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Jaybhaye, M. D.
- A Low Cost Aurdino Controlled Floor Mopping Robot
Abstract Views :207 |
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Authors
Affiliations
1 Dept. of Prod. Engg. & Industrial Mgmt. COEP, Pune, IN
1 Dept. of Prod. Engg. & Industrial Mgmt. COEP, Pune, IN
Source
International Journal of Engineering Research, Vol 5, No SP 2 (2016), Pagination: 319-321Abstract
The floor mopping robot is a upcoming application in service industry. Many researchers are working in this area of development and control of the cleaning robot. This paper focuses on new model development of floor mopping robot in particular at a optimum cost and high mechanical efficiency and also a new low cost algorithm for area filling. The motion of robot will be controlled by using two wheels coupled with stepper motors which will be controlled using Arduino board. Ultrasonic proximity sensors will be used for obstacle detection. The task of area filling, localisation and mapping will be carried out using the data from position encoders of motors, ultrasonic sensors, and a graphical user interface.Keywords
Mopping Robot, Area Filling Techniques, Mapping, Obstacle Avoidance.Full Text
- Application of Pugh Selection Matrix for Fuel Level Sensing Technology Selection
Abstract Views :168 |
PDF Views:0
Authors
Affiliations
1 Dept. of Prod. Engg. & Industrial Mgmt. College of Engineering, Pune, M.H., IN
1 Dept. of Prod. Engg. & Industrial Mgmt. College of Engineering, Pune, M.H., IN
Source
International Journal of Engineering Research, Vol 5, No SP 2 (2016), Pagination: 368-370Abstract
Technology selection is one of the most important step in Design Process. Choosing the right technology alternative, there is not always a single definite criterion of selection, and decision makers have to take into account a large number of criteria including technological, economic, ethical, political, legal, and social factors. The proper technology selection for Fuel Level Sensor using Pugh Selection Matrix for its application in Heavy Commercial Vehicles is discussed in this paper. In this paper, factors affecting sensor technology selection are identified. Various level sensing technologies are compared across these criteria using Pugh Selection Matrix. The entire procedure is illustrated and finally the best technology is selected for fuel level sensing for Heavy Commercial Vehicles.Keywords
Fuellevelsensor, Pugh Selection Matrix, Heavy Commercial Vehicles, Criteria.Full Text
- Vibration Signature Analysis of Two Stage Gearbox using Kurtosis, Skewness and Crest Factor
Abstract Views :208 |
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Authors
Affiliations
1 Mechanical Engineering Department, Marathwada Mitra Mandal’s College of Engineering, Pune, Maharashtra, IN
2 Production Engineering and Industrial Management. Department, College of Engineering, Pune, Maharashtra, IN
1 Mechanical Engineering Department, Marathwada Mitra Mandal’s College of Engineering, Pune, Maharashtra, IN
2 Production Engineering and Industrial Management. Department, College of Engineering, Pune, Maharashtra, IN
Source
Manufacturing Technology Today, Vol 18, No 5 (2019), Pagination: 28-33Abstract
In recent years, innovations and methodologies have been developed in mechanical equipment, mainly in rotating equipment, to increase the reliability of fault finding. World wide vibration indexes such as RMS, Kurtosis, etc. are widely accepted in industry and are also suggested by international standards. Even so, these parameters do not allow reliable diagnosis of the condition of the machinery. Their apparent simplicity of interpretation makes them more attractive. This work presents a discussion based on these traditional parameters about the diagnostic possibilities. The database used includes vibration signals of gears, taking into account different conditions of speeds and load. The results obtained show that these global parameters of vibration are limited in the exact diagnosis of fault, especially in the condition of initial faults. This method tries to acquire a baseline parameter that improves characterization of fault condition. The outcomes of velocity magnitude are compared with RMS, skewness and Kurtosis.Keywords
RMS, Kurtosis, Crest Factor, Condition Monitoring.
References
- Obuchowski, Jakub; Zimroz, Radoslaw; Wylomanska, Agnieszka; Blind equalization using combined skewness-kurtosis criterion for gearbox vibration enhancement, Measurement, 2016, Doi: http://dx.doi.org/10.1016/j.measurement.2016.03.034.
- Praveen kumar, T; Saimurugan, M; Krishnakumar, P; Ramachandran, KI: Fault diagnosis of automobile gearbox based on machine learning techniques, '12th Global congress on manufacturing and management, GCMM 2014, 'Procedia Engineering', vol. 97, 2014, 2092 – 2098.
- Wang, Tianyang; Chu, Fulei; Han, Qinkai; Kong, Yun: Compound faults detection in gearbox via meshing resonance and spectral kurtosis methods, 'Journal of Sound and Vibration', 2017, http://dx.doi.org/10.1016/j.jsv.2016.12.041.
- Klinchaeam, Songpon; Ajavakom, Nopdanai; Yongchareon, Withaya: Fault detection of a spur gear using vibration signal with multivariable statistical parameters, 'Songklanakarin J. Sci. Technol'. vol. 36, no. 5, 2014 563-568, Sep. - Oct. 2014.
- Shukla, Shrikant; Karma, Vijay Kumar: Fault Detection of Two Stage Spur Gearbox using Time Domain Technique: Effect of Tooth Breakage and Improper Chamfering, 'IJISET -International Journal of Innovative Science, Engineering & Technology', vol. 1, no. 4, 2014, 184-189.
- Zhi Qiang Chen, Chuan Li and Rene-Vinicio Sanchez (2015), Gearbox Fault Identification and Classification with Convolutional Neural Networks, 'Hindawi Publishing Corporation, Shock and Vibration', Article ID 390134.
- David G, Lewicki; Kelsen E LaBerge, Ryan T: Ehinger and Jason Fetty (2011), 'Planetary Gearbox Fault Detection Using Vibration Separation Techniques', NASA/TM—2011-217127