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Data fusion based sensor fault identifying system and method

A sensor failure and data fusion technology, applied in the field of agricultural Internet of Things, can solve the problems of being vulnerable to high temperature, high humidity, pollution, sensors prone to failure, and difficult to guarantee the reliability, stability and accuracy of collected data, so as to reduce the Possibility, reduction of malfunction, and effect of improving reliability

Inactive Publication Date: 2017-07-18
JIANGSU UNIV
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Problems solved by technology

Due to the complex environment in which the agricultural Internet of Things system is located, the data collection and transmission process is vulnerable to harsh environments such as high temperature, high humidity, pollution, and electromagnetic interference, which makes the sensor very prone to failure, making the reliability, stability, and reliability of the collected data difficult. Accuracy cannot be guaranteed

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  • Data fusion based sensor fault identifying system and method
  • Data fusion based sensor fault identifying system and method
  • Data fusion based sensor fault identifying system and method

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Embodiment Construction

[0025] In order to make the content of the present invention more clearly understood, the present invention will be further described in detail below based on specific examples and in conjunction with the accompanying drawings.

[0026] The sensor fault recognition structure based on data fusion of the present invention is as follows: figure 1 Shown:

[0027] The present invention builds a greenhouse environment measurement and control system based on the Internet of Things, uses the environmental data collected by the system as the original data, performs data mining on the environmental information collected by the sensor, and utilizes the sensor node abnormal data fault identification method based on spatial similarity Find the outliers of the data collected by sensor nodes, use the sensor fault diagnosis method based on spatio-temporal correlation to realize sensor data prediction, and combine fault feature extraction to realize sensor fault diagnosis and fault point data ...

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Abstract

The invention discloses a cloud model based sensor fault identifying system and method and belongs to a field of agricultural IoT. According to the invention, fault identification of abnormal points is realized through space similarity of sensor node environment information and node information of the current moment is predicated according to time relevance of abnormal point history data. The node information is predicated by utilizing the space relevance among homogeneous sensor nodes and heterogeneous sensor nodes. An estimation value of the sensor node of the current moment is generated through combination of the predication information by utilizing a cloud model based data fusion method, so that fault diagnosis and data restoration of the sensor node are realized. The invention can realize abnormal point identification for sensor nodes in facility agriculture and can realize diagnosis and data restoration by utilizing the fault diagnosis method; data collection accuracy of the sensor nodes can be improved effectively and easiness and quickness are achieved. The invention can be applied to fault identification and diagnosis of abnormal data of the sensor nodes and realizes estimation of sensor abnormal data.

Description

technical field [0001] The invention belongs to the technical field of the agricultural internet of things, and in particular relates to a sensor fault identification system and method based on a cloud model. Background technique [0002] The sensor is an important part of the greenhouse environment measurement and control system for facility agriculture. The main object of its monitoring is the greenhouse environmental parameters. Therefore, the environmental data collected by the sensor has the characteristics of slow transformation and strong redundancy. Due to the complex environment in which the agricultural Internet of Things system is located, the data collection and transmission process is vulnerable to harsh environments such as high temperature, high humidity, pollution, and electromagnetic interference, which makes the sensor very prone to failure, making the reliability, stability, and reliability of the collected data difficult. Accuracy cannot be guaranteed. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24H04L29/08
CPCH04L41/0631H04L41/064H04L41/0677H04L67/12
Inventor 王纪章周金生李萍萍贺通王建平
Owner JIANGSU UNIV
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