Research Activities

Production and testing of bio-diesel from Calophyllum inophyllum (Punnakka)

An alternate fuel was indigenously developed and demonstrated using Bio-diesel developed from the base oil KAMANI (BALLNUT / Alexandrian Laurel).  The fuel was tested on a Twin Cylinder Compression Ignition Engine as well as Single cylinder compression Ignition engine.  The Bio-Diesel had a yield of 95 % from its base oil. The cost of production can be substantially reduced if produced commercially in large quantity.  The new Bio-Diesel was also seen to have lower emission level and reduced vibration effects when tested against normal diesel. This Bio-Diesel can be an effective alternative fuel to be used in pumpsets, generators and agricultural equipment.  It can also aid in electrification programmes.  The Bio-Diesel can be used in automobiles either in pure form or in blends with normal diesel for best results.

Condition Monitoring using LabView based vibration analysis Vibration based data acquisition system with DAQ card and LabView interface was setup in the laboratory.  As a case study, the vibration analysis of Kirloskar, twin cylinder, four-stroke diesel engine was carried out.  The vibration signals in the time domain, frequency domain and time-frequency domain (wavelet analysis) were carried out to predict the performance of the engine.

• Design of power re-circulating gear test rig

To conduct gear test, a versatile power re-circulating gear test rig was designed.  The test rig is capable of simulating actual running conditions and is suitable for conducting accelerated tests.  The power requirement for this test rig is minimal.  The test rig along with the LabView based data acquisition system can effectively monitor the performance of gears subjected to bending and contact fatigue, in laboratory simulated actual working conditions.  The fabrication and assembly of the test rig would be carried out in the next phase.  Vibration analysis on a rolling contact fatigue test rig was conducted by the same group of students in the Mechanical Engineering Department at IIT, Madras and the results were presented in a National Conference at Amal Jyothi College of Engineering, Kanjirapally.  

• Condition monitoring of bearing using LabView and artificial neural networks

Vibration based data acquisition system with DAQ card and LabView interface was used to train an artificial neural network.  Two faulty bearings and a good bearing were tested, and the difference in vibration characteristics was effectively used to train the artificial neural network.  This trained network is capable of distinguishing between a good and faulty bearing, and also differentiate the type of fault based on the vibration amplitudes.

• Vibration signature analysis on 3-phase induction motor

Vibration based data acquisition system with DAQ card and LabView interface was setup to perform vibration signature analysis.  The vibration characteristics from a 3-phase induction motor were used to train an artificial neural network, for different simulated conditions, by varying the voltage and also by single phasing.  The trained network is capable of distinguishing between a good motor and a faulty motor.