{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T19:56:06Z","timestamp":1776110166770,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Technology Development Program to Solve Climate Changes through the National Research Foundation of Korea (NRF) funded by the Ministry of Science","award":["ICT (2021M1A2A2043894)"],"award-info":[{"award-number":["ICT (2021M1A2A2043894)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the growth of factory automation, deep learning-based methods have become popular diagnostic tools because they can extract features automatically and diagnose faults under various fault conditions. Among these methods, a novelty detection approach is useful if the fault dataset is imbalanced and impossible reproduce perfectly in a laboratory. This study proposes a novelty detection-based soft fault-diagnosis method for control cables using only currents flowing through the cables. The proposed algorithm uses three-phase currents to calculate the sum and ratios of currents, which are used as inputs to the diagnosis network to detect novelties caused by soft faults. Autoencoder architecture is adopted to detect novelties and calculate anomaly scores for the inputs. Applying a moving average filter to anomaly scores, a threshold is defined, by which soft faults can be properly diagnosed under environmental disturbances. The proposed method is evaluated in 11 fault scenarios. The datasets for each scenario are collected when an industrial robot is working. To induce soft fault conditions, the conductor and its insulator in the cable are damaged gradually according to the scenarios. Experiments demonstrate that the proposed method accurately diagnoses soft faults under various operating conditions and degrees of fault severity.<\/jats:p>","DOI":"10.3390\/s22051917","type":"journal-article","created":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T21:25:14Z","timestamp":1646169914000},"page":"1917","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Current Only-Based Fault Diagnosis Method for Industrial Robot Control Cables"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9230-4970","authenticated-orcid":false,"given":"Heonkook","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea"},{"name":"Hyundai Robotics Co., Ltd., 50, Techno Sunhwan-ro 3-gil, Yuga, Dalseong-gun, Daegu 43022, Korea"}]},{"given":"Hojin","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea"}]},{"given":"Sang Woo","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2606","DOI":"10.1109\/TIM.2017.2700178","article-title":"Multiple Chirp Reflectometry for Determination of Fault Direction and Localization in Live Branched Network Cables","volume":"66","author":"Chang","year":"2017","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Jacob, R.A., Senemmar, S., and Zhang, J. (2021, January 22\u201325). Fault Diagnostics in Shipboard Power Systems using Graph Neural Networks. Proceedings of the IEEE 13th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), Dallas, TX, USA.","DOI":"10.1109\/SDEMPED51010.2021.9605496"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"93","DOI":"10.4271\/2016-01-0065","article-title":"Locating Wire Short Fault for in-Vehicle Controller Area Network with Resistance Estimation Approach","volume":"9","author":"Du","year":"2016","journal-title":"SAE Int. J. Passeng. Cars Electron. Electr. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kim, H., Jeong, H., Lee, H., and Kim, S.W. (2021). Online and Offline Diagnosis of Motor Power Cables Based on 1D CNN and Periodic Burst Signal Injection. Sensors, 21.","DOI":"10.3390\/s21175936"},{"key":"ref_5","first-page":"179","article-title":"Fault diagnosis of industrial robot gears based on discrete wavelet transform and artificial neural network","volume":"58","author":"Jaber","year":"2016","journal-title":"Insight-Non-Destr. Test. Cond. Monit."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"191","DOI":"10.12700\/APH.17.1.2020.1.11","article-title":"Application of compensation algorithms to control the movement of a robot manipulator","volume":"17","author":"Shadrin","year":"2020","journal-title":"Acta Polytech. Hung."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1109\/TEMC.2018.2830404","article-title":"Never Trust a Cable Bearing Echoes: Understanding Ambiguities in Time-Domain Reflectometry Applied to Soft Faults in Cables","volume":"61","author":"Cozza","year":"2019","journal-title":"IEEE Trans. Electromagn. Compat."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/TIM.2018.2834179","article-title":"Condition Assessment of I&C Cables in Nuclear Power Plants via Stepped-Frequency Wave Form Reflectometry","volume":"68","author":"Lee","year":"2019","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Hu, S., Wang, L., Gao, C., Zhang, B., Liu, Z., and Yang, S. (2018). Non-Intrusive Cable Fault Diagnosis Based on Inductive Directional Coupling. Sensors, 18.","DOI":"10.3390\/s18113724"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1109\/JSEN.2013.2294193","article-title":"A New Algorithm for Wire Fault Location Using Time-Domain Reflectometry","volume":"14","author":"Shi","year":"2014","journal-title":"IEEE Sens. