Special Issue "Vibration Sensor-Based Diagnosis Technologies and Systems: Part Ⅰ "
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 28143
Interests: digital signal processing; structural health monitoring; condition monitoring; artificial intelligence; vibration analysis; motor current signature analysis; adaptation of diagnosis systems
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Vibration sensor-based diagnosis technologies/systems have become very important for most industrial sectors and academic research. The most challenging topic in this field is vibration sensor-based diagnosis of machineries and structures.
The main challenges for these areas are as follows:
- Most industrial assets/machineries are working in non-stationary operations;
- Most excitations of engineering structures and, therefore, sensor outputs are non-stationary;
- One of the most important industrial requirements to vibration sensor-based diagnosis technologies is an effective diagnosis at early stage of damage development.
Addressing these challenges requires novel developments related to vibration sensors and intelligent vibration sensors, time-frequency, and non-linear higher-order spectral analysis of sensor data and adaptation of vibration sensor-based diagnosis technologies to non-stationary conditions, related to machineries and structures.
Therefore, this SI focuses on vibration sensor-based diagnosis technologies and systems for machineries/structures with the main attention to novel developments, related to: vibration sensors and intelligent vibration sensors, signal processing of sensor data, artificial intelligence for diagnosis decision making, and adaptation of vibration sensor-based diagnosis technologies to non-stationary conditions, related to machineries and structures.
This Special Issue will not cover non-novel “case study papers”. Potential authors need to make clear statements of paper novelties that should be based on comprehensive state-of-the art reviews.
The following keywords describe this SI:
- Classical, time-frequency, and higher-order signal processing for vibration sensor-based diagnosis technologies and systems;
- Artificial intelligence for vibration sensor-based diagnosis technologies and systems;
- Vibration sensor-based health diagnosis technologies and systems for engineering structures;
- Vibration sensor-based condition monitoring technologies and systems for machinery and complex electromechanical assets;
- Adaptive vibration sensor-based diagnosis technologies and systems;
- Vibration sensor-based diagnosis technologies and systems for linear and non-linear asset components/assets;
- Diagnostic feature extraction for vibration sensor-based diagnosis technologies and systems.
Prof. Dr. Len Gelman
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