A bearing fault prediction system and method based on multi-source information fusion

A technology of multi-source information fusion and fault prediction, applied in the field of multi-source information fusion bearing fault prediction system, can solve problems such as poor signal quality, complicated service environment of rolling bearings, difficult to capture, identify and extract fault information, and achieve the elimination of dimensionality difference effect

Active Publication Date: 2021-11-05
SHANDONG UNIV
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Problems solved by technology

[0004] In view of the deficiencies in the existing technology, the purpose of the present invention is to provide a bearing fault prediction system and method based on multi-source information fusion, which solves the problem of complex service environment of rolling bearings in complex rotating equipment, poor signal quality, and difficulty in capturing, identifying and Extracted problems: can obtain the full life cycle status of bearing operation, can collect and analyze multiple status signals of bearings at the same time, improve the recognition rate of fault characteristics, and improve the accuracy of model prediction

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  • A bearing fault prediction system and method based on multi-source information fusion
  • A bearing fault prediction system and method based on multi-source information fusion
  • A bearing fault prediction system and method based on multi-source information fusion

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Embodiment 1

[0034] This embodiment provides a multi-source information fusion bearing fault prediction system, including a multi-source information collection system and a fault prediction system. The multi-source information collection system is used to obtain multi-source state information transmitted to the failure prediction system. The fault prediction system then performs preprocessing analysis on the original signal, and combines the feature fusion method to obtain representative fault features, and realizes accurate prediction of bearing faults through model training.

[0035] Considering that vibration signals and temperature signals are often used to describe the degradation process of bearings, this embodiment takes the collection of bearing temperature and vibration data as an example, so the sensors in this embodiment include vibration sensors and temperature sensors. Of course, in other embodiments, other types of sensors may also be included, depending on specific detection...

Embodiment 2

[0045] This embodiment provides a bearing fault prediction method based on multi-source information fusion, such as Figure 4 As shown, taking the vibration data set and temperature data set extracted from the database as an example, they are used as the model training data set, and the data preprocessing module performs data cleaning, data integration, data specification, and data transformation on the original signal to eliminate the noise in the signal. noise and integrate data from different data sources together to eliminate dimensional differences.

[0046] According to the complexity of the model, select the corresponding time-frequency domain features in the feature extraction module, and then select the appropriate dimensionality reduction method in the feature dimensionality reduction module, such as using the local linear embedding method to reduce the dimension of the training data, thereby reducing the complexity of the algorithm calculation. The feature fusion mo...

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Abstract

The invention discloses a bearing fault prediction system and method based on multi-source information fusion. The technical solution is: it includes a multi-source information collection system and a fault prediction system. source information, including several sensors installed on the bearing; the fault prediction system includes a database, a data processing module, a condition monitoring module, and a fault prediction module. The database is used to store data collected by different sensors, and the data processing module is used to process data collected by different sensors The original signal; the status monitoring module is used to display the data in real time, and the fault prediction module can train the processed data to obtain the fault prediction result. The invention can obtain the full life cycle state of bearing operation, simultaneously collect and analyze multiple state signals of the bearing, improve the recognition rate of fault features, and improve the accuracy of model prediction.

Description

technical field [0001] The invention relates to the field of bearing fault prediction, in particular to a bearing fault prediction system and method based on multi-source information fusion. Background technique [0002] With the continuous progress and development of science and technology, modern machinery gradually tends to be large-scale, diversified and complex. Harsh working conditions such as large disturbances and strong impacts often appear, and the service environment of equipment is complex. Once a failure occurs, it will cause serious economic losses or even Casualties, therefore predictive and health management of machinery and equipment are critical. Rolling bearings are important parts in industrial equipment, and their health status largely determines the service performance of equipment. According to relevant research, 45% to 55% of rotating machinery failures are caused by the failure of rolling bearings. Therefore, the failure of rolling bearings Predicti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/045G06F16/25
CPCG01M13/045G06F16/252
Inventor 马嵩华王璐璐
Owner SHANDONG UNIV
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