scispace - formally typeset
Journal ArticleDOI

Vibration Based Fault Diagnosis Study of an Automobile Brake System Using K Star (K*) Algorithm – A Statistical Approach

R. Jegadeeshwaran, +1 more
- 31 Mar 2014 - 
- Vol. 4, Iss: 1, pp 44-56
About
This article is published in Recent Patents on Signal Processing.The article was published on 2014-03-31. It has received 12 citations till now. The article focuses on the topics: Fault (power engineering) & Brake.

read more

Citations
More filters
Journal ArticleDOI

Vibration based brake health monitoring using wavelet features: A machine learning approach:

TL;DR: The application of wavelets has been investigated for diagnosing the faults on a hydraulic brake system of a light motor vehicle using the vibration signals acquired from a brake test setup through a piezoelectric type accelerometer.
Journal ArticleDOI

Tool condition monitoring using Random forest and FURIA through statistical learning

TL;DR: The vibration signals were captured with good and defective tools under different operating conditions, and the extracted features were classified using the various Machine learning models such as random forest, fuzzy unordered rule induction, and Hoeffding tree for predicting the tool condition.
Journal ArticleDOI

Friction stir welding tool condition monitoring using vibration signals and Random forest algorithm – A Machine learning approach

TL;DR: The vibration analysis based on FSW tool condition monitoring using machine learning algorithms such as decision tree, Logistic Model Tree (LMT), Hoeffeding, and Random forest gives better results.
Journal ArticleDOI

Condition monitoring of carbide and non-carbide coated tool insert using decision tree and random tree – A statistical learning

TL;DR: The following work deals to establish a simple and efficient automatic method to detect and monitor the tool condition and two machine learning classifiers namely the decision tree and the random tree were used for the classification process.
Related Papers (5)