Hydraulic cylinder inner leakage fault diagnosis and evaluation method

Abstract

The invention relates to hydraulic cylinder leakage monitoring and inner leakage level classification, in particular, a hydraulic cylinder inner leakage fault diagnosis and evaluation method and belongs to the equipment health monitoring field. According to the method, wavelet decomposition and a BP neural network are used in combination; pressure signals of the inlet of a hydraulic cylinder are segmented through adopting a wavelet analysis method, and time-domain features of segments are extracted; and a hydraulic cylinder leakage level evaluation method is built through adopting a BP neural network method. As indicated by an experiment, the method is effective and can accurately realize diagnosis on the inner leakage of a hydraulic cylinder. According to the method, inner leakage of the hydraulic cylinder can be detected accurately through an inlet pressure sensor which is normally arranged in the hydraulic cylinder; and the level of the inner leakage of the hydraulic cylinder can be detected. The hydraulic cylinder inner leakage fault diagnosis and evaluation method is simple and practical, and can realize the detection of the inner leakage of the hydraulic cylinder. With the method adopted, with no extra sensors adopted, diagnosis on the inner leakage of hydraulic cylinders commonly used in the industry can be realized, and accidents caused by the inner leakage of the hydraulic cylinders can be avoided.

Description

technical field [0001] The invention relates to the field of equipment fault monitoring, in particular to a method for diagnosing and evaluating leakage faults in hydraulic cylinders. Background technique [0002] Hydraulic cylinders are commonly used actuators in construction machinery, and internal leakage is a common failure mode of hydraulic cylinders. Internal leakage will lead to the reduction of hydraulic cylinder pressure rise speed, hydraulic cylinder crawling, insufficient power supply, etc., which will seriously affect the working efficiency and safety of the machine. Timely identification of internal leakage in the hydraulic cylinder can ensure the normal operation of the hydraulic cylinder. The characteristics of the pressure signal at the inlet of the hydraulic cylinder are extracted by wavelet decomposition, and the classifier is established by using the BP neural network, which realizes the intelligent identification of the leakage in the hydraulic cylinder. ...

AI Technical Summary

Problems solved by technology

Internal leakage will lead to a decrease in the pressure rise speed of the hydraulic cylinder, crawling of the hydraulic cylinder, and insufficient power supply, which will seriously affect the working efficiency and safety of the machine. Timely identification of the internal leakage of the hydraulic cylinder can ensure the normal operation of the hydraulic cylinder

Images