Condition Assessment of Power Plant Motors Using a Set of Diagnostic Methods

Nazarychev, A. N.; Strakhov, A. S.; Novoselov, E. M.; Kolobov, A. B.; Polkoshnikov, D. A.; Zakharov, M. A.; Sulynenkov, I. N.; Skorobogatov, A. A.

doi:10.1007/s10749-023-01684-9

Power Technol Eng

2023

DOI: 10.1007/s10749-023-01684-9

|View full text |Cite

Condition Assessment of Power Plant Motors Using a Set of Diagnostic Methods

A. N. Nazarychev,

A. S. Strakhov,

E. M. Novoselov

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Virtual 3D modeling of thermal power plant turbines based on bilateral filtering algorithm for point cloud data

Zhai,

Zhang,

Jia

et al. 2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Point cloud segmentation and recognition for virtual 3D wind turbine modeling in thermal plants are disjointed, limiting coverage and elevating mean square error. A design leveraging bilateral filtering of point cloud data for virtual 3D wind turbine modeling is proposed to address this. This approach encompasses data acquisition, preprocessing, and multi-level segmentation to enhance coverage. Bilateral filtering is then applied to calculate the 3D model, with edge correction and verification. Tests reveal that compared to traditional k-means clustering, reduced project space, and hybrid filtering methods, the proposed bilateral filtering algorithm significantly reduces mean square error, maintaining it below 10, demonstrating improved stability, safety, and practical value for thermal plant fan modeling.

show abstract

Virtual 3D modeling of thermal power plant turbines based on bilateral filtering algorithm for point cloud data

Zhai,

Zhang,

Jia

et al. 2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Condition Assessment of Power Plant Motors Using a Set of Diagnostic Methods

Cited by 1 publication

References 7 publications

Virtual 3D modeling of thermal power plant turbines based on bilateral filtering algorithm for point cloud data

Virtual 3D modeling of thermal power plant turbines based on bilateral filtering algorithm for point cloud data

Contact Info

Product

Resources

About