Rotating equipment fault monitoring method and system based on big data and readable storage medium

Abstract

The invention relates to a rotating equipment fault monitoring method and system based on big data and a readable storage medium, and the method comprises the steps: setting a sampling interval time,generating multiple groups of sample data of different time nodes, and carrying out the standardization of the multiple groups of sample data, and obtaining standard sample data; obtaining historicalsample data through big data analysis, and establishing a regression model; inputting the standard data into a regression model to obtain a plurality of fault prediction samples; performing similaritycalculation on the plurality of fault prediction samples; classifying the sample data of which the similarity is smaller than a preset threshold value to obtain result information; and performing equipment fault diagnosis through the result information.

Description

technical field [0001] The invention relates to a method for monitoring faults of rotating equipment, in particular to a method, system and readable storage medium for monitoring faults of rotating equipment based on big data. Background technique [0002] Vibration fault diagnosis is an indirect diagnosis method based on vibration signal analysis. The vibration signal reaches the vibration sensor through a complex path of the mechanical system. The fault signal is inevitably disturbed during the transmission process. Uncertain fault diagnosis information after complex transmission is easily caused. Misdiagnosis, the occurrence of misdiagnosis will lead to over-maintenance or wrong maintenance, and even lead to major safety accidents. [0003] The existing fault diagnosis is only to detect the simple vibration signal of the rotating equipment, and based on this to monitor the fault of the rotating equipment, the monitoring fault diagnosis deviation is relatively large. The ...

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Problems solved by technology

[0002] Vibration fault diagnosis is an indirect diagnosis method based on vibration signal analysis. The vibration signal reaches the vibration sensor through a complex path of the mechanical system. The fault signal is inevitably disturbed during the transmission process. Uncertain fault diagnosis information after complex transmission is easily caused. Misdiagnosis, the occurrence of misdiagnosis will lead to excessive maintenance or wrong maintenance, and even lead to major safety accidents

[0003] The existing fault diagnosis is only to detect the simple vibration signal of the rotating equipment, and based on this to monitor the fault of the rotating equipment, the monitoring fault diagnosis deviation is relatively large. The vibration signal is vector decomposed, and the vibration vectors in different directions are analyzed and reconstructed separately, and the results obtained have large deviations.

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