Sensor noise and fault judging method based on sparse representation

Abstract

The invention discloses a sensor noise and fault judging method based on sparse representation. The specific method includes the following steps: 1. an overcomplete atom library containing normal signals, noise and fault samples corresponding thereto is built through historical data; 2. based on a hypothesis that linear representation of unknown samples of some category can be effectively realized in a corresponding subspace by a plurality of samples of the category, sparse representation of a mixed signal collected by a sensor is performed with a built dictionary, i.e., atoms best matched with the signal to be decomposed is found out from the overcomplete atom library and are subjected to linear reconstruction to obtain a new representation mode; 3. a reconstruction error of the sample subjected to linear reconstruction is calculated, and an error of a new sample reconstructed by use of a data set of each kind of noise and fault samples is obtained; 4. data of the same kind of fault samples and data of the same kind of noise samples are used to perform training to calculate a corresponding reconstruction error value; and 5. noise and fault judgment is realized through calculation of the reconstruction error.

Description

technical field [0001] The invention relates to the technical field of gas sensor signal processing, in particular to a method for distinguishing sensor noise and fault based on sparse representation. Background technique [0002] As one of the three major components of information technology, sensor technology has been widely used. Sensors are equivalent to human sensory organs, which are used to perceive and measure various physical and chemical quantities and convert them into electrical signals, which are sent to computers or electronic circuits for processing to achieve the purpose of monitoring or control. With the rapid development of sensor technology, the variety of sensors is complete, the accuracy has been greatly improved, and the number of enthusiasts using sensors has also increased rapidly. The noise and failure of sensors have also attracted more and more attention. [0003] With the increasingly complex structure, expanding scale and higher degree of automa...

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Problems solved by technology

[0005]Aiming at the above problems, the present invention proposes a method for distinguishing sensor noise and fault based on sparse representation, so as to solve the problem that sensor noise and fault cannot be distinguished at present, and reduce Interference factors in sensor fault diagnosis, better troubleshooting, and better system operation

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