Equipment fault diagnosis method based on multidimensional segmentation fitting

Abstract

The invention discloses an equipment fault diagnosis method based on multidimensional segmentation fitting. The method successively comprises a fault diagnosis training step and a fault diagnosis operation step. The method realizes mode expression and distance threshold extraction functions of modeling through combining a multidimensional segmentation fitting algorithm and an optimized dynamic time bending algorithm by focusing on the essence of data form characteristics on the basis of equipment fault data, and realizes equipment data fault type identification and cause diagnosis functions by performing mode coupling through extracting form characteristics of discovered equipment abnormal data, thereby solving the problem of incapability of efficiently and accurately describing the similarity degree between fault data by use of a conventional fault diagnosis technology.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis, in particular to an equipment fault diagnosis method based on multidimensional segment fitting. Background technique [0002] In recent years, with the continuous innovation and growth of science and technology and the rapid development of social industrialization, more and more industrial industrialization systems have been installed in large-scale industrial production occasions, creating irreplaceable huge productivity in this application environment . Therefore, the maintenance work of these equipments is particularly important and arduous. However, too many hidden influencing factors may cause the failure or even failure of these system equipment. Therefore, the state, enterprises and institutions are paying more and more attention to the status detection and fault diagnosis of these important system equipment. [0003] Generally speaking, the structure of these devices is becoming...

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Problems solved by technology

[0009] In view of the problems and risks of the above-mentioned common fault diagnosis technologies, the present invention focuses on how to fully mine the potential intuitive expression form of data samples and the effectiveness of measuring the difference of fault modes, and tries to better solve the problem by establishing a new pattern matching technology. The efficiency of fault diagnosis is low and the identification accuracy is not high, which is conducive to the continuous maintenance of equipment in good condition

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