OS-ELM-based rolling bearing health state estimation system and method

Abstract

The invention relates to an OS-ELM-based rolling bearing health state estimation system and method, and belongs to the technical field of fault diagnosis. The system comprises a signal acquisition module, a WIFI transmission module and a PC end analysis module. The signal acquisition module is composed of an infrared imager, an A / D converter and an STM32f103 chip. The WIFI transmission module is composed of a USR-C215 and a wireless router. According to the invention, an infrared camera of the signal acquisition module is used to shoot a rolling bearing, the A / D converter is used to carry out analog-to-digital conversion on an image signal, a converted digital signal is transmitted to an STM32f103 through an SPI interface and then is transmitted to the PC end analysis module through the WIFI module, and a rolling bearing health condition prediction model is established through OS-ELM. Therefore, the running state of the rolling bearing is estimated. The system and the method have the advantages of high safety, good transmission performance, high accuracy, convenience, high efficiency and the like, and are suitable for rolling bearing health state estimation of various devices.

Description

technical field [0001] The invention relates to an OS-ELM-based rolling bearing health state estimation system and method, belonging to the technical field of fault diagnosis. Background technique [0002] As the most commonly used supporting component in rotating machinery, rolling bearings play a vital role and are widely used in rotating machinery in various fields. About 30% of the rotating machinery failures caused by rolling bearings will not only cause huge production and economic losses to the country and enterprises, but also cause casualties in severe cases. Appraisal appears to be very important. When a fault occurs, the cost of manual inspection alone is high, and it is difficult to completely avoid the occurrence of faults and predict faults in advance. [0003] By remotely monitoring and predicting the running status of rolling bearings, online diagnosis of rolling bearing faults can be effectively performed, thereby preventing faults from occurring. Conten...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a rolling bearing health state estimation system and method based on OS-ELM (Online Sequence Extreme Learning Machine), which is used to solve the problems of wear, fatigue spalling, broken shaft, and downtime in the running process of rolling bearings. In order to realize the effective prediction of the running state of rolling bearings, it has strong practicability and engineering significance

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