MEMS Sensor Array Detection for Nonlinear Signal Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
MEMS sensors are often designed as single independent devices, limiting their nonlinear mapping capabilities to relatively simple tasks, constraining their technical advantages and market application possibilities in the Internet of Things era.
Innovation Solution
A detection apparatus comprising a plurality of MEMS sensors with a processing module that processes sensing signals across multiple sampling times, incorporating attenuation coefficients and a neural network-like structure to enhance nonlinear mapping and improve classification and recognition abilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If MEMS sensors are designed as single independent devices, then device simplicity and ease of manufacture are improved, but nonlinear mapping capabilities and classification recognition abilities are limited
Solution Approach 1:
The patent combines multiple MEMS sensors into a single integrated detection apparatus, merging their sensing capabilities to achieve enhanced nonlinear mapping functions. The sensors work together in a coordinated manner, sharing common structural elements and processing resources, which resolves the contradiction by maintaining relative simplicity while expanding functional versatility through collective operation.
Solution Approach 2:
The integrated detection apparatus achieves multi-functionality by enabling the sensor array to perform both simple detection tasks and complex nonlinear mapping operations. The same physical structure supports diverse application scenarios, from basic signal detection to advanced pattern recognition, thereby improving adaptability without proportionally increasing device complexity.
2Adaptability or versatility
If multiple MEMS sensors are integrated into a detection apparatus, then nonlinear mapping capabilities and classification recognition abilities are improved, but device complexity increases
Solution Approach 1:
The detection apparatus is segmented into functionally distinct modules: individual MEMS sensor elements, signal processing units, and data fusion components. This segmentation allows each component to be optimized independently while maintaining overall system simplicity. The modular structure reduces the complexity burden of integration by enabling independent design and manufacturing of subsystems.
Solution Approach 2:
The patent employs a nested structure where multiple sensor elements are integrated within a common housing and sharing framework. The sensors are arranged in a compact configuration where smaller sensor components are nested within the overall apparatus structure, minimizing space requirements and reducing the apparent complexity of the integrated system.
3Measurement precision
If signal processing incorporates multiple sampling times and attenuation coefficients, then sensing accuracy and reliability are improved, but processing complexity and calculation requirements increase
Solution Approach 1:
The system performs preliminary signal processing by pre-calculating attenuation coefficients and establishing processing algorithms before actual detection. Training data is processed in advance to create lookup tables and reference models, which reduces the complexity of real-time processing. This preliminary action allows the system to achieve high measurement precision without proportionally increasing operational processing complexity.
Solution Approach 2:
The detection apparatus incorporates self-calibration and automatic adjustment capabilities, where the system automatically determines optimal processing parameters based on incoming signals. The processing module adapts attenuation coefficients and sampling rates dynamically without external intervention, reducing the need for complex manual configuration and simplifying the user interface while maintaining high processing accuracy.
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
The apparatus achieves more reliable and accurate sensing results by fusing signals from multiple sensors, enhancing fault tolerance, environmental adaptability, and calculation speed, while improving the detection apparatus's precision and calculation force.
Implementation Method 1
a pressure sensing layer located on a side of the pressure sensing chamber along a direction of a depth of the pressure sensing chamber
Data Source
AI summary
The present disclosure provides a detection apparatus, a training method and a training apparatus. The detection apparatus includes a plurality of MEMS sensors configured to collect signals to be detected in real time and output sensing signals according to the signals to be detected; a processing module configured to receive the sensing signals of the plurality of MEMS sensors and determine a detection result of the detection apparatus according to the sensing signals of the plurality of MEMS sensors at each sampling time; wherein, there is a predetermined interval duration between two adjacent sampling times, and a sensing signal of each of the MEMS sensors at the current sampling time is related to a signal to be detected at the current sampling time, a sensing signal at the previous sampling time and an attenuation coefficient.