RMG_NDE_Disssertation

Code to support non-destructive evaluation of RMG cranes PhD dissertation

Overal Goals for Crane Data:

Show comparison of Beta Wavelet with other standard for catagorizing fualts
Compare standard Wavelet, with Fingerprint, with video, with image, with expert system, with straight signal

To do list for Beta Wavelet:

make it work
make real time analysis
compare against all options with real time analysis

To Do list for Crane Data Analysis:

Choose Random set from Repository
Parse Name to get accepted output vector
Filter out non-move data set
Train Models on data
- Data Prep:
  - Try un smoothed
  - Try smoothed with rolling average
  - Make fingerprints by dimmension
  - Make fingerprints by r
  - try smooth with kalman
  - set up wavelet low-pass filter
- Model TypesVideo and Image
  - Video:
    - Rolling, 3x100, 3x changing frame sizes
    - overlapping segments, 3x?? hoping down line
    - rolling fingerprints
      - Try many fingerprints
      - look at Beta, and classification as it is going
      - Features from live fingerprints
  - Image:
    - Fingerprint
    - 3 x 60k image
Examine differences of results

Rail LASER

Start data
Figure frequency needed
Specific test cases
- 'Singing track'
- Over center anchor rise
- Old, new, ground, rough, tamped, shakey

EFIT and related

Write code
Get code working
GPU parrallelization
Inner simulation space bundary conditions
Compare LASER measurement to EFIT

