Fault diagnosis method for switching current circuit based on improved FastICA

A technology of switching current and circuit faults, which is applied in the field of fault diagnosis of switching current circuits, can solve the problems of long time consumption and heavy algorithm workload, achieve fast convergence speed, good separation effect, and improve the efficiency of fault diagnosis

Active Publication Date: 2019-01-11
CHANGSHA UNIVERSITY
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Problems solved by technology

[0004] In the fault diagnosis process, the above methods all have a common problem, that is, the data involved is massive,

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  • Fault diagnosis method for switching current circuit based on improved FastICA
  • Fault diagnosis method for switching current circuit based on improved FastICA
  • Fault diagnosis method for switching current circuit based on improved FastICA

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Embodiment 1

[0067] Basic Principles of Independent Component Analysis

[0068] ICA is a signal processing method developed from blind signal separation in recent years. It can be regarded as an extension of PCA. It transforms data into mutually independent directions. Independent. For a set of n-dimensional observation data, ICA decomposes n-dimensional random signals into a set of linear combinations of statistically independent random variables by looking for directions that can make the data independent of each other in the feature space. Compared with the disadvantage that PCA can only use the second-order statistics of data, ICA uses high-order statistical information, which is more conducive to the decomposition of observed signals.

[0069] Let a group of observation signals X={x 1 ,x 2 ,L,x m} is the source signal S={s 1 ,s 2 ,L,s n}, assuming that the i-th observation signal is linearly mixed with n independent components S:

[0070] x 1 =a i1 the s 1 +a i2 the s 2 +...

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Abstract

The invention discloses a fault diagnosis method for a switching current circuit based on improved FastICA. The fault diagnosis method comprises the steps that firstly, collected circuit frequency domain response data are subjected to centralization and whitening preprocessing; then an independent component analysis technology is utilized to find the maximum non-Gaussian direction of the data, animproved FastICA algorithm is applied to extract fault features of the switching current circuit, and a projection tracing technology is combined to achieve successful dimension reduction of originaldata; and finally, aiming at the two situations of not considering the circuit tolerance and considering the circuit tolerance, different diagnostic steps are given to complete fault classification and identification. Simulation experimental results show that a proposed fault extraction method can obtain the optimal fault features, and shows better performance than other feature extraction methods, and the fault diagnosis efficiency of the switching current circuit is advantageously improved.

Description

technical field [0001] The invention relates to an improved FastICA-based switching current circuit fault diagnosis method. Background technique [0002] With the development of analog-digital mixed-signal integrated circuits, the analog circuit part of the system is required to have a standard digital CMOS integration process, and the analog part in the mixed-signal circuit can be realized by switching current technology using the same low-cost digital CMOS process as the digital part. , Switched Current (Switched Current, SI) circuit belongs to current mode analog sampling data signal processing technology, as an alternative technology of switched capacitor technology, it uses discrete time sampling data to process continuous time analog signal, with low voltage, low power consumption, high speed , Small chip area, simple current summation operation, no need for linear floating capacitors, fully compatible with standard digital CMOS technology, etc., which is conducive to ...

Claims

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Application Information

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IPC IPC(8): G01R31/28G01R31/316
CPCG01R31/2834G01R31/2836G01R31/2846G01R31/316
Inventor 龙英熊跃军李正大尹江平
Owner CHANGSHA UNIVERSITY
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