Fault diagnosis method for centrifugal pump rotor system

Abstract

The invention discloses a fault diagnosis method for a centrifugal pump rotor system, particularly relates to a fault diagnosis method for the centrifugal pump rotor system based on variational mode decomposition and a kernel extreme learning machine, and belongs to the field of rotary machine fault diagnosis. The method mainly comprises the steps that S1, acquiring vibration acceleration signals(normal, rotor misalignment, rotor imbalance, bearing inner ring faults, bearing outer ring faults and bearing rolling body faults) of a centrifugal pump rotor system in a normal state and a fault state, and obtaining a time domain signal sample set; S2, carrying out variational mode decomposition on the obtained time domain signal sample set to obtain an intrinsic mode function component; S3, solving an energy value, a waveform factor, a pulse index, a margin coefficient, a peak factor and a kurtosis value for each intrinsic mode function component; S4, constructing a feature matrix, and normalizing the processed data; S5, training the fault diagnosis system of the centrifugal pump rotor system by adopting the training sample; S6, inputting the test sample or the real-time sample into thecentrifugal pump rotor system fault diagnosis model to diagnose the fault.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of rotating machinery, in particular to a method for fault diagnosis of a centrifugal pump rotor system based on variational mode decomposition and nuclear extreme learning machine. Background technique [0002] As a general-purpose rotating machinery product, centrifugal pumps are widely used in various industries, including petrochemical, water supply and drainage, agricultural irrigation, etc. According to statistics, about 21% of the electric power is used to drive various types of pumps, and centrifugal pumps are the most used type of pumps. The centrifugal pump rotor system mainly includes impellers, rolling bearings, shafts, couplings and other components. The rotor is the part with the highest failure rate of centrifugal pumps. Therefore, it is of great significance to improve the safety performance of production to carry out condition monitoring and fault diagnosis on the centrifugal pump ...

AI Technical Summary

Problems solved by technology

The traditional feed-forward neural network uses an iterative algorithm of gradient descent to challenge the weight parameters, which has obvious defects: the learning speed is slow, which increases the calculation time of the system; Generalization performance drops

These deficiencies become the bottlenecks restricting the application of feed-forward neural networks using iterative algorithms

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