Yes, you can access articles related to specific electrical machine fault analysis or diagnosis algorithms in various journals and publications. These resources are valuable for researchers, engineers, and practitioners in the field of electrical machine fault analysis and diagnosis. Here are some popular journals and publications where you can find relevant articles:

1. IEEE Transactions on Industrial Electronics:
- This renowned journal covers a wide range of topics related to industrial electronics, including electrical machine fault analysis and diagnosis.
- It publishes high-quality research papers that present novel algorithms, techniques, and case studies in this field.

2. IEEE Transactions on Power Electronics:
- This journal focuses on power electronics and its applications, including the diagnosis and analysis of electrical machine faults.
- It features articles that propose innovative fault detection and diagnosis algorithms, as well as their implementation in power electronic systems.

3. IEEE Transactions on Energy Conversion:
- This publication is dedicated to the field of energy conversion, which includes electrical machines.
- It publishes articles related to fault analysis and diagnosis algorithms for various types of electrical machines, such as motors and generators.

4. International Journal of Electrical Power & Energy Systems:
- This journal covers a wide range of topics related to electrical power systems, including fault analysis and diagnosis of electrical machines.
- It presents research papers on fault detection algorithms, condition monitoring techniques, and diagnostic methods for different types of electrical machines.

5. Electric Power Systems Research:
- This publication focuses on research related to electric power systems, including fault analysis and diagnosis of electrical machines.
- It features articles on fault detection algorithms, fault location techniques, and fault diagnosis methods for electrical machines in power systems.

These journals and publications provide a wealth of knowledge and research findings in the field of electrical machine fault analysis and diagnosis. By accessing these resources, you can stay up to date with the latest advancements, learn about new algorithms, and gain insights from case studies and practical implementations.