Fault prediction performed from data on twenty vibration sensor readings
The dataset, FaultDataset.csv, consists of multiple rows, each containing twenty vibration sensor readings. The final column in the dataset is the target variable, where:
0 indicates that there was no fault with the machine at the time of the readings. 1 indicates that a fault was identified in the machine during the readings.
Our primary objective is to develop a predictive maintenance model using machine learning techniques. By analyzing the sensor data, we aim to create a classification model that can accurately predict whether a fault exists in the machinery based on the vibration sensor readings.