FYP Executive Summary
Title:
analysis an acoustic emission
in machining process
name: nur syazwani
binti che azli
matrix id no:fb11024
supervisor: dr mohd azmir bin
mohd azhan
2. Problem statement
Acoustic emission
is the wave sound produced when any materials undergoes stress or internal
change ,or as a result of external force. There are several method used to
analyze and generate acoustic emission in machining process. AE system usually
use in machining to monitor tool wear and failures. We will use AE technique
because AE detects the activities inside the materials while other methods are
usually examine the structural of the materials.Besides, this research also
about how to maintain the quality on machining process between tool and
materials. A group of AE sensors or transducers will be mounted in certain area
to detect the signal wave from machining process. Through the signal produced,
the data will be analyze and observe.
3. Objectives
(minimum 3)
1.
To monitor the acoustic emission within materials during stress, failures or
crack propagation.
2.
To analyze and generate the signal waveform from AE system.
3.
To verify the analysis data through Acoustic Emission Technique.(AE).
4. Scope of
research
The project will
start by searching and reading the related journals and articles on acoustic
emission especially in machining process. Then, determine the requirements
materials and components needed for project’s experiments such as AE Sensor,
amplifier and so on. After that, decide which analysis method will be used to
analyze the acoustic emission data from AE system. After that , We will conduct
an experiment on acoustic emission in machining process.All details
explanations will be discussed and write in project report.
5. Expected outcome
The expected outcome will be based on the experiment data on acoustic
emission signal waveform. From the data, we analyze and observe the signal waveform
from machining process. The AE
method capture certain parameters including AE counts,peaks level and energies. Based on the data, we will know how
the acoustic emission reacts on
tool and materials or work pieces. From the result, we will have a suggestions and a recommend for the project analysis
method.
