Dual-fusion method for intelligent electric room sensor data

Abstract

The invention discloses a dual-fusion method for intelligent electric room sensor data, which comprises the following steps of: fusing multi-sensor data: after primary fusion of single-sensor data, performing further fusion, namely secondary system-level fusion, on the multi-sensor data subjected to primary fusion to ensure that an electric room monitoring system is more stable and reliable; in the multi-sensor data fusion process, the sensors can be of the same type or different types, so that the measurement results of the sensors for the same variable are different, the data measured by thesensors must be judged to determine whether the data is credible or not, and a statistical method is used for defining a relation matrix between the sensors. According to the invention, the biological fusion processing enables the data collected by the sensor data to be more accurate, stable and efficient, overcomes the discreteness and uncertainty of the original data, enables the correlation ofthe single sensor data to be stronger in time, and enables the reliability of the data to be stronger.

Description

technical field [0001] The invention relates to a double fusion method, in particular to a double fusion method of sensor data in an intelligent electric room, and belongs to the technical field of sensors. Background technique [0002] The concept of sensor data fusion was proposed in the 1970s, but people did not pay enough attention at that time. In recent years, with the rapid development of science and technology, multi-sensor data fusion technology has attracted widespread attention worldwide and has become a Emerging research directions. In terms of smart power houses, with the continuous advancement of my country's "Internet +" smart grid construction, the number of sensors in smart power houses is also increasing, and the sensors are gradually replacing traditional non-intelligent sensors with intelligent digital sensors. Therefore, it is more and more important to be able to fuse sensor data efficiently and reliably. [0003] However, in the smart electric room, ...

AI Technical Summary

Problems solved by technology

[0005] (1) The stability and accuracy of unfused single-sensor data are low, resulting in low reliability and effectiveness;

[0006] (2) Single-sensor data is more likely to be independent of the system in time and space, and becomes discrete and has no practical value;

[0008] (1) A unified fusion theory and an effective generalized fusion model and algorithm have not yet been established;

[0009] (2) The problem of fault tolerance in the fusion system has not been well solved;

[0010] (3) There are still many practical problems in the design of data fusion system

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