{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:11:55Z","timestamp":1758269515053,"version":"3.37.3"},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T00:00:00Z","timestamp":1720137600000},"content-version":"vor","delay-in-days":2,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"MSIT","doi-asserted-by":"publisher","award":["NRF-2021R1A4A2001824)"],"award-info":[{"award-number":["NRF-2021R1A4A2001824)"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>A frequency-focused sound data generator was developed for the in situ fault sound diagnosis of industrial robot reducers. The sound data generator, based on a conditional generative adversarial network, selects a target frequency range without relying on domain knowledge. A sound dataset of normal and faulty harmonic drive rotations of in situ industrial robots was collected using an attachable wireless sound sensor. The generated sound data were evaluated based on the fault diagnosis accuracy of a simple classifier trained using the generated data and tested using real data. The proposed method well-defined the frequency feature clusters and produced high-quality data, exhibiting up to 16.0% higher precision score on normal and 13.0% higher accuracy on weak-fault harmonic drive compared with the conventional methods, achieving fault diagnosis accuracy of 95.6% even in situations of fault data comprising only 5% of the normal data.<\/jats:p>","DOI":"10.1093\/jcde\/qwae061","type":"journal-article","created":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T12:47:08Z","timestamp":1720010828000},"page":"234-248","source":"Crossref","is-referenced-by-count":6,"title":["Frequency-focused sound data generator for fault diagnosis in industrial robots"],"prefix":"10.1093","volume":"11","author":[{"given":"Semin","family":"Ahn","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinoh","family":"Yoo","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyu-Wha","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0135-3660","authenticated-orcid":false,"given":"Byeng Dong","family":"Youn","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University , Seoul 08826 , Republic of Korea"},{"name":"OnePredict Inc. , Seoul 06160 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sung-Hoon","family":"Ahn","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University , Seoul 08826 , Republic of Korea"},{"name":"Institute of Advanced Machines and Design, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,7,4]]},"reference":[{"key":"2024091413065525200_bib1","article-title":"Wasserstein generative adversarial networks","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Arjovsky","year":"2017"},{"key":"2024091413065525200_bib2","doi-asserted-by":"crossref","first-page":"103329","DOI":"10.1016\/j.cviu.2021.103329","article-title":"Pros and cons of GAN evaluation measures: New developments","volume":"215","author":"Borji","year":"2022","journal-title":"Computer Vision and Image Understanding"},{"key":"2024091413065525200_bib3","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"Journal of Artificial Intelligence Research"},{"key":"2024091413065525200_bib4","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.jmsy.2022.12.006","article-title":"Compound fault diagnosis for industrial robots based on dual-transformer networks","volume":"66","author":"Chen","year":"2023","journal-title":"Journal of Manufacturing Systems"},{"key":"2024091413065525200_bib5","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1109\/JAS.2023.124107","article-title":"Dynamic vision enabled contactless cross-domain machine fault diagnosis with neuromorphic computing","volume":"11","author":"Chen","year":"2024","journal-title":"IEEE-CAA Journal of Automatica Sinica"},{"key":"2024091413065525200_bib6","first-page":"1","article-title":"Modified varying index coefficient autoregression model for representation of the nonstationary vibration from a planetary gearbox","volume":"72","author":"Chen","year":"2023","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"2024091413065525200_bib7","doi-asserted-by":"crossref","first-page":"108907","DOI":"10.1016\/j.ymssp.2022.108907","article-title":"Physics-informed LSTM hyperparameters selection for gearbox fault detection","volume":"171","author":"Chen","year":"2022","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2024091413065525200_bib8","first-page":"2672","article-title":"Generative adversarial nets","volume-title":"Advances in neural information processing systems 27 (Nips 2014)","author":"Goodfellow","year":"2014"},{"key":"2024091413065525200_bib9","doi-asserted-by":"crossref","first-page":"107076","DOI":"10.1016\/j.engfailanal.2023.107076","article-title":"A systematic review on failure modes and proposed methodology to artificially seed faults for promoting PHM studies in laboratory environment for an industrial gearbox","volume":"146","author":"Goswami","year":"2023","journal-title":"Engineering Failure Analysis"},{"key":"2024091413065525200_bib10","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1007\/978-3-319-32552-1_54","article-title":"Industrial robotics","volume-title":"Springer handbook of robotics","author":"H\u00e4gele","year":"2016"},{"key":"2024091413065525200_bib11","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.jechem.2023.10.032","article-title":"Challenges and opportunities for battery health estimation: Bridging laboratory research and real-world applications","volume":"89","author":"Han","year":"2024","journal-title":"Journal of Energy