Adaptive Particulate Matter Collection Interval Control
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Solution Overview
Problem
Traditional portable particulate matter detectors use a fixed collection rate for air particulate matter data, which leads to inefficient energy consumption and inaccurate data collection, especially when particulate matter concentrations change frequently.
Innovation Solution
A collection method that adjusts the particulate matter collection rate in real-time based on changes in particulate matter concentrations, using a stepwise approximation method and table lookup to calculate a real-time collection cycle coefficient and collection interval time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed collection rate is used to collect air particulate matter data, then the device structure is simple and easy to operate, but the energy consumption is high and battery life is short (6-8 hours)
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed collection rate to a dynamic adaptive collection rate that automatically adjusts based on real-time particulate matter concentration variations. The system calculates variation rates and modifies collection intervals accordingly, making the collection rate flexible and responsive to environmental conditions rather than static.
Solution Approach 2:
The patent implements parameter changes by modifying the collection rate parameter based on calculated particulate matter concentration variations. When variations exceed thresholds, the system changes the collection rate from normal to high frequency, and vice versa, optimizing energy consumption while maintaining data quality through parameter adaptation.
2Device complexity
If a fixed collection rate is used, then the device complexity is low, but the data collection accuracy is insufficient when particulate matter concentration changes frequently
Solution Approach 1:
The patent implements feedback by continuously monitoring particulate matter concentration, calculating variation rates, and using this information to adjust the collection rate. The system establishes a feedback loop where detection results inform subsequent collection strategies, ensuring data accuracy is maintained during rapid concentration changes while reducing unnecessary collections during stable periods.
Solution Approach 2:
The patent applies dynamics by making the collection rate adaptive rather than static. The system dynamically adjusts collection frequency based on real-time analysis of concentration variations, enabling it to respond to changing environmental conditions and maintain measurement precision without requiring complex manual control mechanisms.
3Measurement precision
If the collection interval is shortened to capture rapid concentration changes, then the data accuracy improves, but the energy consumption increases and battery life decreases
Solution Approach 1:
The patent implements parameter changes by adjusting the collection interval parameter based on calculated variation rates. During periods of rapid concentration change, the system shortens the collection interval to capture important data. During stable periods, it extends the interval to conserve energy, thus optimizing the balance between measurement precision and battery life through adaptive parameter modification.
Solution Approach 2:
The patent applies dynamics by making the collection interval flexible and responsive to environmental conditions. Instead of using a fixed interval that either wastes energy or misses important changes, the system dynamically adjusts the interval based on real-time analysis of concentration variation rates, extending intervals during stability and shortening them during rapid changes.
4Ease of operation
If a fixed collection rate is used, then the control method is simple, but it cannot adapt to variations in particulate matter concentration in the air
Solution Approach 1:
The patent implements self-service by enabling the system to automatically adjust its own collection rate based on analyzed environmental conditions. The device performs self-diagnosis of concentration variation patterns and self-adjusts the collection strategy without external intervention, maintaining simplicity while achieving adaptability through autonomous decision-making based on calculated variation rates.
Solution Approach 2:
The patent applies dynamics by transforming the static fixed collection rate into a dynamic adaptive rate that automatically responds to concentration variations. The system maintains operational simplicity while gaining adaptability through automatic adjustment mechanisms that modify collection frequency based on real-time environmental analysis.
Data Source
AI summary
The present invention relates to a collection method for a particulate matter detector, including: performing normalized calculation on collected initial air particulate matter values, to calculate an initial particulate matter variation among the initial air particulate matter values; obtaining a real-time collection cycle coefficient by performing calculation on the initial particulate matter variation through a stepwise approximation method and table lookup, and calculating a real-time particulate matter collection interval time; then, collecting an air particulate matter value again after the real-time collection interval time, where the air particulate matter value collected at this time is a latest air particulate matter value; performing normalized calculation on the latest air particulate matter value and a data value displayed by the particulate matter detector, to calculate a real-time particulate matter variation; and obtaining a new real-time collection cycle coefficient by performing calculation on the real-time particulate matter variation through the stepwise approximation method and table lookup. According to the present invention, a particulate matter detector can adjust a collection interval time in real time as a concentration of particulate matters in the air changes, thereby improving an endurance capacity thereof.