Joon Ha Jung

823 total citations
25 papers, 657 citations indexed

About

Joon Ha Jung is a scholar working on Control and Systems Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Joon Ha Jung has authored 25 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Control and Systems Engineering, 14 papers in Mechanical Engineering and 10 papers in Mechanics of Materials. Recurrent topics in Joon Ha Jung's work include Machine Fault Diagnosis Techniques (19 papers), Fault Detection and Control Systems (11 papers) and Engineering Diagnostics and Reliability (8 papers). Joon Ha Jung is often cited by papers focused on Machine Fault Diagnosis Techniques (19 papers), Fault Detection and Control Systems (11 papers) and Engineering Diagnostics and Reliability (8 papers). Joon Ha Jung collaborates with scholars based in South Korea and Puerto Rico. Joon Ha Jung's co-authors include Byeng D. Youn, Byung Chul Jeon, Jin Uk Ko, Hyunseok Oh, Moussa Hamadache, Jung‐Ho Park, Kyung Ho Sun, Jin‐Wook Lee, Bayu Adhi Tama and Seung‐Chul Lee and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Access.

In The Last Decade

Joon Ha Jung

23 papers receiving 644 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Joon Ha Jung South Korea 13 498 301 171 98 62 25 657
Zhenhui Zhan China 11 449 0.9× 272 0.9× 126 0.7× 85 0.9× 47 0.8× 14 566
Aisong Qin China 14 553 1.1× 279 0.9× 200 1.2× 127 1.3× 51 0.8× 30 713
Mohd Syahril Ramadhan Mohd Saufi Malaysia 8 455 0.9× 267 0.9× 128 0.7× 87 0.9× 43 0.7× 22 584
Qinghua Zhang China 12 567 1.1× 301 1.0× 198 1.2× 101 1.0× 41 0.7× 44 728
Maogui Niu China 7 699 1.4× 423 1.4× 250 1.5× 103 1.1× 37 0.6× 8 803
Jiande Wu China 13 419 0.8× 306 1.0× 136 0.8× 68 0.7× 74 1.2× 90 604
Chenyu Liu China 11 368 0.7× 242 0.8× 108 0.6× 107 1.1× 42 0.7× 32 547
Kun Xu China 17 661 1.3× 441 1.5× 262 1.5× 145 1.5× 62 1.0× 41 899
Khandaker Noman China 16 446 0.9× 224 0.7× 138 0.8× 81 0.8× 69 1.1× 52 590
Dongfang Zhao China 12 347 0.7× 205 0.7× 120 0.7× 80 0.8× 45 0.7× 28 471

Countries citing papers authored by Joon Ha Jung

Since Specialization
Citations

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

Fields of papers citing papers by Joon Ha Jung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joon Ha Jung. 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 Joon Ha Jung. The network helps show where Joon Ha Jung may publish in the future.

