Method for determining lubricating grease content of motor bearing by using BP neural network

A BP neural network, motor bearing technology, applied in the direction of neural learning method, biological neural network model, neural architecture, etc., to achieve the convenient effect of the method of grease content

Active Publication Date: 2019-04-26
ANHUI UNIVERSITY
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Problems solved by technology

However, under normal conditions, when the motor is running, it is difficult to m

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  • Method for determining lubricating grease content of motor bearing by using BP neural network
  • Method for determining lubricating grease content of motor bearing by using BP neural network
  • Method for determining lubricating grease content of motor bearing by using BP neural network

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[0033] In order to deepen the understanding of the present invention, the present invention will be described in further detail below in conjunction with embodiments. The present embodiments are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0034] according to figure 1 , 2 As shown, this embodiment provides a method for determining the grease content of a motor bearing using a BP neural network, which is characterized in that it includes the following steps:

[0035] Step 1: Measurement of hollow volume of motor bearing and selection of grease content

[0036] First, use the water injection method to measure the hollow volume between the motor bearing rollers to be 7ml, and inject 6 different contents of grease into the motor bearing, respectively 0ml, 0.7ml, 1.4ml, 2.1ml, 2.8ml, 3.5ml;

[0037] Step 2: Data collection

[0038] Use the acceleration sensor to collect the vibration data of the motor bearin...

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Abstract

The invention discloses a method for determining the lubricating grease content of a motor bearing by using a BP neural network. The method comprises the following steps of 1) measuring the capacity of the motor bearing by means of a water injection method; 2) injecting lubricating grease with six different contents into the motor bearing separately, wherein the contents are 0 time, 0.1 time, 0.2time, 0.3 time, 0.4 time and 0.5 time the capacity of the motor bearing respectively; 3) using a vibration sensor for collecting vibration data of the motor bearing under different lubricating greasecontents; 4) extracting statistical characteristics of the vibration data; 5) constructing the BP neural network with double hidden layers, and utilizing the established neural network for establishing a functional relationship between the input statistical characteristics and the output lubricating grease content. By means of the method, the collected vibration data of the motor bearing can be utilized, the corresponding lubricating grease content of the motor bearing is effectively detected through the BP neural network, and the method has important significance for the maintenance and protection of the motor bearing.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of mechanical equipment, and in particular relates to a method for judging the lubricating grease content of a motor bearing by using a BP neural network. Background technique [0002] In modern production, motors, as a common mechanical device, are getting more and more attention. As a part of the supporting shaft, if the bearing cannot be found and eliminated when a fault occurs, it will not only cause damage to the mechanical equipment, but also bring huge hidden dangers to economic property and personal safety. The key to ensure the normal operation of the bearing is to start with its maintenance, and the most important material is grease. As a lubricating medium for separating rolling elements and rings, grease has an important influence on the life of bearings. It is estimated that more than 80% of the bearings are lubricated with grease, and its content is directly related to the running pe...

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Application Information

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IPC IPC(8): G01N33/30G06N3/04G06N3/08
CPCG01N33/30G06N3/04G06N3/08
Inventor 王辉林加剑蔡孟翔阚鑫
Owner ANHUI UNIVERSITY
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