Acoustic Mesh Estimation for Indoor Temperature and Airflow Mapping
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Solution Overview
Problem
Existing methods for measuring temperature and airflow distributions in a target space, such as an indoor environment, are inefficient and lack accuracy due to insufficient data constraints in estimating these parameters.
Innovation Solution
An environmental measuring device that utilizes a sound wave transceiver unit to transmit and receive detection sound waves, a setter to divide the space into virtual meshes, and an estimator to estimate temperature and airflow distributions using a prediction method with additional constraint conditions, including measured temperature values and airflow amounts, to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a virtual mesh with a large number of sections is used to estimate temperature and airflow distribution, then measurement precision is improved, but the system becomes underdetermined when the number of unknowns exceeds the number of equations
Solution Approach 1:
The target space is divided into multiple sections forming a virtual mesh, allowing temperature and airflow to be estimated at different spatial resolutions. The system can switch between a first virtual mesh with more sections (higher precision) and a second virtual mesh with fewer sections (lower precision), enabling flexible adaptation to different measurement requirements while maintaining mathematical solvability.
Solution Approach 2:
The system changes the parameter of virtual mesh section count to balance precision and reliability. By selecting appropriate mesh granularity and applying constraint conditions, the system optimizes the relationship between the number of unknowns (temperature and airflow values at each section) and the number of equations (sound wave propagation measurements), ensuring the system remains determined or overdetermined.
2Measurement precision
If constraint conditions are added to the prediction method, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system incorporates constraint conditions that provide feedback to the estimation process. These constraints (such as physical laws, boundary conditions, or previously measured values) guide the prediction method to produce more accurate results by correcting or refining the estimates based on additional information about the target space's physical characteristics.
Solution Approach 2:
Constraint conditions are prepared in advance based on known properties of the target space (such as fixed boundary temperatures, known airflow patterns, or physical limitations). These preliminary constraints are then applied during the estimation process to improve accuracy without requiring real-time complex calculations.
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
Enhances the accuracy of temperature and airflow distribution measurements by employing constraint conditions and a generalized inverse matrix, allowing for precise estimation even with more unknowns than equations, thereby improving measurement precision.
Implementation Method 1
A method of generating a virtual mesh including a plurality of sections divided from a target space and obtaining a temperature and an airflow of the target space, based on a time of flight and a propagation distance of detection sound waves passing through each section of the virtual mesh
Implementation Method 2
obtain a temperature and an airflow of the target space, based on a time of flight and a propagation distance of detection sound waves
Data Source
AI summary
An environmental measuring device includes a sound wave transceiver unit, a setter, and an estimator. The sound wave transceiver unit transmits and receives detection sound waves. The setter divides the target space into sections, and sets a first virtual mesh. The estimator estimates temperature or airflow distribution in the target space, based on a time of flight of the detection sound waves passing through a section of the first virtual mesh. The estimator estimates temperature or airflow in each of the sections of the first virtual mesh, using a predetermined prediction method and a constraint condition. The constraint condition includes at least one of a value representing temperature or airflow in a second virtual mesh having fewer sections than the first, an amount of air flowing in at least one section of the first virtual mesh, and at least one measured temperature value in the first virtual mesh.