Co-authorship network of co-authors of Joon Ha Jung

This figure shows the co-authorship network connecting the top 25 collaborators of Joon Ha Jung. A scholar is included among the top collaborators of Joon Ha Jung 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 Joon Ha Jung. Joon Ha Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ko, Jin Uk, et al.. (2024). Latent space alignment based domain adaptation (LSADA) for fault diagnosis of rotating machinery. Advanced Engineering Informatics. 62. 102862–102862. 10 indexed citations
2.
Ko, Jin Uk, et al.. (2024). Spectrum-guided GAN with density-directionality sampling: Diverse high-fidelity signal generation for fault diagnosis of rotating machinery. Advanced Engineering Informatics. 62. 102821–102821. 12 indexed citations
3.
Jung, Joon Ha, et al.. (2024). Development of Rotor Balancing Algorithm for a High‐Precision Rotor System considering Dynamic Reliability through Automatic‐Adaptive DBSCAN. Structural Control and Health Monitoring. 2024(1). 5 indexed citations
4.
Kim, Tae-Hun, et al.. (2024). Gradient Alignment based Partial Domain Adaptation (GAPDA) using a domain knowledge filter for fault diagnosis of bearing. Reliability Engineering & System Safety. 250. 110293–110293. 14 indexed citations
5.
Khalid, Salman, et al.. (2024). Artificial Intelligence-Driven Prognostics and Health Management for Centrifugal Pumps: A Comprehensive Review. Actuators. 13(12). 514–514. 2 indexed citations
6.
Park, Y., et al.. (2024). Intelligent Helicopter Turbine Engine Fault Diagnosis Using Multi-Head Attention. Annual Conference of the PHM Society. 16(1).
7.
Ko, Jin Uk, et al.. (2023). Domain adaptation with label-aligned sampling (DALAS) for cross-domain fault diagnosis of rotating machinery under class imbalance. Expert Systems with Applications. 243. 122910–122910. 23 indexed citations
8.
Yoo, Seung‐Jin, et al.. (2023). A Convolutional Autoencoder Based Fault Diagnosis Method for a Hydraulic Solenoid Valve Considering Unknown Faults. Sensors. 23(16). 7249–7249. 4 indexed citations
9.
Jo, Soo-Ho, Joon Ha Jung, Jong Moon Ha, et al.. (2023). A Hybrid Approach of Data-driven and Physics-based Methods for Estimation and Prediction of Fatigue Crack Growth. International Journal of Prognostics and Health Management. 11(1). 3 indexed citations
10.
Ko, Jin Uk, et al.. (2021). A Domain Adaptation with Semantic Clustering (DASC) method for fault diagnosis of rotating machinery. ISA Transactions. 120. 372–382. 56 indexed citations
11.
Lee, Jin‐Wook, et al.. (2021). Asymmetric inter-intra domain alignments (AIIDA) method for intelligent fault diagnosis of rotating machinery. Reliability Engineering & System Safety. 218. 108186–108186. 57 indexed citations
12.
Jung, Joon Ha, et al.. (2021). Label-based, Mini-batch Combinations Study for Convolutional Neural Network Based Fluid-film Bearing Rotor System Diagnosis. Computers in Industry. 133. 103546–103546. 5 indexed citations
13.
Jung, Joon Ha, et al.. (2020). Direct Connection-Based Convolutional Neural Network (DC-CNN) for Fault Diagnosis of Rotor Systems. IEEE Access. 8. 172043–172056. 36 indexed citations
14.
Ko, Jin Uk, et al.. (2020). Multi-task learning of classification and denoising (MLCD) for noise-robust rotor system diagnosis. Computers in Industry. 125. 103385–103385. 28 indexed citations
15.
Oh, Hyunseok, et al.. (2019). A robust and convex metric for unconstrained optimization in statistical model calibration—probability residual (PR). Structural and Multidisciplinary Optimization. 60(3). 1171–1187. 15 indexed citations
16.
Hamadache, Moussa, Joon Ha Jung, Jung‐Ho Park, & Byeng D. Youn. (2019). A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning. 1(1-2). 125–151. 128 indexed citations
17.
Oh, Hyunseok, Joon Ha Jung, Byung Chul Jeon, & Byeng D. Youn. (2017). Scalable and Unsupervised Feature Engineering Using Vibration-Imaging and Deep Learning for Rotor System Diagnosis. IEEE Transactions on Industrial Electronics. 65(4). 3539–3549. 122 indexed citations
18.
Oh, Hyunseok, Byung Chul Jeon, Joon Ha Jung, & Byeng D. Youn. (2016). Smart Diagnosis of Journal Bearing Rotor Systems: Unsupervised Feature Extraction Scheme by Deep Learning. Annual Conference of the PHM Society. 8(1). 10 indexed citations
19.
Jung, Joon Ha, et al.. (2016). Omnidirectional regeneration (ODR) of proximity sensor signals for robust diagnosis of journal bearing systems. Mechanical Systems and Signal Processing. 90. 189–207. 39 indexed citations
20.
Jung, Joon Ha, et al.. (2015). Omni-Directional Regeneration (ODR) of Gap Sensor Signal for Journal Bearing System Diagnosis. Annual Conference of the PHM Society. 7(1). 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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