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Fault diagnosis method and apparatus

A fault diagnosis and fault technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as difficulty in finding, constructing models and improving classification accuracy, and reducing fault diagnosis accuracy.

Inactive Publication Date: 2017-08-18
SUZHOU UNIV
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Problems solved by technology

At present, the linear SVM feature selection method is mainly used in combination with SVM for fault diagnosis, but this method is linear, and the industrial process itself is nonlinear, so it is not easy to find the most important features for constructing models and improving classification accuracy. Causes difficulties and reduces the accuracy of fault diagnosis

Method used

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  • Fault diagnosis method and apparatus

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Embodiment Construction

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0070] see figure 1 A schematic flowchart of a fault detection method disclosed by an embodiment of the present invention is shown.

[0071] Depend on figure 1 It can be seen that the present invention includes:

[0072] S101: Obtain normal training samples and fault training samples.

[0073] Collect normal training samples from industrial processes and faulty training samples

[0074] Among them, N 1 and N 2 Denote the sample numbers of normal trai...

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Abstract

The invention discloses a fault diagnosis method and apparatus. According to the method and the apparatus, feature selection is combined with a support vector machine; by utilizing difference between features, the feature related to a fault are selected out; large difference represents that the feature has a very large deviation with that in a normal condition and is possibly an important reason for causing the fault, so that the influence of useless features on a classification result is reduced; and important features related to the fault can be selected out more easily, so that the fault diagnosis precision is improved.

Description

technical field [0001] The present application relates to the field of industrial systems, and more specifically, to a fault diagnosis method and device. Background technique [0002] Faults in industrial systems will not only affect product quality and cause economic losses, but may also endanger personal safety. Therefore, fault diagnosis has become a research branch in the field of automation. In view of the rapid development of industrial system automation and sensors, a large amount of process data can be generated through the control system, and data-driven process monitoring methods have been widely used. This type of method is to use the collected process data to complete fault detection and fault diagnosis by using multivariate statistics and machine learning methods. [0003] Fault diagnosis can actually be regarded as a classification problem. Support Vector Machine (SVM) is a classifier with good generalization ability and has been widely used in fault diagnosis...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2411
Inventor 张莉薛杨涛王邦军张召李凡长姚望舒
Owner SUZHOU UNIV
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