Name		Name	Last commit message	Last commit date
Latest commit History 190 Commits
FingerprintML		FingerprintML
FromOthers		FromOthers
Generative		Generative
LASER and EFIT Paper		LASER and EFIT Paper
Laser Code		Laser Code
MLphase2		MLphase2
Piecemeal		Piecemeal
Rail Charicterization Paper		Rail Charicterization Paper
SensorCode		SensorCode
Transformer		Transformer
.gitignore		.gitignore
00 EarlyFilterWork.ipynb		00 EarlyFilterWork.ipynb
01 Initial Analysis.ipynb		01 Initial Analysis.ipynb
01_SplitFullDayDataIntoMoves.py		01_SplitFullDayDataIntoMoves.py
02 KalmanFilter.ipynb		02 KalmanFilter.ipynb
02-Make3dFingerprintsFrom01.py		02-Make3dFingerprintsFrom01.py
03 Ridge Count on all.ipynb		03 Ridge Count on all.ipynb
03_LSTM_Predict_on_xFold.py		03_LSTM_Predict_on_xFold.py
04 2ndRoundAnalysis.ipynb		04 2ndRoundAnalysis.ipynb
05 AllFilesSummaryStatistics.ipynb		05 AllFilesSummaryStatistics.ipynb
05a SlickSummaryStatistics.ipynb		05a SlickSummaryStatistics.ipynb
05b Stats on Long Runs.ipynb		05b Stats on Long Runs.ipynb
06 Make Many Move Graphs.ipynb		06 Make Many Move Graphs.ipynb
06b Test Many Wavelets.ipynb		06b Test Many Wavelets.ipynb
07 Beta Wavelet.ipynb		07 Beta Wavelet.ipynb
08 Convolution Experiments.ipynb		08 Convolution Experiments.ipynb
08 Laser Tests.ipynb		08 Laser Tests.ipynb
08 Laser simulation analysis.ipynb		08 Laser simulation analysis.ipynb
09 Custum Convolution.ipynb		09 Custum Convolution.ipynb
10 Segment then 3 color.ipynb		10 Segment then 3 color.ipynb
10b No Segment then LSTM.ipynb		10b No Segment then LSTM.ipynb
10b Segment then Attention Errors.ipynb		10b Segment then Attention Errors.ipynb
10b Segment then LSTM Errors.ipynb		10b Segment then LSTM Errors.ipynb
10b3 Segment then small LSTM 32Node-Copy1.ipynb		10b3 Segment then small LSTM 32Node-Copy1.ipynb
10b3 Segment then small LSTM 32Node.ipynb		10b3 Segment then small LSTM 32Node.ipynb
10b3a LSTM 32Node load model and test.ipynb		10b3a LSTM 32Node load model and test.ipynb
10b4 Small LSTM predict future-Copy1.ipynb		10b4 Small LSTM predict future-Copy1.ipynb
10bSegLSTM.py		10bSegLSTM.py
10bSeg_DataPrep-Copy1.ipynb		10bSeg_DataPrep-Copy1.ipynb
10bSeg_DataPrep.ipynb		10bSeg_DataPrep.ipynb
10bSeg_DataPrep.py		10bSeg_DataPrep.py
10bSegmentAndAnomaly.py		10bSegmentAndAnomaly.py
10c RMOR Concept Development.ipynb		10c RMOR Concept Development.ipynb
10d tangents.ipynb		10d tangents.ipynb
11 ML Unsupervised segmentation.ipynb		11 ML Unsupervised segmentation.ipynb
13 Sort the results from clustering.ipynb		13 Sort the results from clustering.ipynb
13asPython.py		13asPython.py
14 All Together Now.ipynb		14 All Together Now.ipynb
2 Laser readout fan turn on.zip		2 Laser readout fan turn on.zip
3ColorImagesMachineLearning.ipynb		3ColorImagesMachineLearning.ipynb
3dFingerprints-Image-save-images-Copy1.ipynb		3dFingerprints-Image-save-images-Copy1.ipynb
Animation from Data with Josh.gif		Animation from Data with Josh.gif
Batches Average to 0.ipynb		Batches Average to 0.ipynb
CoreFunctions.py		CoreFunctions.py
CountReadingsByLine.ipynb		CountReadingsByLine.ipynb
DWFT.py		DWFT.py
Experiments copy.ipynb		Experiments copy.ipynb
Experiments.ipynb		Experiments.ipynb
From_TF_site.ipynb		From_TF_site.ipynb
GraphMaking.py		GraphMaking.py
Prospectus.mplstyle		Prospectus.mplstyle
PyTorch Encoder Decoder Attempt.ipynb		PyTorch Encoder Decoder Attempt.ipynb
PyTorchTry.py		PyTorchTry.py
PyTorchTry2.py		PyTorchTry2.py
PytorchTS_Try.py		PytorchTS_Try.py
README.md		README.md
SPSS.py		SPSS.py
Save3DImages-Jay.py		Save3DImages-Jay.py
SciClone_FirstCut.ipynb		SciClone_FirstCut.ipynb
SciClone_FirstCut.py		SciClone_FirstCut.py
SciClone_Transformer_Classification.ipynb		SciClone_Transformer_Classification.ipynb
Segment3ColorFP.ipynb		Segment3ColorFP.ipynb
Segment3ColorFP.py		Segment3ColorFP.py
SegmentLSTMyDim.py		SegmentLSTMyDim.py
SegmentLSTMzDim.py		SegmentLSTMzDim.py
SegmentationExperiments.ipynb		SegmentationExperiments.ipynb
SensorLocations.csv		SensorLocations.csv
SensorStatsSmall.csv		SensorStatsSmall.csv
Sort_Folder.ipynb		Sort_Folder.ipynb
Speaker Noise for testing wavelets and laser stand.ipynb		Speaker Noise for testing wavelets and laser stand.ipynb
Split_File.ipynb		Split_File.ipynb
TF_Segmentation.py		TF_Segmentation.py
Test Analysis.py		Test Analysis.py
TestAnalysis.py		TestAnalysis.py
The Plan.ipynb		The Plan.ipynb
Track Sensor Analysis.py		Track Sensor Analysis.py
UnZip-Data.ipynb		UnZip-Data.ipynb
animation copy.gif		animation copy.gif
animation-Date.gif		animation-Date.gif
animation.gif		animation.gif
attention.py		attention.py
lstm_encoder_decoder.py		lstm_encoder_decoder.py
plotting.py		plotting.py
tictoc.py		tictoc.py
track_memory.py		track_memory.py

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RMG_NDE_Disssertation

Overal Goals for Crane Data:

To do list for Beta Wavelet:

To Do list for Crane Data Analysis:

Rail LASER

EFIT and related

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danchendrickson/RMG_NDE_Disssertation

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RMG_NDE_Disssertation

Overal Goals for Crane Data:

To do list for Beta Wavelet:

To Do list for Crane Data Analysis:

Rail LASER

EFIT and related

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