Indoor air cleaning method
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Solution Overview
Problem
Existing air purification systems struggle to efficiently achieve clean room level cleanliness in indoor environments while optimizing installation cost, power consumption, and noise levels.
Innovation Solution
An indoor air cleaning system integrated with gas detection modules and a cloud computing service device that intelligently determines the optimal number and cycle of air cleaning devices, regulating actuation time, airflow volume, and noise level to reach clean room cleanliness levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple air cleaning devices are deployed to achieve clean room level cleanliness, then air purification effectiveness is improved, but installation cost and device complexity increase
Solution Approach 1:
The system dynamically adjusts the number and operation cycles of air cleaning devices based on real-time air quality detection data. The cloud computing service device calculates the optimal number of devices needed and their sampling cycles, allowing the system to achieve clean room level purification only when necessary, rather than continuously operating multiple devices. This dynamic adaptation resolves the contradiction by making device deployment flexible rather than fixed.
Solution Approach 2:
The system changes operational parameters (actuation time period, wind speed, noise level) based on detected air pollution levels. When air quality is good, fewer devices operate at lower power; when pollution increases, more devices activate at higher power settings. This parameter adjustment allows the system to maintain purification effectiveness while reducing overall device complexity and installation cost requirements.
2Reliability
If air cleaning devices operate continuously to maintain clean room cleanliness, then air quality is improved, but power consumption increases
Solution Approach 1:
The cloud computing service device determines optimal sampling cycles for air cleaning devices based on air quality conditions. Instead of continuous operation, devices operate periodically with varying intervals - more frequent sampling when pollution is detected, less frequent when air quality is good. This periodic action maintains air quality reliability while dramatically reducing overall power consumption compared to continuous operation.
Solution Approach 2:
The system implements closed-loop feedback where gas detection modules continuously monitor air quality, transmit data to the cloud computing service device, which then adjusts the operation cycles of air cleaning devices accordingly. This feedback mechanism ensures air quality is maintained at clean room levels only when necessary, avoiding unnecessary power consumption during periods of good air quality while responding quickly when pollution occurs.
3Productivity
If air cleaning devices operate at high wind speed to achieve rapid purification, then air cleaning efficiency is improved, but noise level increases
Solution Approach 1:
The system dynamically adjusts wind speed parameters based on real-time air quality detection. When air pollution is detected, the cloud computing service device increases wind speed to maximize cleaning efficiency. When air quality is good, wind speed is reduced to minimize noise. This dynamic parameter adjustment resolves the contradiction by making wind speed variable rather than fixed at high levels.
Solution Approach 2:
The system changes operational parameters including wind speed and noise level based on detected air pollution conditions. The cloud computing service device calculates optimal parameter combinations that achieve sufficient purification efficiency while minimizing noise disturbance. This parameter optimization allows the system to adapt between high-efficiency/high-noise and low-efficiency/low-noise modes as conditions require.
Data Source
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AI summary
An indoor air cleaning method is disclosed and includes following steps: a. providing an indoor air cleaning system for performing air pollution detection and cleaning treatment in an indoor field (A); b. intelligently calculating and comparing based on a field air quality database to provide reference suspended particulate (PM) air quality data and determine a number of the air cleaning devices (2) in the indoor field (A) and a sampling cycle; c. confirming whether the gas state of the air pollution in the indoor field (A) reaches a cleanliness requirement of clean room level ZAPClean room 6+, 7+, 6, 7, 6- or 7-; d. determining the optimal number of the air cleaning devices (2) and the sampling cycle to implement air pollution cleaning treatment; and e. testing a verification of the air pollution data in the indoor field (A), and providing the verification for a third-party testing unit to test.