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
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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

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  • 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

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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...

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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

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F2119/08G06F30/23
Inventor 王迪张玺
Owner PEKING UNIV
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