Fault diagnosis in electrical motors through vibration monitoring using Fiber
Bragg Grating-based accelerometers
Name: LEANDRO CASSA MACEDO
Publication date: 17/10/2023
Advisor:
Name |
Role |
|---|---|
| ANSELMO FRIZERA NETO | Co-advisor * |
| ARNALDO GOMES LEAL JÚNIOR | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| ANSELMO FRIZERA NETO | Co advisor * |
| ARNALDO GOMES LEAL JÚNIOR | Advisor * |
| CAMILO ARTURO RODRIGUEZ DIAZ | Internal Examiner * |
Summary: Structural Health Monitoring (SHM) techniques have been explored in fault and
damage diagnosis in structures and machines. These techniques are explored within the scope of Industry 4.0 and Smart Cities, WHERE the data provided by SHM techniques are used in the development of predictive and preventive maintenance plans, avoiding catastrophic failures, reducing machinery downtime, and providing more security in the cities. Sensor developments play an important role in this scenario since these devices are responsible for turning physical measurements into data that are capable of being processed to provide data-based decisions in industrial processes and city management. Different types of sensors are developed to attend to industrial requirements, such as thermocouples for temperature measurements, accelerometers for acceleration measurements, and strain gauges for strain measurements. In this context, optical fiber sensors can offer some advantages for sensor ap-
plications: they can be immunity to electromagnetic interference (ideal for industrial harsh environments), can be easily embedded into structures since they are thin and flexible, can be multiplexed (i.e. produce multiple sensors in the same optical fiber cable), and can combine sensing and data transmission over long distances applications using the same optical fiber cable. In this work, a Fiber Bragg Grating-based accelerometer design is reported for machinery fault diagnosis. Different geometries are analyzed as candidates for developing FBG-based accelerometer projects. Through analytical models, the flexible hinge structure was selected based on the sensitivity and natural frequency features to attend to the project requirements. The geometric dimensions are then selected by a multi-objective optimization procedure,
in which a variety of combinations of geometric parameters are evaluated with respect to sensitivity and natural frequency. This procedure served as an efficient tool for varying different geometric parameters to find combinations that maximize sensitivity and natural frequency. Four structures are selected to compose this work and, before fabrication, they are analyzed using a Finite Element Modal Analysis. These results were compared to the analytical model results, implying relative errors of 23%, 33%, 14%, and 6% for accelerometers 1, 2, 3, and 4, respectively. These errors are related to idealizations assumed and neglected effects in the analytical models. The sensors were then fabricated and characterized. The experimental natural frequencies were 607.8 Hz, 366.7 Hz, 294.7 Hz, and 236.5 Hz for accelerome-
ters 1, 2, 3, and 4, respectively. The experimental sensitivities are characterized by the exciting frequencies of 17 Hz, 35 Hz, and 50 Hz. For 17 Hz, the experimental sensitivities were 180 pm/g, 690 pm/g, 380 pm/g, and 400 pm/g, for accelerometers 1, 2, 3, and 4, correspondingly. For 35 Hz, the experimental sensitivities were 150 pm/g, 510 pm/g, 290 pm/g, and 230 pm/g, for accelerometers 1, 2, 3, and 4, respectively. For 50 Hz, the experimental sensitivities were 120 pm/g, 410 pm/g, 150 pm/g, and 160 pm/g, for accelerometers 1, 2, 3, and 4, respectively. These sensors were applied in fault diagnosis experiments for 9 fault conditions, WHERE the
results were compared and validated by a commercial piezoelectric accelerometer. For all cases, the FBG-based accelerometer frequency vibration spectra were similar to the piezoelectric accelerometer measurements, and it was concluded that the projected accelerometers in this work identified correctly the vibration pattern in all fault conditions.