Chemistry"},{"key":"2024091413065525200_bib12","doi-asserted-by":"crossref","first-page":"119496","DOI":"10.1016\/j.ins.2023.119496","article-title":"Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine","volume":"648","author":"Han","year":"2023","journal-title":"Information Sciences"},{"key":"2024091413065525200_bib13","first-page":"1322","article-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning","volume-title":"Proceedings of the 2008 IEEE International Joint Conference on Neural Networks","author":"He","year":"2008"},{"key":"2024091413065525200_bib14","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.jmsy.2022.12.001","article-title":"In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks","volume":"66","author":"He","year":"2023","journal-title":"Journal of Manufacturing Systems"},{"key":"2024091413065525200_bib15","article-title":"GANs trained by a two time-scale update rule converge to a local Nash equilibrium","volume-title":"Advances in neural information processing systems 30 (NIPS 2017)","author":"Heusel","year":"2017"},{"key":"2024091413065525200_bib16","doi-asserted-by":"crossref","first-page":"108463","DOI":"10.1016\/j.apacoust.2021.108463","article-title":"Intelligent worm gearbox fault diagnosis under various working conditions using vibration, sound and thermal features","volume":"186","author":"Karabacak","year":"2022","journal-title":"Applied Acoustics"},{"key":"2024091413065525200_bib17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3146389","article-title":"On fault detection and diagnosis in robotic systems","volume":"51","author":"Khalastchi","year":"2018","journal-title":"Acm Computing Surveys"},{"key":"2024091413065525200_bib18","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s10115-014-0754-y","article-title":"Online data-driven anomaly detection in autonomous robots","volume":"43","author":"Khalastchi","year":"2015","journal-title":"Knowledge and Information Systems"},{"key":"2024091413065525200_bib19","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1093\/jcde\/qwad031","article-title":"MPARN: Multi-scale path attention residual network for fault diagnosis of rotating machines","volume":"10","author":"Kim","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"Kingma","key":"2024091413065525200_bib20"},{"key":"2024091413065525200_bib21","doi-asserted-by":"crossref","first-page":"106587","DOI":"10.1016\/j.ymssp.2019.106587","article-title":"Applications of machine learning to machine fault diagnosis: A review and roadmap","volume":"138","author":"Lei","year":"2020","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2024091413065525200_bib22","first-page":"9159","article-title":"Unsupervised representation learning of image-based plant disease with deep convolutional generative adversarial networks","volume-title":"Proceedings of the 2018 37th Chinese Control Conference (CCC)","author":"Li","year":"2018"},{"key":"2024091413065525200_bib23","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1109\/TII.2023.3262854","article-title":"Intelligent machinery fault diagnosis with event-based camera","volume":"20","author":"Li","year":"2024","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"2024091413065525200_bib24","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/s10845-020-01579-w","article-title":"A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis","volume":"32","author":"Luo","year":"2021","journal-title":"Journal of Intelligent Manufacturing"},{"article-title":"Conditional generative adversarial nets","year":"2014","author":"Mirza","key":"2024091413065525200_bib25"},{"key":"2024091413065525200_bib26","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.isatra.2021.11.019","article-title":"A deep transferable motion-adaptive fault detection method for industrial robots using a residual-convolutional neural network","volume":"128","author":"Oh","year":"2022","journal-title":"ISA Transactions"},{"key":"2024091413065525200_bib27","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1093\/jcde\/qwad076","article-title":"Multi-head de-noising autoencoder-based multi-task model for fault diagnosis of rolling element bearings under various speed conditions","volume":"10","author":"Park","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024091413065525200_bib28","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1109\/TVCG.2016.2570755","article-title":"Approximated and user steerable tSNE for progressive visual analytics","volume":"23","author":"Pezzotti","year":"2016","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"2024091413065525200_bib29","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.jmsy.2018.04.004","article-title":"Quick health assessment for industrial robot health degradation and the supporting advanced sensing development","volume":"48","author":"Qiao","year":"2018","journal-title":"Journal of Manufacturing Systems"},{"key":"2024091413065525200_bib30","first-page":"11","article-title":"Harmonic drive gear failures in industrial robots applications: An overview","volume-title":"Proceedings of the European Conference of the PHM Society 2021","author":"Raviola","year":"2021"},{"key":"2024091413065525200_bib31","article-title":"Improved techniques for training GANs","volume-title":"Advances in neural information processing systems","author":"Salimans","year":"2016"},{"key":"2024091413065525200_bib32","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.compind.2019.01.001","article-title":"Generative adversarial networks for data augmentation in machine fault diagnosis","volume":"106","author":"Shao","year":"2019","journal-title":"Computers in Industry"},{"key":"2024091413065525200_bib33","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.ins.2020.07.014","article-title":"RCSMOTE: