A Signal Pattern Extraction Method Useful for Monitoring the Condition of Actuated Mechanical Systems Operating in
Adriana Munteanu1, Mihaita Horodinca1, Neculai-Eduard Bumbu1
1Faculty of Machines Manufacturing and Industrial Management, "Gheorghe Asachi" Technical University of Iasi, 700050 Iasi, Romania.
Sensors (Basel, Switzerland)
|February 26, 2025
Summary
This study introduces a novel method for condition monitoring of mechanical systems using signal pattern analysis. The technique effectively identifies and characterizes rotating part behavior in steady-state operation.
Area of Science:
- Mechanical Engineering
- Signal Processing
- Condition Monitoring
Background:
- Mechanical systems generate complex signals during steady-state operation.
- These signals contain periodic components that can indicate the health of rotating parts.
- Existing methods may struggle to isolate these subtle periodic patterns.
Purpose of the Study:
- To present a new approach for condition monitoring of actuated mechanical systems in steady-state.
- To characterize the state of rotating parts via periodic signal components.
- To develop a method for extracting time-domain patterns from sensor signals.
Main Methods:
- Utilizing arithmetic averaging of signal samples at regular intervals.
- Applying the method to sensor signals from a lathe headstock gearbox.
- Analyzing active electrical power, vibration, and angular speed signals.
Main Results:
- Successfully extracted time-domain patterns representing periodic components.
- Demonstrated the method's effectiveness for condition monitoring experimentally.
- Identified relevant patterns indicative of rotating part behavior within the gearbox.
Conclusions:
- The proposed arithmetic averaging method is effective for condition monitoring.
- This approach enables the extraction of characteristic patterns from steady-state signals.
- The technique offers a valuable tool for diagnosing the condition of rotating machinery.
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