Fault diagnosis method based on adaptive manifold embedding dynamic distribution alignment

Abstract

The invention discloses a fault diagnosis method based on adaptive manifold embedding dynamic distribution alignment. According to the method, the feature distortion of data in an original Euclidean space can be effectively avoided through the automatic calculation of the optimal subspace dimension and the calculation of the streaming kernel of a geodesic line and converted manifold feature representations; a similarity measure A-distance is introduced to define a self-adaptive factor; relative weights of condition distribution and edge distribution of sample data are dynamically adjusted, andtherefore, the distribution difference of source domain and target domain samples can be effectively reduced, the accuracy and effectiveness of rolling bearing fault diagnosis under variable workingconditions can be greatly improved. The method is high in interpretability, is lower in requirements for computer hardware resources, is higher in execution speed, and is excellent in diagnosis precision, algorithm convergence and parameter robustness. The method is especially suitable for multi-scene and multi-fault bearing fault diagnosis under variable working conditions, and can be widely applied to fault diagnosis tasks of complex systems such as machinery, electric power, chemical engineering and aviation under variable working conditions.

Description

technical field [0001] The invention relates to the technical fields of mechanical fault diagnosis and machine learning, in particular to a fault diagnosis method based on adaptive manifold embedding and dynamic distribution alignment. Background technique [0002] Rotating machinery is ubiquitous in modern industrial production. As a key component in industrial production equipment, rolling bearings are widely used in various important fields such as machinery, electric power, chemical industry, aviation, etc. At the same time, rolling bearings often work under high temperature, high speed, heavy load In such harsh environments, failures such as wear, cracks, and fractures are prone to occur. Once the bearing fails, it will bring huge economic losses, and cause catastrophic accidents such as casualties. Therefore, it is necessary to strengthen the condition monitoring capabilities of mechanical equipment and improve It is of positive and great significance to qualitatively ...

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Problems solved by technology

Furthermore, when adaptive distribution alignment is performed in the original Euclidean space, data feature distortions inevitably occur, leading to suboptimal diagnostic performance of the model

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