A diagnosis method and system based on machine failure

A diagnostic method and technology for machine faults, applied in instruments, computer parts, and pattern recognition in signals, etc., can solve problems such as noise pollution, gear tooth manufacturing errors, affecting the accuracy of fault diagnosis, and achieve the effect of improving accuracy.
CN108664936BActive Publication Date: 2020-09-01ZHEJIANG NORMAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG NORMAL UNIVERSITY
Publication Date
2020-09-01

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Abstract

The invention discloses a diagnosis method and system based on machine faults. The diagnosis method includes: obtaining observation signals of machine faults to be diagnosed; determining time-frequency grayscale images corresponding to each product function according to each observation signal; The time-frequency grayscale image corresponding to each of the product functions determines a time-frequency image pixel matrix; performing redundancy cancellation processing on the time-frequency image pixel matrix to obtain a redundancy cancellation image pixel matrix; through the scale-invariant feature, Determine the Gaussian image difference function, gradient magnitude and gradient direction according to the redundant cancellation image pixel matrix; determine multiple base images according to the Gaussian image difference function, gradient magnitude and gradient direction; determine according to multiple base images Image slices; input image slices into the support vector machine classification model to realize fault classification and diagnosis, and improve the accuracy of fault diagnosis.
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Description

technical field

[0001] The invention relates to the technical field of fault diagnosis, in particular to a diagnosis method and system based on machine faults. Background technique

[0002] Mechanical fault diagnosis is essentially a pattern recognition problem. It extracts features from different patterns (such as normal state, gear defect, bearing fault, rotor fault, etc.) and characterizes the data of each pattern.

[0003] At present, in order to carry out effective feature extraction, most of the fault diagnosis technologies often need to adopt some special technical methods, such as spectrum analysis, time-frequency analysis and filtering technology, etc., using these technical methods to achieve the purpose of detecting and obtaining the fault characteristic frequency . Typical fault characteristic frequency components include gear mesh frequency and its higher harmonic components, modulation components and so on. However, due to structural resonance, gear tooth man...

Claims

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