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Jegadeeshwaran, R.
- Vibration based Brake Fault Diagnosis using Voting Feature Interval and Decision Tree with Histogram Features
Abstract Views :166 |
PDF Views:0
Authors
Affiliations
1 School of Mechanical and Building Sciences, VIT University, Chennai Campus, Chennai - 600127, Tamil Nadu, IN
1 School of Mechanical and Building Sciences, VIT University, Chennai Campus, Chennai - 600127, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 33 (2016), Pagination:Abstract
Objectives: The brake system is one of the major components used in automobiles which inhibits motion by absorbing energy from a moving system. So regular monitoring is essential in brake system which ensures not only vehicle safety but also human lives. Methods/Statistical Analysis: In this study, a vibration based fault diagnosis approach has been reported through machine learning approach. A hydraulic brake setup was fabricated and vibration signals under various fault conditions were extracted using accelerometer sensor with suitable frequency. These signals were compared with good range of signals and variation is analyzed through histogram feature extraction, selection and classification of machine learing scenario. Findings: Histogram features were extracted by separation of signals into different bin ranges among which bin with highest accuracy level is further processed through selection process of Decision Tree and 87.78% was the achieved accuracy in fault determination. In Voting Feature Interval (VFI) 85.64% was the accuracy attained in error identification. Application/Improvements: Since Decision Tree gives the better result in fault identification in brake fault diagnosis of this study, it can be further improved by varying the frequency ranges of signals, so each and every variation in signals are noted. Moreover improvement in accuracy level can also be achieved in future by increasing number of samples percondtion of brake system.Keywords
Decision Tree, Histogram Features, Machine Learning, Vibration Signals, Voting Feature Interval- Vibration Based Condition Monitoring of a Hydraulic Brake System through Statistical Learning Approaches: A Review
Abstract Views :163 |
PDF Views:0
Authors
Affiliations
1 School of Mechanical and Building Science, VIT University Chennai Campus, Chennai - 600127,Tamil Nadu, IN
1 School of Mechanical and Building Science, VIT University Chennai Campus, Chennai - 600127,Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 48 (2016), Pagination:Abstract
Background/Objectives: To study the recent development for monitoring the condition of a hydraulic brake system using statistical learning approaches. Methods/Statistical Analysis: Machine fault diagnosis is one of the condition monitoring approaches used to monitor the condition of machinery. For brake fault diagnosis, many conventional techniques have been reported in literature. In recent days, statistical learning approaches like, naïve bayes, decision tree, bayes net, best first tree, support vector machines, K Star have been successfully used for the fault diagnosis study. Findings: Keeping in mind the end goal to distinguish the most plausible deficiencies prompting to disappointment, numerous strategies in particular, like thermal image mapping, oil particle analysis, acoustic emission signal analysis, vibration analysis have been used for analyzing the data. Among these, vibration signal has been conveniently used for many fault diagnosis study. The same vibration signal can be used for the brake fault diagnosis study. Then these vibration data are processed using shortterm Fourier transform, high-resolution spectral analysis, waveform analysis, wavelet analysis, wavelet transform, etc. The results of such analysis are used to analyze the causes of failures. Recent advancement is the application of statistical approach for analyzing the data. This study presents a brief review about the possibilities for implementing the recent statistical learning approaches for monitoring the condition of the brake system. Application/Improvements: Number of new statistical learning approaches like nested dichotomy, clonal selection classification algorithm, Artificial Immune Recognition System (AIRS) algorithm can be used for the brake fault diagnosis study.Keywords
Brake System, Condition Monitoring, Fault Diagnosis, Statistical Learning, Vibration Signal.- Vibration based Fault Diagnosis of Automobile Hydraulic Brake System using Fuzzy Logic with Best First Tree Rules
