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Analysis and Diagnosis of Coal Shearer Machine Fault Based on Improved Support Vector Theory-所有数据库
Source: webofscience.com
Article summary:
1. This paper introduces an improved support vector machine theory for detecting faults in coal shearers under mine conditions.
2. A multiple fault classifier is used to identify the types of faults in coal shearers.
3. Simulation results demonstrate the effectiveness of this method for early detection of faults in coal shearer monitoring systems.
Article analysis:
The article is generally reliable and trustworthy, as it provides a detailed description of the improved support vector machine theory and its application to detect faults in coal shearers under mine conditions. The authors provide evidence for their claims through simulation results, which demonstrate the effectiveness of this method for early detection of faults in coal shearer monitoring systems. Furthermore, the authors provide a comprehensive overview of the research topic, including a discussion on the multiple fault classifier used to identify the types of faults in coal shearers and how temperature fault types can be reconstructed.
The article does not appear to have any major biases or one-sided reporting, as it presents both sides equally and does not make any unsupported claims or missing points of consideration. Additionally, there is no promotional content or partiality present in the article, and all possible risks are noted throughout. Therefore, overall this article appears to be reliable and trustworthy with regards to its content and presentation.