کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6956364 1451868 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines
ترجمه فارسی عنوان
تشخیص گسل سیستم ترمز هیدرولیک خودرو با استفاده از ویژگی های آماری و پشتیبانی از ماشین های بردار
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volumes 52–53, February 2015, Pages 436-446
نویسندگان
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