A method, system and device for abnormal diagnosis of equipment wear

Abstract

The invention discloses an equipment wear abnormity diagnosis method, system and device and relates to the technical field related to wear detection. The method comprises steps that according to an equipment operation time sequence diagram, particle data of an air flow field of present motion equipment parts is correspondingly acquired; according to the particle data, an equipment part which generates abnormality and corresponds to the air flow field is determined; for the abnormal equipment part, sound or vibration data is acquired, and the sound or vibration data and the particle data are fused to acquire composition relationships between the sound or vibration data and the particle data under the same time standards; the specific wear generation position or action is determined according to the composition relationships between the sound or vibration data and the particle data. The method is advantaged in that the abnormal wear position or action of a motion mechanism of the equipment can be accurately acquired.

Description

technical field [0001] The invention relates to the technical field related to wear detection, in particular to a method, system and device for diagnosing abnormal wear of equipment. Background technique [0002] In the field of finishing related technologies, the production line process equipment is mostly high-speed automatic conveying equipment and mechanical movement process equipment, and the equipment has various moving parts such as motors and connecting shafts. The action of these moving parts will inevitably bring about wear. Taking the TFT-LCD process as an example, the preparation process of TFT-LCD is complicated, and there are many process production equipment. The moving mechanism components in the equipment, such as crawlers, screw rods, sliders, gears, etc., inevitably have wear and tear. If the particles (Particles) are not eliminated in time, they will flow with the air flow, and there is a risk of being brought into the Glass. After the Glass is transport...

AI Technical Summary

Problems solved by technology

Taking the TFT-LCD process as an example, the preparation process of TFT-LCD is complicated, and there are many process production equipment. The moving mechanism components in the equipment, such as crawlers, screw rods, sliders, gears, etc., inevitably have wear and tear. If the particles (Particles) are not eliminated in time, they will flow with the air flow, and there is a risk of being brought into the Glass. After the Glass is transported through the Cell vacuum boxing process, the attached particles will not be repaired, which will greatly affect the yield rate and production efficiency.

[0003] For this kind of conveying reciprocating motion process equipment, the current fault diagnosis generally adopts the method of listening to abnormal noises, but it is impossible to detect fault omens only by listening to abnormal noises. When abnormal noises occur, the equipment wear is already very serious, causing the production line to The internal particles are high, the equipment is damaged, and it cannot be operated, and it cannot effectively solve the problems of absorption of individual differences in the actual machine and the determination of the cause of the fault in the fault judgment.

Therefore, the current fault diagnosis cannot accurately determine which motion mechanism produces wear particles due to the complexity of the motion state when the particles are high.

[0004] Therefore, in the process of implementing the present application, the inventors found that the prior art has at least the following defects: it is impossible to accurately determine the location or action of abnormal wear

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