Fault detection method for industrial system based on Euclidean distance multi-scale fuzzy sample entropy

A technology of Euclidean distance and industrial system, which is applied in the research field of system complexity to achieve the effect of overcoming one-sidedness, increasing inaccuracy and instability, and improving accuracy and stability
CN111122162BActive Publication Date: 2020-12-01HANGZHOU DIANZI UNIV
11 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HANGZHOU DIANZI UNIV
Publication Date
2020-12-01

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses an industrial system fault detection method based on Euclidean distance multiscale fuzzy sample entropy. According to the method provided by the invention, the complexity of atime sequence can be described from a plurality of time scales; meanwhile, compared with an existing multiscale entropy method and an existing composite multiscale entropy (FME) method, the method hasthe advantages that the stability and the accuracy of the calculation of multi-scale fuzzy sample entropy (FME) are remarkably improved. The method can be used for judging and detecting the fault type of an industrial system and analyzing the complexity of the time sequence.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the research field of system complexity, and relates to a method for describing the time series complexity of industrial system signals, in particular to an industrial system fault detection method based on Euclidean distance multi-scale fuzzy sample entropy. Background technique

[0002] The time series of bearing vibration signals is an important high-dimensional data type, which is a sequence composed of the sampling values ​​of a certain physical quantity of an objective object at different time points in chronological order. Quantitatively analyzing the complexity of a signal time series is a complex and important task for understanding the operation rules of a system. In order to analyze the characteristics of time series and distinguish the normal and chaotic behavior of the system, many years ago experts and scholars proposed many methods to measure the complexity of a system signal.

[0003] Multiscale Entropy (Multis...

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