Vamsi Inturi

606 total citations
24 papers, 443 citations indexed

About

Vamsi Inturi is a scholar working on Mechanical Engineering, Control and Systems Engineering and Mechanics of Materials. According to data from OpenAlex, Vamsi Inturi has authored 24 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Mechanical Engineering, 16 papers in Control and Systems Engineering and 5 papers in Mechanics of Materials. Recurrent topics in Vamsi Inturi's work include Gear and Bearing Dynamics Analysis (16 papers), Machine Fault Diagnosis Techniques (16 papers) and Fault Detection and Control Systems (6 papers). Vamsi Inturi is often cited by papers focused on Gear and Bearing Dynamics Analysis (16 papers), Machine Fault Diagnosis Techniques (16 papers) and Fault Detection and Control Systems (6 papers). Vamsi Inturi collaborates with scholars based in India and Ireland. Vamsi Inturi's co-authors include G. R. Sabareesh, Pavan Kumar Penumakala, Sudha Radhika, Kurra Suresh, Vikram Pakrashi, S. Rajkumar, Bidisha Ghosh and Rajkumar Soundrapandiyan and has published in prestigious journals such as Expert Systems with Applications, Sensors and Mechanical Systems and Signal Processing.

In The Last Decade

Vamsi Inturi

22 papers receiving 430 citations

Peers

Vamsi Inturi

CSE

IME

Guoying Meng China

Zhi Zheng China

D.H. Pandya India

Huibin Lin China

Xiaosun Wang China

Zhanqun Shi China

Hongdi Zhou China

Lanto Rasolofondraibe France

Minh Thi Tran Vietnam

Jong Moon Ha South Korea

Guoying Meng China

Vamsi Inturi

211 ×0.7

CSE

248 ×0.9

101 ×0.9

40 ×0.6

CSE

50 ×1.0

IME

Citations per year, relative to Vamsi Inturi Vamsi Inturi (= 1×) peers Guoying Meng

Countries citing papers authored by Vamsi Inturi

Since Specialization

Citations

This map shows the geographic impact of Vamsi Inturi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Vamsi Inturi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vamsi Inturi more than expected).

Fields of papers citing papers by Vamsi Inturi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vamsi Inturi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Vamsi Inturi. The network helps show where Vamsi Inturi may publish in the future.

Co-authorship network of co-authors of Vamsi Inturi

This figure shows the co-authorship network connecting the top 25 collaborators of Vamsi Inturi. A scholar is included among the top collaborators of Vamsi Inturi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Vamsi Inturi. Vamsi Inturi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sabareesh, G. R., et al.. (2025). Using machine learning approach to investigate the impact of missing sensors on fault classification of multistage gear box. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 47(3). 2 indexed citations

Inturi, Vamsi, et al.. (2025). Combining Sensor Fusion and a Machine Learning Framework for Accurate Tool Wear Prediction During Machining. Machines. 13(2). 132–132. 3 indexed citations

Inturi, Vamsi, et al.. (2025). Combined Vibro-acoustic Analysis to Identify the Health State of a Multi-stage Gearbox Through Hjorth’s Parameters. Journal of Vibration Engineering & Technologies. 13(8).

Inturi, Vamsi, et al.. (2024). Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning. Journal of Medical Engineering & Technology. 48(6). 213–222.

Inturi, Vamsi, Bidisha Ghosh, G. R. Sabareesh, & Vikram Pakrashi. (2024). A Review of Digital Twinning for Rotating Machinery. Sensors. 24(15). 5002–5002. 7 indexed citations

Inturi, Vamsi, et al.. (2024). A wavelet and local binary pattern-based feature descriptor for the detection of chronic infection through thoracic X-ray images. Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine. 238(11-12). 1133–1145. 1 indexed citations

Inturi, Vamsi, et al.. (2022). Damage monitoring of pultruded GFRP composites using wavelet transform of vibration signals. Measurement. 195. 111177–111177. 15 indexed citations

Sabareesh, G. R., et al.. (2022). Component level signal segmentation method for multi-component fault detection in a wind turbine gearbox. Measurement. 195. 111180–111180. 22 indexed citations

Inturi, Vamsi, Pavan Kumar Penumakala, & G. R. Sabareesh. (2022). Effect of Multiple Defects and Multi-component Failure on the Dynamic Behaviour of a Wind Turbine Gearbox. Arabian Journal for Science and Engineering. 47(7). 8969–8983. 8 indexed citations

10.

Inturi, Vamsi, et al.. (2021). Wavelet and deep learning-based detection of SARS-nCoV from thoracic X-ray images for rapid and efficient testing. Expert Systems with Applications. 185. 115650–115650. 16 indexed citations

11.

Inturi, Vamsi, et al.. (2021). Principal Component Analysis Based Gear Fault Diagnostics in Different Stages of a Multi-Stage Gearbox Subjected to Extensive Fluctuating Speeds. Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems. 4(3). 3 indexed citations

12.

Inturi, Vamsi, et al.. (2021). Detection of Local Gear Tooth Defects on a Multistage Gearbox Operating Under Fluctuating Speeds Using DWT and EMD Analysis. Arabian Journal for Science and Engineering. 46(12). 11999–12008. 19 indexed citations

13.

Sabareesh, G. R., et al.. (2021). Optimal sensor placement for identifying multi-component failures in a wind turbine gearbox using integrated condition monitoring scheme. Applied Acoustics. 187. 108505–108505. 29 indexed citations

14.

Inturi, Vamsi, et al.. (2021). Fingerprinting based data abstraction technique for remaining useful life estimation in a multi-stage gearbox. Measurement. 174. 109021–109021. 17 indexed citations

15.

Inturi, Vamsi, et al.. (2020). Evaluation of surface roughness in incremental forming using image processing based methods. Measurement. 164. 108055–108055. 54 indexed citations

16.

Inturi, Vamsi, et al.. (2020). Comprehensive fault diagnostics of wind turbine gearbox through adaptive condition monitoring scheme. Applied Acoustics. 174. 107738–107738. 39 indexed citations

17.

Inturi, Vamsi, et al.. (2019). Integrated Vibro-Acoustic Analysis and Empirical Mode Decomposition for Fault Diagnosis of Gears in a Wind Turbine. Procedia Structural Integrity. 14. 937–944. 13 indexed citations

18.

Inturi, Vamsi, et al.. (2019). Integrated condition monitoring scheme for bearing fault diagnosis of a wind turbine gearbox. Journal of Vibration and Control. 25(12). 1852–1865. 53 indexed citations

19.

Inturi, Vamsi, et al.. (2019). Hyperparameter optimization for enabling multi-level feature classification in a wind turbine gearbox. Vibroengineering PROCEDIA. 29. 24–30. 1 indexed citations

20.

Inturi, Vamsi, et al.. (2019). PCA based health indicator for remaining useful life prediction of wind turbine gearbox. Vibroengineering PROCEDIA. 29. 31–36. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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