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工业机器人故障诊断与健康预测方法研究 - 中国知网
Source: kns.cnki.net
Article summary:
1. This article provides an overview of industrial robots, including their system composition and typical failure modes.
2. It then outlines knowledge-driven and data-driven fault diagnosis methods for industrial robots, as well as performance degradation monitoring and remaining service life prediction methods.
3. Finally, it looks forward to the future development trend of industrial robot fault diagnosis and health prediction methods in the big data environment.
Article analysis:
The article is generally reliable and trustworthy, providing a comprehensive overview of industrial robots, their system composition, typical failure modes, fault diagnosis methods, performance degradation monitoring and remaining service life prediction methods. The article also looks ahead to the future development trend of industrial robot fault diagnosis and health prediction methods in the big data environment.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by outlining both knowledge-driven and data-driven fault diagnosis methods for industrial robots. Furthermore, the article provides evidence for its claims by citing relevant research papers throughout the text.
The only potential issue with this article is that it does not explore any counterarguments or alternative points of view on the topics discussed; however, this is understandable given that this is an overview article rather than a critical analysis piece. Additionally, there is no promotional content present in the text; instead, it focuses solely on providing an objective overview of industrial robots and their associated technologies.