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2467","DOI":"10.1109\/TDEI.2018.007344","article-title":"Detection of Abnormality Occurring over the Whole Cable Length by Frequency Domain Reflectometry","volume":"25","author":"Ohki","year":"2018","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1082","DOI":"10.1109\/JSEN.2020.2997696","article-title":"Industrial Applications of Cable Diagnostics and Monitoring Cables via Time\u2013Frequency Domain Reflectometry","volume":"21","author":"Lee","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lee, C.K., and Chang, S.J. (2020). Fault Detection in Multi-Core C&I Cable via Machine Learning Based Time-Frequency Domain Reflectometry. Appl. Sci., 10.","DOI":"10.3390\/app10010158"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2482","DOI":"10.1109\/JSYST.2020.3010334","article-title":"Online Detection of Aircraft ARINC Bus Cable Fault Based on SSTDR","volume":"15","author":"Shi","year":"2021","journal-title":"IEEE Syst. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.1109\/TPWRD.2017.2665818","article-title":"Online Monitoring and Diagnosis of HV Cable Faults by Sheath System Currents","volume":"32","author":"Dong","year":"2017","journal-title":"IEEE Trans. Power Deliv."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1109\/JSYST.2018.2822549","article-title":"Fast Current-Only Based Fault Detection Method in Transmission Line","volume":"13","author":"Jarrahi","year":"2019","journal-title":"IEEE Syst. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1109\/JSEN.2006.874017","article-title":"The Invisible Fray: A Critical Analysis of the Use of Reflectometry for Fray Location","volume":"6","author":"Griffiths","year":"2006","journal-title":"IEEE Sens. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.sigpro.2013.12.026","article-title":"A Review of Novelty Detection","volume":"99","author":"Pimentel","year":"2014","journal-title":"Signal Process."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"132330","DOI":"10.1109\/ACCESS.2020.3010274","article-title":"Anomalous Example Detection in Deep Learning: A Survey","volume":"8","author":"Bulusu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1016\/j.patcog.2006.07.009","article-title":"Kernel PCA for Novelty Detection","volume":"40","author":"Hoffmann","year":"2007","journal-title":"Pattern Recognit."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1541880.1541882","article-title":"Anomaly Detection: A Survey","volume":"41","author":"Chandola","year":"2009","journal-title":"ACM Comput. Surv."},{"key":"ref_22","unstructured":"Kim, K., Shim, S., Lim, Y., Jeon, J., Choi, J., Kim, B., and Yoon, A. (May, January 26). RAPP: Novelty Detection with Reconstruction Along Projection Pathway. Proceedings of the International Conference on Learning Representations, Addis Ababa, Ethiopia."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5102","DOI":"10.1109\/JSEN.2020.3035754","article-title":"A Method of Fault Localization Within the Blind Spot Using the Hybridization Between TDR and Wavelet Transform","volume":"21","author":"Lee","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1049\/iet-gtd.2017.0670","article-title":"Equivalent Circuit and Calculation of Unbalanced Power in Three-Wire Three-Phase Linear Networks","volume":"12","author":"Diez","year":"2018","journal-title":"IET Gener. Transm. Distrib."},{"key":"ref_25","unstructured":"Rahman, M.A.A., and Ghosh, P.S. (2008, January 21\u201324). Diagnosis on MV XLPE Power Cable by Using Frequency Variance Leakage Current Analysis. Proceedings of the 2008 International Conference Condition Monitor Diagnosis, Beijing, China."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1017\/S1481803500013336","article-title":"Understanding Receiver Operating Characteristic (ROC) Curves","volume":"8","author":"Fan","year":"2006","journal-title":"Can. J. Emerg. Med."},{"key":"ref_27","unstructured":"Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A. (2017, January 4\u20139). Automatic Differentiation in Pytorch. NIPS-W. Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA."},{"key":"ref_28","unstructured":"Kingma, D.P., and Ba, J. (2015, January 7\u20139). Adam: A Method for Stochastic Optimization. Proceedings of the International Conference Learn, San Diego, CA, USA."},{"key":"ref_29","first-page":"2579","article-title":"Visualizing Data Using t-SNE","volume":"9","author":"Hinton","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/5\/1917\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:30:10Z","timestamp":1760135410000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/5\/1917"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,1]]},"references-count":29,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["s22051917"],"URL":"https:\/\/doi.org\/10.3390\/s22051917","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,1]]}}}