ABSTRACT
This DSP project is based on vibration analysis procedure. This method has a quick way to implement in the existing method by attaching accelerometers outside the gearbox. By using this method we can easily identify the condition of gearbox. This method completely depends on the vibration frequencies in the gearbox.
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INTRODUCTION
Gearboxes have been used from many years in all types of machines to control torque and angular velocity. Diagnosis helps detect and separate faults at early stage and making monitored systems for easy and perfect working. The data change is a competition conducted by the prognostics and health management society.
The main purpose of the modes is to study and evaluate different signal processing technique which can be used for gearbox diagnosis. And this system was them used for the data analysis competition to diagnose the 560 cases. The main aim of the system is to identify and separate the majority of the component faults that may in the competition.
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MATERIALS REQUIRED
In this DSP project, we have some equipment such as gearbox geometry, gears, bearings, fault modes, gear faults, bearing faults, data acquisition.
ADVANTAGES
It has low noise and low maintenance and high precision for gearboxes. For gears has non slip drives, large and constant velocity ratio of 60:1, gears are very strong it has the capacity to lift higher loads and longer services.
The bearing has less in dimension, easy to mount and erect, it provides good service and maintains neat or clean.
Reduced data redundancy, reduced updating errors and increased consistency, reduced data entry, storage, and flexible cost. Main advantage has facilitated the development of new applications program.
CONCLUSION
The used to create this theory is to diagnosis the system by using unlabeled data and having knowledge about the gearbox dimensions. In this unlabeled data, both the fault-free and fault cases should be included. And the system should recognize the fault case and separate the fault these are so many reasons why there is no accurate result in the competition. The fault mode error in the gearboxes is the most common fault. This system diagnosis detects and separates the faults which make us use the machine with safety.
To develop this project the sampling frequency is much higher than the interesting fault characteristic frequencies. By LPF (low pass filter) and downsampling the data initially become very faster and synchronized data will be reduced.
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