Development of Capacitive Imaging measurement methods for non-destructive testing applications
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Development of Capacitive Imaging measurement methods for non-destructive testing applications
This thesis work has as its objective the study of non-destructive techniques (NDT), that is techniques capable of obtaining information from a measured object without damaging it. In particular, the activity focused on the analysis, development, and comparison of different measurement techniques for Capacitive Imaging (CI) to define, characterize and detect defects in dielectric materials such as polymers, ceramics, pyrex. The application of materials on these, combined with the possibility of simpler configurations from a practical point of view, makes this technique rather versatile than the other non-destructive ones. The theoretical aspects related to the problem were initially addressed, simulating different configurations of the measurement setup to evaluate their sensitivity and accuracy. Subsequently, the experimental setup was carried out, totally managed by Python script, including the definition and generation of the excitation signals, the acquisition and processing of the digital output signals of the capacitive sensor. For each measurement configuration, the results obtained in terms of sensitivity were experimentally compared.
To get a local copy up and running follow these simple example steps.
This is a list of things you need for use the software and how to install them.
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Python3
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Driver and software of TiePie (mod. HS5) at: https://www.tiepie.com/en/usb-oscilloscope/handyscope-hs5#downloads
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Install the Python bindings by executing:
pip install python-libtiepie
more information here.
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Install packages manually:
- Pandas
or
pip install pandas
conda install pandas
- Numpy reference here
or
pip install numpy
conda install numpy
- Scipy reference here
pip install scipy
- Matplotlib reference here
pip install matplotlib
- GitPython reference here
pip install gitpython
- PyUsb reference here
pip install pyusb
- Pandas
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...or you can use the requirements file:
pip3 install -r requirements.txt
- Clone the repo
git clone https://github.com/DeanSupertramp/pyTiePie.git
- project: contains scripts written to work with TiePie.
- libtiepie: TiePie's Python module.
- example: contains example for TiePie written in Python.
- images: contains images useful for the repository or output graphs of Python's script.
- utils: contains scripts, Python's module, tools and simulations:
- Circuit sensitivity analysis respect to a capacity variation, simulating the use of an ADC for acquisition
- Impedance measurement with R series
- Calculate the voltage difference measured for a given variation in capacitance
- Simulate the quantization of the ADC
- Apply lock-in
- Derive the phasors at the various frequencies and therefore dC at the various frequencies by comparing the estimated dC with the theoretical simulated one
- Impedance measurement with Wheatstone bridge
- Simulate both the reference capacitor on a healthy point and in the air
- Repeat the analysis for the estimate of dC
- Data elaboration and manipulation
- Signal filtering (Butterworth)
- Lock-in
- Model fitting
- Extrapolation of the capacity value
- Plotting
- Methods of data acquisition
- Live
- Offline (from data pre-saved)
- Generation of a map of capacity value from a generic UUT (Unit Under Test)
- CLI implementation
- Parsing input
- TiePie basic control (using libtiepie module and variables)
- Implement data processing and capacity analysis in the cli
See the open issues for a full list of proposed features (and known issues).
Distributed under the MIT License. See LICENSE.txt for more information.
Andrea Alecce - @DeanSupertramp - andrealecce3@gmail.com
Project Link: https://github.com/DeanSupertramp/pyTiePie