{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T06:24:31Z","timestamp":1762410271846,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,10]],"date-time":"2023-11-10T00:00:00Z","timestamp":1699574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001409","name":"DST\u2014Science and Engineering Research Board","doi-asserted-by":"publisher","award":["ECR\/2016\/002068"],"award-info":[{"award-number":["ECR\/2016\/002068"]}],"id":[{"id":"10.13039\/501100001409","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The brake system requires careful attention for continuous monitoring as a vital module. This study specifically focuses on monitoring the hydraulic brake system using vibration signals through experimentation. Vibration signals from the brake pad assembly of commercial vehicles were captured under both good and defective conditions. Relevant histograms and wavelet features were extracted from these signals. The selected features were then categorized using Nested dichotomy family classifiers. The accuracy of all the algorithms during categorization was evaluated. Among the algorithms tested, the class-balanced nested dichotomy algorithm with a wavelet filter achieved a maximum accuracy of 99.45%. This indicates a highly effective method for accurately categorizing the brake system based on vibration signals. By implementing such a monitoring system, the reliability of the hydraulic brake system can be ensured, which is crucial for the safe and efficient operation of commercial vehicles in the market.<\/jats:p>","DOI":"10.3390\/s23229093","type":"journal-article","created":{"date-parts":[[2023,11,10]],"date-time":"2023-11-10T05:04:56Z","timestamp":1699592696000},"page":"9093","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Comprehensive Approach for Detecting Brake Pad Defects Using Histogram and Wavelet Features with Nested Dichotomy Family Classifiers"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3877-3063","authenticated-orcid":false,"given":"Sakthivel","family":"Gnanasekaran","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Vellore Institute of Technology, Chennai 600127, India"},{"name":"Centre for Automation, Vellore Institute of Technology, Chennai 600127, India"}]},{"given":"Lakshmi Pathi","family":"Jakkamputi","sequence":"additional","affiliation":[{"name":"Centre for Automation, Vellore Institute of Technology, Chennai 600127, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4144-827X","authenticated-orcid":false,"given":"Jegadeeshwaran","family":"Rakkiyannan","sequence":"additional","affiliation":[{"name":"Centre for Automation, Vellore Institute of Technology, Chennai 600127, India"}]},{"given":"Mohanraj","family":"Thangamuthu","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India"}]},{"given":"Yogesh","family":"Bhalerao","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering and Design, School of Engineering, University of East Anglia, Norwich Research Park, Norwich NR4 7TIJ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,10]]},"reference":[{"key":"ref_1","unstructured":"National Highway Traffic Safety Administration (2015). 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