Design & Implementation of Automatic Machine Condition Monitoring and Maintenance System in Limited Resource Situations
Description
The different properties of the collected data are given shortly: 5. Data Types: Vibration data of three different types of faults occur in Rotating motor/devices 6. Data length: 1 seconds 7. Rotations/Second: 48.33 8. Data acquisition system: ESP32, gyro acceleration sensor, SD card, OLED display. 9. Initial data dimension: 1600 rows, 4 columns. Initially, we computed the average of columns containing axis values at different frequencies. Subsequently, to form the dataset, we calculated the partial derivative of the averages concerning frequency, representing changes in data magnitude relative to different frequencies. This data, processed with Machine Learning models, demonstrated that different faults produce varying magnitudes at different frequencies, exhibiting distinct patterns. Structural looseness, misalignment, and bearing problems manifested differing magnitudes at different frequencies, contributing to distinct overall patterns . Structures: Folders (Structural_Looseness, Bearing, Misalignment) contains the Raw CSV Files containing vibration signals of faulty machines. The MatLab Files Features and Models containing the features, visualization, spectrum and trained models with the features.
Files
Steps to reproduce
To reproduce this data or using the data, one should use the .MAT files. Both the Eaw data and Precessed data are stored there. Performing Automatic Spectrums Analysis, Using different Machine Learning Models can be usefull with the data. The data acquisition process is described in detail in the section on data collection. • Circuit Overview: The circuit collects acceleration/vibration data using an ESP32 microcontroller and a gyro acceleration sensor. • ESP32 Functionality: ESP32 serves as the circuit's brain, controlling operations. It interfaces with the gyro acceleration sensor and handles analogue-to-digital conversion (ADC). • Calibration Process: The analogue voltage signal from the gyro sensor is calibrated to establish a relationship between voltage readings and acceleration/vibration values (calibration equation 6.1). • OLED Display Interface: The circuit incorporates a 1.3-inch OLED display module for user configuration. Settings like data acquisition time can be adjusted through a push-button switch connected to the microcontroller. • Data Acquisition Process: After configuring settings, the microcontroller initiates data collection based on user-defined time. ADC samples the analogue voltage signal at a high frequency (typically 1600 samples per second). • Data Storage: Collected data is temporarily saved in EPROM during acquisition for data integrity. After completion, it is stored on an SD card in CSV format for easy access by a computer. • Circuit Operation Control: The ESP32 program controls circuit operations, including peripheral initialization, sensor calibration, display module configuration, timer setup, and data acquisition management. • Algorithm Integration: The code includes algorithms converting analogue voltage signals to acceleration/vibration values based on calibration equations. It also facilitates data storage on the SD card in CSV format.