Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A temperature field prediction method based on sensor data fusion

A technology for sensing data and prediction methods, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of less consideration of the spatiotemporal dynamic coupling characteristics of the temperature system, difficult to obtain temperature prediction results, etc., and achieve accurate prediction. Effect

Active Publication Date: 2019-02-26
PEKING UNIV
View PDF2 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing technology has little consideration of the space-time dynamic coupling characteristics of the temperature system, and it is difficult to obtain more accurate temperature prediction results

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A temperature field prediction method based on sensor data fusion
  • A temperature field prediction method based on sensor data fusion
  • A temperature field prediction method based on sensor data fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] Below in conjunction with accompanying drawing, further describe the present invention through embodiment, but do not limit the scope of the present invention in any way.

[0050] The invention provides a temperature field prediction method based on sensing data fusion, and establishes a spatio-temporal prediction model composed of a global temperature change process and a local temperature change process. The global temperature change is described by the thermodynamic model, and the local temperature change is described by the time-space transfer learning model, so as to realize the comprehensive and accurate prediction of the engineering temperature system.

[0051] Taking a grain reserve depot in a certain area as an example, consider two granaries (L=2) with similar attributes in the grain depot, and select one of the granaries as the target granary, establish a grain temperature system prediction model, and realize the target granary Prediction of temperature syste...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a temperature prediction method based on a spatio-temporal condition autoregressive process, belonging to the technical field of industrial engineering. A spatio-temporal prediction model composed of global temperature change process and local temperature change process is established. The global temperature change is described by thermodynamic model, and the local temperature change is described by spatio-temporal transfer learning model, so that the engineering temperature system can be predicted comprehensively and accurately. The invention uses the existing temperature sensor data to predict the temperature system in a short time in the future, and can obtain the comprehensive and accurate information of the temperature system in a period of time in the future.It can solve the problem that the temperature system can not be accurately predicted due to the insufficiency of sensor data and partial missing of data in the engineering system.

Description

technical field [0001] The invention provides a temperature prediction method, in particular to a temperature prediction method utilizing existing sensing data and based on an autoregressive process of spatio-temporal conditions, and belongs to the technical field of industrial engineering. Background technique [0002] Temperature prediction technology plays an important role in engineering systems and has been widely used in processing and manufacturing, meteorology, grain storage and other fields. In engineering systems, temperature prediction technology provides important information for tasks such as monitoring product quality and improving system performance. [0003] The existing temperature prediction technology collects temperature data in an engineering system through wireless sensing equipment, and uses these existing data to establish a temperature prediction model to predict the temperature of the engineering system for a period of time in the future. In engine...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F2119/08G06F30/23
Inventor 王迪张玺
Owner PEKING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com