Research on Fault Diagnosis Method of Industrial Robots Based on Case-Based Reasoning
Lin Zhang, Chunling Wang
- Year
- 2019
- Citations
- 3
- Access
- Open access
Abstract
The application enterprises of industrial robots generally do not have the ability to independently diagnose and repair the faults of industrial robots. When robots fail and stop operation, they often need to notify external service providers to diagnose and repair the fault sites of enterprises, which seriously affects the production tempo of enterprises. The loss of the enterprise is aggravated. Therefore, according to the dynamic evolution of the industrial robot fault diagnosis method and the characteristics of the case reasoning method, this paper applies the Case-Based Reasoning method to the industrial robot fault diagnosis. By using the concept of Inverse Document Frequency (IDF) index in information theory, the case organization, case retrieval and case retention technology in CBR technology are designed, which provides an effective method for the diagnosis of industrial robot faults.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991