Machine Learning For Bearing Fault Detection | Feature Extraction | Data Preprocessing | PART-1
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- Опубликовано: 1 ноя 2024
- #machinelearningtutorial #machinelearning #DatadrivenPrognostics #DatadrivenFaultDiagnosis
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This video series demonstrates the use of a machine-learning algorithm to predict the faults in a bearing. This first section will see the data preprocessing part and how we can read the data from the given text file and do the feature extraction from the obtained data to get meaningful features. In this case, we have extracted time domain features from the given acceleration data and saved them in a CSV file. In the later part of this series, we will use the preprocessed data to train machine learning algorithms that will be able to predict the faults in a Bearing.
github-
github.com/moh...
dataset-
www.kaggle.com...
reference-
github.com/bis...
LinkedIn - / balyogi-mohan-dash
sir, you applied the PCA method can u tell me how to apply the SVM method
Thanks a lot for the video. Excellent work
EXcelente video saludos desde PERU :)
Thank you so much sir for this wonderful guidance, can i get that data set file on my email, their is no such a dataset file in that link
I am sorry akash, it's been so long since I have made this video. I currently don't have it
Hello Great explanations sir, could you please provide Part 2
ruclips.net/video/Mqi-plJR56g/видео.html
Can you please check the dataset know the files are completely different showing in bearing dataset related temp and all that
If possible send the proper link of dataset which is used in videos
Hi, you are right. I will try to update the files. Thank you for informing
@@Mohankumardash thank you for checking
Is it possible for you to share the files via drive link or other resources which are used in videos
@@Mohankumardash or can you gmail me all the files I will ping you on Gmail
can you please provide the part 2 of this section
ruclips.net/video/Mqi-plJR56g/видео.html
Hi, I am doing my bachelor thesis in this field and I would like to ask you if there is a way to get in contact with you. I would appreciate if I could use the bearing data you are using. Best regards, Alexander
Hi, here's my email, mohandash96@gmail.com
Updated Dataset: www.kaggle.com/datasets/vinayak123tyagi/bearing-dataset
Thank you
Hi Sir, do you have feature extraction code for "Test 1" I can refer to. I am actually confused what to do when two channels are extracting data points for each bearing. You have only discussed about feature extraction of "Test 2 datasets" where only single channels was devoted to each bearings.
Well...i just used the first channel only..for the first bearing
@@Mohankumardash ohh okay makes sense, thanx
So meaning you used the first four columns only of the Test 1 datasets ? were the first four columns for channel 1 ?
why in syntax 17 just go to df2, df3 and df4, because on my laptop I can't find the directory
same issue
@@JourneyBeyond59 You have created only one csv file for bearing 1 in the previous cell. while slicing the data, you have taken only bearing 1's data at index 0 so you should probably change your code from there if you want to include 4 bearings.
voice quality is very poor , could you please tell me what kind of data or tests were performed
when I run it says name dataset is not defined
You may have to change the location of the csv file in the python code according to your system
what i do