrate; and a control unit for outputting data based on the digital signals.