{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T04:14:57Z","timestamp":1760328897633,"version":"3.41.2"},"reference-count":25,"publisher":"ASME International","issue":"8","license":[{"start":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T00:00:00Z","timestamp":1717718400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.asme.org\/publications-submissions\/publishing-information\/legal-policies"}],"content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Hydraulic cylinders with higher stages of extraction are extensively used in earthmoving and heavy machines due to their longer stroke, shorter retracted length, and high-end performance. The rigorous and long hours of operations make cylinders prone to internal leakage, which visually remains unnoticeable. This paper presents the conceptualization and realization of a newly developed 210 bar high-pressure hydraulic test rig actuated by a two-stage hydraulic cylinder. Experiments have been carried out to acquire pressure signals for two different leakage conditions (3% and 5% for moderate and severe leakages respectively) in the ramp wave motion of the cylinder. A decline in the working pressure and the piston velocity by approximately 10% and 45% for these leakage conditions respectively is noted. The time\u2013frequency analysis infers these signals contain low-frequency components. For the automated leakage detection, a new iterative probability-based, transductive semi-supervised support vector machine (TS-SVM) is proposed capable of learning with limited datasets in several iterations. TS-SVM classifies the internal leakage with 100% accuracy in four iterations and utilizes only 64% of the total training data.<\/jats:p>","DOI":"10.1115\/1.4065526","type":"journal-article","created":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T14:25:53Z","timestamp":1715783153000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":5,"title":["Semi-Supervised Approach Using Transductive Support Vector Machine for Internal Leakage Detection in Two-Stage Hydraulic Cylinder"],"prefix":"10.1115","volume":"24","author":[{"given":"Jatin","family":"Prakash","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Indore System Dynamics Lab, Department of Mechanical Engineering, , Indore, Madhya Pradesh 453552 , India"}]},{"given":"Ankur","family":"Miglani","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Indore Microfluidics and Droplet Dynamics Lab, Department of Mechanical Engineering, , Indore, Madhya Pradesh 453552 , India"}]},{"given":"P. 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