Variable-speed variable-load large rolling bearing fault prediction system and method

Abstract

The invention discloses a variable-speed variable-load large rolling bearing fault prediction system and method. The system comprises a variable-speed variable-load rolling bearing experiment table and a bearing intelligent information system. The variable-speed variable-load rolling bearing experiment table is used for simulating the variable-speed variable-load working environment of the rollingbearing and comprises a control system, a loading device and a testing system, and the testing system is connected with the control system and the loading device; the bearing intelligent informationsystem carries out state monitoring and fault prediction on the rolling bearing based on data collected by the variable-speed variable-load rolling bearing experiment table and comprises a database, adata processing module, a state monitoring module and a fault prediction module, the database is connected with the state monitoring module, and the database is sequentially connected with the data processing module and the fault prediction module. By constructing the rolling bearing experiment table, the variable-speed and variable-load working characteristics of the bearing are simulated, and the collection of full-life-cycle bearing operation signals is realized; a system training data set is obtained by collecting the operation state information of the bearing, and fault prediction of therolling bearing under variable speed and variable load is achieved.

Description

technical field [0001] The invention relates to the technical field of rolling bearing fault prediction and health management (PHM), in particular to a fault prediction system and method for a large rolling bearing with variable speed and variable load. Background technique [0002] In modern industrial production and manufacturing, large-scale rotating equipment is widely used, and its normal operation has a great impact on product quality and processing efficiency. Rolling bearings are key parts of rotating equipment, and their health status largely determines the quality, precision and safety of equipment production. Due to the increasing complexity and intelligence of large rotating equipment, bearings are often in working environments such as variable speed, variable load, large disturbance, and strong impact, so the failure of rolling bearings has become the main failure mode of rotating equipment. Therefore, the fault prediction of rolling bearings And health managem...

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Problems solved by technology

[0003] The full life cycle data of rolling bearings is the basis for fault prediction, but it is difficult to collect complete operating status information at industrial sites

On the one hand, due to the complex structure of the equipment, it is difficult to install the sensor; on the other hand, due to the complex working conditions on site, there are many unexpected shutdowns and other factors, resulting in incomplete signal acquisition

In addition, a large number of interference factors on the production site make the quality of the target signal not high, coupled with the disturbance caused by the variable speed and variable load service environment itself, it is difficult to judge the performance of the equipment intuitively even if the signal is collected

Moreover, faulty bearings in large-scale equipment are often large in size, and currently there is no test bench that can reflect the variable-speed and variable-load service environment of large-scale rolling bearings in actual production due to cost and technical issues, and it is difficult to obtain operating data for the entire life cycle of actual bearings. Its failure prediction has become a difficult point, so the current large and complex rotating equipment mainly adopts regular and after-the-fact maintenance

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