Lakshmikanthan C. currently serves as Assistant Professor at Department of Mechanical Engineering, School of Engineering, Coimbatore Campus. His areas of research include CAD/CAM and CFD.
Qualification : M. Tech. (Engineering Design)
Area of Specialisation
- CAD
- Automotive NVH
Research Expertise
- Psycho Acoustic Studies
- Pass-by-Noise and Vehicle Noise.
- Noise Source Detection
Ongoing Research and Other Activities
- Psycho acoustic study of vehicle noise.
- Pass-by-noise reduction in Automotive vehicles
- Consultancy work with OEMs in vehicle related noise and vibration problems.
- Exhaust sound design for Euro VI vehicles.
Teaching
- Vehicle Dynamics
- Chassis and Transmission System
- Noise, Vibration and Harshness (NVH) Practical
Publications
| Year of Publication | Title |
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2019 |
R. Vankayala, Saravanan R., and Lakshmikanthan C., “Reduction of Noise in The Vehicle Cabin by Using Natural Fibres with Polyurethane and Comparison with Other acoustic Materials”, IOP Conference Series: Materials Science and Engineering, vol. 577, p. 012013, 2019.[Abstract] As natural fibres are noise-absorbing materials, biodegradable and renewable by using natural fibres such as betel nut, sugarcane fibres are combing with polyurethane for the automobile application to reduce cabinet noise of the vehicle, which currently contains traditional materials such as foams, glass, metals and plastics that are difficult to recycle. Four samples of natural fibres were prepared with different quantities of betel nut & sugarcane ratios of 35: 35, 50: 20, 55: 15, 60: 10. Polyurethane is common with 30% of all samples. The sound absorption coefficient (SAC) in the material was tested by using impedance tube and compared with other acoustic material like nitrile rubber, nonwoven polyester fabric and glass wool. It was observed that betel nut & sugarcane showing better SAC than other acoustic materials mainly at lower and higher frequency 60% betel, 10% sugarcane & 30% polyurethane showing better sound absorption level. More »» |
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2019 |
J. Annamalai and Lakshmikanthan C., “An Optimized Computer Vision and Iimage Processing Algorithm for Unmarked Road Edge Detection”, Advances in Intelligent Systems and Computing, vol. 900, pp. 429-437, 2019.[Abstract] A report published by Ministry of Road Transport and Highways, Government of India, claims Mohan (IATSS Res 33:75–79, 2009 [1]) that around 17 deaths happen every hour by road accidents. Driver negligence is one of the major contributors to road accidents. Deviating from the road and hitting roadside objects can be avoided with early warning systems. Lane departure warning systems are inadequate to find the road edges, because of its indefinite nature. In this paper, an efficient algorithm has been proposed to identify the road edges. The algorithm was developed as a combination of concepts like HSV, thresholding, Canny edge detection, and random sample consensus (RANSAC) algorithm. Initially, the sample dataset was used to validate the algorithm. In the second iteration, real-time video was used to validate the algorithm. The algorithm was able to identify the road edge at various light conditions and various vehicle speeds. The algorithm was also developed further to calculate the distance from the center line and the road width. More »» |
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2016 |
Lakshmikanthan C., Ramesh N., Sane O, Lakshminarasimhan A., and Parthasarathy S.P., “An Assessment of in-cabin noise and vibration transfer in a hatchback”, International Journal of Vehicle Noise and Vibration, vol. 12, pp. 292 – 301, 2016.[Abstract] India, being the fastest growing economy, has an ever increasing demand for transportation leading to increased competition between the manufacturers. Boundaries of the various parameters were pushed for saving time to market and cost. Among these parameters, the in-cabin noise level plays a major role in defining the comfort of the passengers. This article assesses the in-cabin noise levels of one of the entry level vehicles from a manufacturer. The whole study was conducted in two parts. The first part involving overall measurement of the noise levels in the vehicle and the second part is to study the major noise transfer mechanism. An acceleration test was first conducted to study the overall noise level. Various test conditions are designed to predict the major contributor of the in-cabin noise as part of the second step. The major contributing factors are engine noise and road and tyre interaction noise. Tests were repeated to eliminate the road noise. Noise levels measured in the cabin show that the airborne noise is the major contributor. More »» |
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2015 |
Jolly J. and Lakshmikanthan C., “Experimental determination of gasoline vapor loss due to sloshing in a fuel tank”, International Journal of Applied Engineering Research (IJAER), vol. 10, no. 17, pp. 38202 – 38204, 2015. |
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2015 |
Nair A.J. and Lakshmikanthan C., “Head gasket failure analysis”, International Journal of Applied Engineering Research (IJAER), vol. 10, no. 17, pp. 38187 – 38191, 2015. |
| Year of Publication | Title |
|---|---|
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2016 |
Lakshmikanthan C., Dr. K. I. Ramachandran, Sharma, A., and Subramaniam, S. Devi, “A Handheld device to capture Fundus images”, 2016.[Abstract] The present invention relates to a hand held device used to capture fundus images. More particularly the intention provides a low cost hand held device to image entire fundus either it is central or peripheral. The invention is smart phone based hand held device capable of capturing regions of peripheral most retina such as ora serrata and further till pars plana apart from central fundus. Advantageously, the present invention is operated by single hand. |
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