Abstract:
This study presents the use of acoustic emission (AE) analysis in combination with signal
processing and LabVIEW software for monitoring 4 different types of oils in different conditions.
AE signals were collected using a free filed microphone 4188 with good frequency range placed
near the valve train, and the signals were conditioned using a signal conditioner to amplify the
signal. The amplified signals were then processed using Fast Fourier Transform (FFT) analysis
with National Instruments DAQ cards and LabVIEW software to extract features related to valve
train behavior i.e. engine sound, frictional torque etc. The results showed that AE analysis using
LabVIEW and signal processing techniques can effectively detect and characterize valve train
behavior under various operating conditions. Then investigates the effect of different engine oils
on the behavior of engine valve trains using acoustic emission (AE) analysis and FFT analysis
with LabVIEW software. Four different types of engine oils of the same grades were tested on a
single-cylinder four-stroke engine with four valves. AE signals were collected using a microphone
and amplified using a signal conditioner, and then analyzed using FFT analysis with National
Instruments DAQ cards and LabVIEW software to extract peak values related to valve train
behavior. The results show that the different types of engine oils have a significant effect on the
peak values of the AE signals, which is indicative of valve train behavior and from this behavior
the frictional torque can be find out[1]. The study demonstrates the potential of AE analysis and
FFT analysis with LabVIEW software as a valuable tool for evaluating the performance of engine
oils on engine valve train behavior.