Range-controlled synthetic minority over-sampling technique for handling the class imbalance problem","volume":"542","author":"Soltanzadeh","year":"2021","journal-title":"Information Sciences"},{"key":"2024091413065525200_bib34","doi-asserted-by":"crossref","first-page":"113294","DOI":"10.1016\/j.measurement.2023.113294","article-title":"A survey of mechanical fault diagnosis based on audio signal analysis","volume":"220","author":"Tang","year":"2023","journal-title":"Measurement"},{"key":"2024091413065525200_bib35","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/TII.2019.2912809","article-title":"Data-driven gearbox failure detection in industrial robots","volume":"16","author":"Vallachira","year":"2020","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"2024091413065525200_bib36","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/0278-6125(94)90036-1","article-title":"Augmented timed petri nets for modeling, simulation, and analysis of robotic systems with breakdowns","volume":"13","author":"Venkatesh","year":"1994","journal-title":"Journal of Manufacturing Systems"},{"key":"2024091413065525200_bib37","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.jmsy.2012.06.005","article-title":"Current envelope analysis for defect identification and diagnosis in induction motors","volume":"31","author":"Wang","year":"2012","journal-title":"Journal of Manufacturing Systems"},{"key":"2024091413065525200_bib38","doi-asserted-by":"crossref","first-page":"106333","DOI":"10.1016\/j.asoc.2020.106333","article-title":"Imbalanced sample fault diagnosis of rotating machinery using conditional variational auto-encoder generative adversarial network","volume":"92","author":"Wang","year":"2020","journal-title":"Applied Soft Computing"},{"key":"2024091413065525200_bib39","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1093\/jcde\/qwad081","article-title":"A diagnosis method for imbalanced bearing data based on improved SMOTE model combined with CNN-AM","volume":"10","author":"Wang","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2024091413065525200_bib40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2021.3126366","article-title":"Fault diagnosis of harmonic drive with imbalanced data using generative adversarial network","volume":"70","author":"Yang","year":"2021","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"2024091413065525200_bib41","doi-asserted-by":"crossref","first-page":"108151","DOI":"10.1016\/j.apacoust.2021.108151","article-title":"Fault diagnosis of planetary gearbox based on acoustic signals","volume":"181","author":"Yao","year":"2021","journal-title":"Applied Acoustics"},{"key":"2024091413065525200_bib42","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1007\/s10845-021-01862-4","article-title":"Autoencoder-based anomaly detection of industrial robot arm using stethoscope based internal sound sensor","volume":"34","author":"Yun","year":"2023","journal-title":"Journal of Intelligent Manufacturing"},{"key":"2024091413065525200_bib43","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.1016\/j.promfg.2020.05.147","article-title":"Development of internal sound sensor using stethoscope and its applications for machine monitoring","volume":"48","author":"Yun","year":"2020","journal-title":"Procedia Manufacturing"},{"key":"2024091413065525200_bib44","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.isatra.2021.02.042","article-title":"Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions","volume":"119","author":"Zhang","year":"2022","journal-title":"ISA Transactions"},{"key":"2024091413065525200_bib45","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.ymssp.2018.05.050","article-title":"Deep learning and its applications to machine health monitoring","volume":"115","author":"Zhao","year":"2019","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2024091413065525200_bib46","doi-asserted-by":"crossref","first-page":"107738","DOI":"10.1016\/j.ymssp.2021.107738","article-title":"Sound singularity analysis for milling tool condition monitoring towards sustainable manufacturing","volume":"157","author":"Zhou","year":"2021","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2024091413065525200_bib47","article-title":"HYPE: A benchmark for Human eYe Perceptual Evaluation of generative models","volume-title":"Advances in neural information processing systems 32 (Nips 2019)","author":"Zhou","year":"2019"},{"key":"2024091413065525200_bib48","doi-asserted-by":"crossref","first-page":"2116","DOI":"10.1007\/s11431-022-2129-9","article-title":"Harmonic reducer fault diagnosis for industrial robots based on deep learning","volume":"65","author":"Zhou","year":"2022","journal-title":"Science China-Technological Sciences"}],"container-title":["Journal of Computational Design and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jcde\/advance-article-pdf\/doi\/10.1093\/jcde\/qwae061\/58444884\/qwae061.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/4\/234\/59122029\/qwae061.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/4\/234\/59122029\/qwae061.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T13:25:30Z","timestamp":1726320330000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jcde\/article\/11\/4\/234\/7706325"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,3]]},"references-count":48,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,7,3]]}},"URL":"https:\/\/doi.org\/10.1093\/jcde\/qwae061","relation":{},"ISSN":["2288-5048"],"issn-type":[{"type":"electronic","value":"2288-5048"}],"subject":[],"published-other":{"date-parts":[[2024,8]]},"published":{"date-parts":[[2024,7,3]]}}}