Mechanical fault diagnosis method based on collaborative mechanism immune particle swarm network

Abstract

The invention relates to a mechanical fault diagnosis technology, in particular to a mechanical fault diagnosis method based on a collaborative mechanism immune particle swarm network. The problems that according to an existing mechanical fault diagnosis technology, requirements for the number of fault samples are high, and the diagnosis accurate rate is low are solved. The mechanical fault diagnosis method based on the collaborative mechanism immune particle swarm network includes the following steps that (1) mechanical fault samples collected by a sensor are taken as antigens; (2) appetencies between the antigens and antibodies of the immune network are calculated; (3) low-frequency variation and antibody recombination are performed on subgroup bodies A with large appetencies, particle swarm optimization and antibody recombination are performed on subgroup bodies B with small appetencies, and therefore a new antibody group is obtained; (4) the new antibody group is adjusted through the immune network; (5) the step (2), the step (3) and the step (4) are executed circularly; (6) the mechanical fault samples collected by the sensor are input into the new immune network. The mechanical fault diagnosis method is suitable for mechanical fault diagnosis.

Description

technical field [0001] The invention relates to a mechanical fault diagnosis technology, in particular to a mechanical fault diagnosis method based on an immune particle swarm network of a cooperative mechanism. Background technique [0002] With the development of industrial production and science and technology, electromechanical equipment has become more and more sophisticated, and the level of automation has also increased accordingly. Once the mechanical and electrical equipment fails, it will not only cause damage to the equipment itself, but also cause serious production safety accidents and personal safety accidents. Therefore, mechanical fault diagnosis is of great significance for protecting electromechanical equipment and reducing safety accidents. Under the existing technical conditions, most of the mechanical fault diagnosis adopts the way of regular maintenance by experts. Practice has shown that due to the limitations of its own principles, this method gener...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem that the existing mechanical fault diagnosis technology has high requirements on the number of fault samples and low diagnostic accuracy, the present invention provides a mechanical fault diagnosis method based on the immune particle swarm network of the cooperative mechanism

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