Intelligent Fault Diagnosis of Photoelectric Pod Bearing Based on Multi-information Fusion

Research of Intelligent Fault Diagnosis Model on Multi-Information Fusion

From the intelligent fault diagnosis system requirements, this article analyzes the relationship between the fault diagnosis and the multi-information fusion basing on the summing up the multi-sensor information fusion technology, and studies the hierarchical structure of multisensor information fusion system and the content of integration, and establishes an intelligent fault diagnosis model w...

Bearing Fault Diagnosis Using Information Fusion and Intelligent Algorithms

Transformer Fault Diagnosis Based on Information Fusion Technology

Transformer faults have many types and fault information is uncertain, in response to these problems, this paper presents evidence theory and neural network integrated fault diagnosis. In order to realize the reasonable assignment of reliability by Dempster combination rule after the information fusion between strong conflict evidence, the concept of a trust coefficient is introduced to correct...

Research on Transformer Fault Diagnosis based on Multi-source Information Fusion

DGA (Dissolved Gas Analysis) is the traditional transformer fault diagnosis method, but it mainly depends on the experience of operators. In order to solve the limitations of traditional method, this paper introduces intelligent method for fault diagnosis of transformer. The intelligent method made fusion of various data, including SCADA data, oil dissolved gas sensor data, related electrical t...

Bearing Fault Diagnosis Based on Vibration Signals

The vibration signal obtained from operating machines contains information relating to machine condition as well as noise. Further processing of the signal is necessary to elicit information particularly relevant to bearing faults. Many techniques have been employed to process the vibration signals in bearing faults detection and diagnosis. Two common techniques, time domain techniques and freq...