Lishu Lv

582 total citations
25 papers, 426 citations indexed

About

Lishu Lv is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Lishu Lv has authored 25 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Mechanical Engineering, 14 papers in Industrial and Manufacturing Engineering and 9 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Lishu Lv's work include Advanced machining processes and optimization (16 papers), Manufacturing Process and Optimization (12 papers) and Advanced Surface Polishing Techniques (9 papers). Lishu Lv is often cited by papers focused on Advanced machining processes and optimization (16 papers), Manufacturing Process and Optimization (12 papers) and Advanced Surface Polishing Techniques (9 papers). Lishu Lv collaborates with scholars based in China. Lishu Lv's co-authors include Zhaohui Deng, Tao Liu, Hua Zhang, Linlin Wan, Zhongyang Li, Wei Liu, Shichun Li, Wei Li, Julong Yuan and Yiwen Li and has published in prestigious journals such as Journal of Cleaner Production, Mechanical Systems and Signal Processing and International Journal of Production Research.

In The Last Decade

Lishu Lv

22 papers receiving 413 citations

Peers

Lishu Lv

IME

EEE

RESE

Nitesh Sihag India

Lukáš Weiss Switzerland

Antoni Świć Poland

Apostolos Fysikopoulos Greece

Umberto La Commare Italy

Anna Hnydiuk-Stefan Poland

Salman Sagheer Warsi Pakistan

Athulan Vijayaraghavan United States

Lirong Zhou China

Alexander Christ Australia

Nitesh Sihag India

Lishu Lv

143 ×0.5

104 ×0.5

IME

118 ×0.9

EEE

105 ×1.0

RESE

93 ×1.0

Citations per year, relative to Lishu Lv Lishu Lv (= 1×) peers Nitesh Sihag

Countries citing papers authored by Lishu Lv

Since Specialization

Citations

This map shows the geographic impact of Lishu Lv'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 Lishu Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lishu Lv more than expected).

Fields of papers citing papers by Lishu Lv

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lishu Lv. 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 Lishu Lv. The network helps show where Lishu Lv may publish in the future.

Co-authorship network of co-authors of Lishu Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Lishu Lv. A scholar is included among the top collaborators of Lishu Lv 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 Lishu Lv. Lishu Lv 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

Lv, Lishu, et al.. (2025). An online monitoring approach of grinding wheel wear condition for robotic weld grinding based on enhanced CNN-GRU model. Mechanical Systems and Signal Processing. 241. 113483–113483.

Chen, Bing, S. Li, Jun Yi, et al.. (2025). Research on precision dressing of resin-bonded arc-shaped diamond grinding wheel via tantalum metal.. Precision Engineering. 97. 839–850.

Lv, Lishu, et al.. (2025). The grinding wheel wear condition monitoring method based on multi-sensor information hierarchical fusion for high-speed cylindrical grinding. Advanced Engineering Informatics. 67. 103541–103541. 2 indexed citations

Liu, Tao, et al.. (2024). A chatter online prediction method and system software in high-speed grinding of camshaft. The International Journal of Advanced Manufacturing Technology. 134(9-10). 4771–4783.

Li, Yiwen, et al.. (2024). An online chatter detection and recognition method for camshaft non-circular contour high-speed grinding based on improved LMD and GAPSO-ABC-SVM. Mechanical Systems and Signal Processing. 216. 111487–111487. 12 indexed citations

Deng, Zhaohui, et al.. (2024). Research on Cloud-Edge-Device Collaborative Intelligent Monitoring System of Grinding Wheel Wear State for High-Speed Cylindrical Grinding of Bearing Rings. Actuators. 13(9). 327–327. 2 indexed citations

Deng, Zhaohui, et al.. (2023). Study on modelling simulation and distribution characteristics of residual stress during robotic weld end grinding of high strength modulated steel. Journal of Manufacturing Processes. 108. 98–113. 10 indexed citations

Jiang, Wenxiang, et al.. (2023). A multi-objective modeling and optimization method for high efficiency, low energy, and economy. The International Journal of Advanced Manufacturing Technology. 128(5-6). 2483–2498. 7 indexed citations

Deng, Zhaohui, et al.. (2021). Prediction research for surface topography of internal grinding based on mechanism and data model. The International Journal of Advanced Manufacturing Technology. 113(3-4). 821–836. 13 indexed citations

10.

Li, Zhongyang, et al.. (2021). A hybrid approach of case-based reasoning and process reasoning to typical parts grinding process intelligent decision. International Journal of Production Research. 61(2). 503–519. 8 indexed citations

11.

Liu, Tao, et al.. (2021). Chatter detection in camshaft high-speed grinding process based on VMD parametric optimization. Measurement. 187. 110133–110133. 26 indexed citations

12.

Deng, Zhaohui, et al.. (2021). Robot welding seam online grinding system based on laser vision guidance. The International Journal of Advanced Manufacturing Technology. 116(5-6). 1737–1749. 20 indexed citations

13.

Liu, Tao, et al.. (2020). Theoretical and experimental study of temperature field in noncircular high-speed grinding. The International Journal of Advanced Manufacturing Technology. 107(7-8). 3581–3592. 10 indexed citations

14.

Lv, Lishu, Zhaohui Deng, Tao Liu, Zhongyang Li, & Wei Liu. (2020). Intelligent technology in grinding process driven by data: A review. Journal of Manufacturing Processes. 58. 1039–1051. 50 indexed citations

15.

Lv, Lishu, et al.. (2020). Modelling and analysis for processing energy consumption of mechanism and data integrated machine tool. International Journal of Production Research. 58(23). 7078–7093. 13 indexed citations

16.

Lv, Lishu, et al.. (2019). A Composite Evaluation Model of Sustainable Manufacturing in Machining Process for Typical Machine Tools. Processes. 7(2). 110–110. 15 indexed citations

17.

Deng, Zhaohui, et al.. (2019). Modelling of carbon utilisation efficiency and its application in milling parameters optimisation. International Journal of Production Research. 58(8). 2406–2420. 18 indexed citations

18.

Deng, Zhaohui, et al.. (2018). Research on intelligent expert system of green cutting process and its application. Journal of Cleaner Production. 185. 904–911. 20 indexed citations

19.

Zhang, Hua, et al.. (2017). A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions. Journal of Cleaner Production. 148. 174–184. 84 indexed citations

20.

Chen, Jian, et al.. (2014). Stability and Control of Tooling System for High-Speed Machining. Applied Mechanics and Materials. 684. 375–380. 1 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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