Rapid diagnosis rotary machine resonance method based on cross statistic analysis

Abstract

The present invention discloses a rapid diagnosis rotary machine resonance method based on cross statistic analysis. For vibration faults of a large-scale rotary machine device, the method comprises the steps of: preliminarily determining that the type of the vibration fault belongs to a power frequency vibration fault and the fault has no typical power frequency fault atlas expression through adoption of a typical atlas of a large-scale rotary machine measured by a vibration measurement probe; exporting at least two sets of complete starting-stop machine data, wherein there is not any work such as assembling regulation or field balancing in the multi-time test run period; and performing batch processing of the unit data set of each set of data, and performing cross statistic analysis between the internal portion of each set of data and each set of data to achieve rapid identification for the rotary machine resonance faults. The rapid diagnosis rotary machine resonance method can rapidly, accurately and effectively perform accurate identification of the power frequency faults of the rotary machine resonance.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of large rotating machinery, and in particular relates to a method for quickly diagnosing resonance based on multi-vibration trend data analysis of large rotating machinery. Background technique [0002] Large rotating mechanical equipment is the core equipment of modern enterprises such as petroleum refining, chemical industry, power generation, etc., and power frequency fault (also known as frequency conversion fault) is a common vibration fault of large rotating mechanical equipment. The large-scale rotating machinery system is a strong nonlinear complex system. There are many factors that cause failures, and the manifestations of failures are also diverse. There is no one-to-one correspondence between the causes of failures and symptoms. The complex coupling relationship makes the diagnosis of this problem more difficult and profoundly affects the safety and production efficiency of en...

AI Technical Summary

Problems solved by technology

The large-scale rotating machinery system is a strong nonlinear complex system. There are many factors that cause failures, and the manifestations of failures are also diverse. There is no one-to-one correspondence between the causes of failures and symptoms. The complex coupling relationship makes the diagnosis of this problem more difficult and profoundly affects the safety and production efficiency of enterprises.

[0003] At present, most of the research on power frequency fault diagnosis technology for large rotating machinery equipment is still in the stage of pure simulation and laboratory verification. The cause of vibration faults, due to the only or dominant vibration fault in the frequency spectrum structure, its frequency spectrum structure is usually very similar or even identical, and an accurate identification method cannot be given, resulting in the diagnosis and treatment of power frequency faults of rotating machinery equipment at the user site. , to eliminate the cause of the fault through the most primitive elimination method

[0004] The frequency spectrum display of resonance faults belongs to the above situation. The technical difficulties of fault diagnosis are mainly manifested in: the spectrum performance of the failure causes such as insufficient bearing tight force, loose rotor parts, and rotor cracks is similar and indistinguishable; The data, the analysis results are quite different from the theory, and cannot be clearly defined; due to the limitation of the insufficient number of vibration measuring probes and the single location, the difficulty of diagnosing resonance faults is further increased

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