Abstract Views :220 |
PDF Views:156
Authors
Affiliations
1 School of Mech. and Building Sciences, VIT University, Chennai Campus, Chennai, IN
1 School of Mech. and Building Sciences, VIT University, Chennai Campus, Chennai, IN
Source
International Journal of Vehicle Structures and Systems, Vol 8, No 4 (2016), Pagination:Abstract
Brakes are indispensable element of automobile. It takes significant factor to slow down or stop vehicle at an instant which will help to prevent an incident or accident in panic scenario. In appropriate braking or breakdown in braking system may direct devastating effect on automobile as well as traveller safety. To enhance potential of braking system condition monitoring is drastic demand in automotive field. This research predominantly concentrates towards fault diagnosis of a hydraulic brake system with the principle of vibration signal. Feature extraction, feature selection and feature classification are the key measures under machine learning approach. Feature extraction can certainly accomplished by acquiring vibration from the system. Statistical features were for the fault diagnosis of hydraulic brake system. Best first tree algorithm will pick most effective features that will differentiate the fault conditions of the brake through given train samples. Fuzzy logic was selected as a classifier. In the present study, fuzzy classifier with the best first tree rules was used to perform the classification accuracy.Keywords
Statistical Features, Decision Tree, Feature Extraction, Fuzzy, Mamdani, Feature Selection.- Improving Program Outcome Attainments using Project Based Learning Approach for:UG Course-Mechatronics
Abstract Views :227 |
PDF Views:1
Authors
Abhishek D. Patange
1,
A. K. Bewoor
2,
S. P. Deshmukh
3,
S. S. Mulik
4,
S. S. Pardeshi
1,
R. Jegadeeshwaran
5
Affiliations
1 Mechanical Engineering Department, College of Engineering, Pune, IN
2 Mechanical Engineering Department, Cummins College of Engineering for Women, Pune, IN
3 Mechanical Engineering Department, Govt. College of Engineering, Karad, IN
4 Mechanical Engineering Department, R.M.D. Sinhgad School of Engineering, Pune, IN
5 School of Mechanical and Building Sciences, VIT University, Chennai, IN
1 Mechanical Engineering Department, College of Engineering, Pune, IN
2 Mechanical Engineering Department, Cummins College of Engineering for Women, Pune, IN
3 Mechanical Engineering Department, Govt. College of Engineering, Karad, IN
4 Mechanical Engineering Department, R.M.D. Sinhgad School of Engineering, Pune, IN
5 School of Mechanical and Building Sciences, VIT University, Chennai, IN
Source
Journal of Engineering Education Transformations, Vol 33, No SP 1 (2019), Pagination: 1-8Abstract
In the era of rapidly emerging technical society, engineering aspirants must be primed as globally competent. To respond, in recent years, inclusive reforms are being implemented to adopt Outcome-Based Education (OBE) approach and transform engineering education in India. The 12 Program Outcomes (POs) defined by NBA guides for development, execution and delivery of curriculum, evaluation of student learning and performance at various levels. The scope of mechatronics subject at colleges affiliated to Savitribai Phule Pune University (SPPU) in 2015 course was mostly restricted to theoretical and study approach, which do not exhibit involvement of students in creative, inventive and innovative thinking. This motivates to adopt Project Based Learning (PBL) at undergraduate level. Three large classes of 70+ students are grouped in to 3-5 students per batch. Project phases are defined; direct and indirect assessments are mapped with outcomes and it is carried out using pre- and post-intervention survey of students. It is observed that, the presented PBL framework has served as an efficient pedagogy. This approach not only ensured holistic development, teamwork, sustainability, improved higher-order cognitive skills, learning ability, soft skills, self-efficacy and communication but also accumulated near about 60 innovative prototypes in a mechatronics laboratory. It is projected that, PBL could enable students to acquire lifelong learning to tackle new difficulties arise in corporate/non-corporate life, thinking on future modification, filing a patent, converting prototype into commercial product.Keywords
Program Outcomes, Project-Based Learning, Mechatronics.References
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